技术领域Technical Field
本申请涉及智能电网技术领域，特别是涉及一种设备启动的操作信息自动校核方法、装置、计算机设备、存储介质和计算机程序产品。The present application relates to the field of smart grid technology, and in particular to a method, device, computer equipment, storage medium and computer program product for automatically checking operation information started by a device.
背景技术Background Art
随着计算机技术的发展，出现了设备启动的操作信息校核技术，这个技术是指在设备启动前，对设备状态、操作参数、安全措施和启动程序等各项信息进行检查和验证，确保所有操作符合规定，并记录启动过程中的相关信息，以确保设备安全、正常运行。With the development of computer technology, the operation information verification technology for equipment startup has emerged. This technology refers to checking and verifying various information such as equipment status, operating parameters, safety measures and startup procedures before the equipment is started to ensure that all operations comply with regulations and record relevant information during the startup process to ensure the safety and normal operation of the equipment.
传统技术中，通常通过人工检查和机械仪表进行实现。操作员根据操作手册和检查清单，逐项核对设备状态、操作参数和安全措施，使用仪表测量电压、电流、温度等关键参数，确保符合启动要求，并记录检查结果和启动过程中的各项信息。然而通过人工检查和机器仪表的方式对设备启动的操作信息进行校核，在大量校核的过程中容易导致工人疲劳，进一步导致校核的过程中容易发生意外，导致对设备启动的操作信息校核的效率低下。In traditional technology, this is usually achieved through manual inspection and mechanical instruments. The operator checks the equipment status, operating parameters and safety measures item by item according to the operation manual and checklist, uses instruments to measure key parameters such as voltage, current, temperature, etc. to ensure that the startup requirements are met, and records the inspection results and various information during the startup process. However, the verification of the operation information of the equipment startup through manual inspection and machine instruments is prone to worker fatigue during the large-scale verification process, which further leads to accidents during the verification process, resulting in low efficiency in the verification of the operation information of the equipment startup.
发明内容Summary of the invention
基于此，有必要针对上述技术问题，提供一种能够提高对设备启动的操作信息校核的效率的设备启动的操作信息自动校核方法、装置、计算机设备、计算机可读存储介质和计算机程序产品。Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for automatically checking the operation information of device startup, which can improve the efficiency of checking the operation information of device startup, in order to solve the above technical problems.
第一方面，本申请提供了一种设备启动的操作信息自动校核方法。所述方法包括：In a first aspect, the present application provides a method for automatically checking operation information started by a device. The method comprises:
获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据；Obtain dispatching data, operation control data and protection signal data corresponding to each device in the power grid system;
融合所述调度数据、所述操作控制数据和所述保护信号数据中的异构数据，得到设备运行状态模型；fusing heterogeneous data in the scheduling data, the operation control data, and the protection signal data to obtain a device operation status model;
根据所述调度数据、所述操作控制数据和所述保护信号数据中的实时数据以及历史数据，生成各所述设备对应的连接关系图以及状态变化预测信息；Generate a connection relationship diagram and state change prediction information corresponding to each of the devices according to the real-time data and historical data in the scheduling data, the operation control data and the protection signal data;
将所述连接关系图以及所述状态变化预测信息输入至所述设备运行状态模型，得到初始操作信息校核信息；Inputting the connection relationship diagram and the state change prediction information into the equipment operation state model to obtain initial operation information verification information;
根据所述操作控制数据和所述保护信号数据中的实时数据，生成调整设别操作信息；Generate adjustment device operation information according to the operation control data and the real-time data in the protection signal data;
根据所述初始操作信息校核信息以及所述调整设别操作信息，确定所述电网系统的操作信息自动校核信息。According to the initial operation information verification information and the adjustment device operation information, the operation information automatic verification information of the power grid system is determined.
第二方面，本申请还提供了一种设备启动的操作信息自动校核装置。所述装置包括：In a second aspect, the present application also provides a device for automatically checking the operation information started by a device. The device comprises:
电网数据获取模块，用于获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据；A power grid data acquisition module is used to obtain the dispatching data, operation control data and protection signal data corresponding to each device in the power grid system;
状态模型得到模块，用于融合所述调度数据、所述操作控制数据和所述保护信号数据中的异构数据，得到设备运行状态模型；A state model obtaining module, used for fusing heterogeneous data in the scheduling data, the operation control data and the protection signal data to obtain a device operation state model;
第一数据处理模块，用于根据所述调度数据、所述操作控制数据和所述保护信号数据中的实时数据以及历史数据，生成各所述设备对应的连接关系图以及状态变化预测信息；A first data processing module, configured to generate a connection relationship diagram corresponding to each of the devices and state change prediction information according to the real-time data and historical data in the scheduling data, the operation control data and the protection signal data;
第二数据处理模块，用于将所述连接关系图以及所述状态变化预测信息输入至所述设备运行状态模型，得到初始操作信息校核信息；A second data processing module is used to input the connection relationship diagram and the state change prediction information into the equipment operation state model to obtain initial operation information verification information;
操作信息生成模块，用于根据所述操作控制数据和所述保护信号数据中的实时数据，生成调整设别操作信息；An operation information generating module, used for generating adjustment device identification operation information according to the operation control data and the real-time data in the protection signal data;
校核信息确定模块，用于根据所述初始操作信息校核信息以及所述调整设别操作信息，确定所述电网系统的操作信息自动校核信息。A verification information determination module is used to determine the automatic verification information of the operation information of the power grid system according to the initial operation information verification information and the adjustment device operation information.
第三方面，本申请还提供了一种计算机设备。所述计算机设备包括存储器和处理器，所述存储器存储有计算机程序，所述处理器执行所述计算机程序时实现以下步骤：In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:
获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据；Obtain dispatching data, operation control data and protection signal data corresponding to each device in the power grid system;
融合所述调度数据、所述操作控制数据和所述保护信号数据中的异构数据，得到设备运行状态模型；fusing heterogeneous data in the scheduling data, the operation control data, and the protection signal data to obtain a device operation status model;
根据所述调度数据、所述操作控制数据和所述保护信号数据中的实时数据以及历史数据，生成各所述设备对应的连接关系图以及状态变化预测信息；Generate a connection relationship diagram and state change prediction information corresponding to each of the devices according to the real-time data and historical data in the scheduling data, the operation control data and the protection signal data;
将所述连接关系图以及所述状态变化预测信息输入至所述设备运行状态模型，得到初始操作信息校核信息；Inputting the connection relationship diagram and the state change prediction information into the equipment operation state model to obtain initial operation information verification information;
根据所述操作控制数据和所述保护信号数据中的实时数据，生成调整设别操作信息；Generate adjustment device operation information according to the operation control data and the real-time data in the protection signal data;
根据所述初始操作信息校核信息以及所述调整设别操作信息，确定所述电网系统的操作信息自动校核信息。According to the initial operation information verification information and the adjustment device operation information, the operation information automatic verification information of the power grid system is determined.
第四方面，本申请还提供了一种计算机可读存储介质。所述计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现以下步骤：In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:
获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据；Obtain dispatching data, operation control data and protection signal data corresponding to each device in the power grid system;
融合所述调度数据、所述操作控制数据和所述保护信号数据中的异构数据，得到设备运行状态模型；fusing heterogeneous data in the scheduling data, the operation control data, and the protection signal data to obtain a device operation status model;
根据所述调度数据、所述操作控制数据和所述保护信号数据中的实时数据以及历史数据，生成各所述设备对应的连接关系图以及状态变化预测信息；Generate a connection relationship diagram and state change prediction information corresponding to each of the devices according to the real-time data and historical data in the scheduling data, the operation control data and the protection signal data;
将所述连接关系图以及所述状态变化预测信息输入至所述设备运行状态模型，得到初始操作信息校核信息；Inputting the connection relationship diagram and the state change prediction information into the equipment operation state model to obtain initial operation information verification information;
根据所述操作控制数据和所述保护信号数据中的实时数据，生成调整设别操作信息；Generate adjustment device operation information according to the operation control data and the real-time data in the protection signal data;
根据所述初始操作信息校核信息以及所述调整设别操作信息，确定所述电网系统的操作信息自动校核信息。According to the initial operation information verification information and the adjustment device operation information, the operation information automatic verification information of the power grid system is determined.
第五方面，本申请还提供了一种计算机程序产品。所述计算机程序产品，包括计算机程序，该计算机程序被处理器执行时实现以下步骤：In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:
获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据；Obtain dispatching data, operation control data and protection signal data corresponding to each device in the power grid system;
融合所述调度数据、所述操作控制数据和所述保护信号数据中的异构数据，得到设备运行状态模型；fusing heterogeneous data in the scheduling data, the operation control data, and the protection signal data to obtain a device operation status model;
根据所述调度数据、所述操作控制数据和所述保护信号数据中的实时数据以及历史数据，生成各所述设备对应的连接关系图以及状态变化预测信息；Generate a connection relationship diagram and state change prediction information corresponding to each of the devices according to the real-time data and historical data in the scheduling data, the operation control data and the protection signal data;
将所述连接关系图以及所述状态变化预测信息输入至所述设备运行状态模型，得到初始操作信息校核信息；Inputting the connection relationship diagram and the state change prediction information into the equipment operation state model to obtain initial operation information verification information;
根据所述操作控制数据和所述保护信号数据中的实时数据，生成调整设别操作信息；Generate adjustment device operation information according to the operation control data and the real-time data in the protection signal data;
根据所述初始操作信息校核信息以及所述调整设别操作信息，确定所述电网系统的操作信息自动校核信息。According to the initial operation information verification information and the adjustment device operation information, the operation information automatic verification information of the power grid system is determined.
上述一种设备启动的操作信息自动校核方法、装置、计算机设备、存储介质和计算机程序产品，通过获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据；融合调度数据、操作控制数据和保护信号数据中的异构数据，得到设备运行状态模型；根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，生成各设备对应的连接关系图以及状态变化预测信息；将连接关系图以及状态变化预测信息输入至设备运行状态模型，得到初始操作信息校核信息；根据操作控制数据和保护信号数据中的实时数据，生成调整设别操作信息；根据初始操作信息校核信息以及调整设别操作信息，确定电网系统的操作信息自动校核信息。The above-mentioned method, device, computer equipment, storage medium and computer program product for automatic verification of operation information initiated by a device obtain the dispatching data, operation control data and protection signal data corresponding to each device in the power grid system; integrate the heterogeneous data in the dispatching data, operation control data and protection signal data to obtain the device operation status model; generate the connection relationship diagram and state change prediction information corresponding to each device according to the real-time data and historical data in the dispatching data, operation control data and protection signal data; input the connection relationship diagram and state change prediction information into the device operation status model to obtain initial operation information verification information; generate adjustment device identification operation information according to the real-time data in the operation control data and protection signal data; determine the automatic verification information of the operation information of the power grid system according to the initial operation information verification information and the adjustment device identification operation information.
通过获取并融合电网系统中设备的调度数据、操作控制数据和保护信号数据，建立设备运行状态模型，生成设备连接关系图和状态变化预测信息，从而实现了对设备运行状态的精确监控和动态预测。基于实时和历史数据进行校核，有效提升了操作信息的准确性和及时性，减少了由于人工校核带来的错误风险和延迟问题。最终，通过自动校核操作信息，实现了电网系统操作的智能化管理，提高对设备启动的操作信息校核的效率，进而大幅提高了电网运行的安全性、稳定性和效率，能够迅速应对并预防潜在故障，保障电力供应的连续性和可靠性。By acquiring and integrating the dispatching data, operation control data and protection signal data of the equipment in the power grid system, establishing the equipment operation status model, generating the equipment connection relationship diagram and state change prediction information, it is possible to achieve accurate monitoring and dynamic prediction of the equipment operation status. Verification based on real-time and historical data effectively improves the accuracy and timeliness of operation information and reduces the risk of errors and delays caused by manual verification. Ultimately, by automatically verifying the operation information, the intelligent management of the power grid system operation is realized, and the efficiency of the operation information verification of the equipment startup is improved, thereby greatly improving the safety, stability and efficiency of the power grid operation, and being able to quickly respond to and prevent potential failures, ensuring the continuity and reliability of power supply.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1为一个实施例中一种设备启动的操作信息自动校核方法的应用环境图；FIG1 is a diagram showing an application environment of a method for automatically checking operation information started by a device in one embodiment;
图2为一个实施例中一种设备启动的操作信息自动校核方法的流程示意图；FIG2 is a schematic flow chart of a method for automatically checking operation information started by a device in one embodiment;
图3为一个实施例中状态变化预测信息得到方法的流程示意图；FIG3 is a schematic diagram of a flow chart of a method for obtaining state change prediction information in one embodiment;
图4为另一个实施例中状态变化预测信息得到方法的流程示意图；FIG4 is a schematic flow chart of a method for obtaining state change prediction information in another embodiment;
图5为一个实施例中算法结果判断方法的流程示意图；FIG5 is a schematic diagram of a flow chart of a method for determining an algorithm result in one embodiment;
图6为一个实施例中初始操作信息校核信息得到方法的流程示意图；FIG6 is a schematic diagram of a flow chart of a method for obtaining initial operation information verification information in one embodiment;
图7为一个实施例中优化操作信息自动校核信息得到方法的流程示意图；FIG7 is a schematic flow chart of a method for obtaining automatic verification information of optimization operation information in one embodiment;
图8为一个实施例中一种设备启动的操作信息自动校核装置的结构框图；FIG8 is a structural block diagram of an automatic verification device for operation information started by a device in one embodiment;
图9为一个实施例中计算机设备的内部结构图。FIG. 9 is a diagram showing the internal structure of a computer device in one embodiment.
具体实施方式DETAILED DESCRIPTION
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
本申请实施例提供的一种设备启动的操作信息自动校核方法，可以应用于如图1所示的应用环境中。其中，终端102通过网络与服务器104进行通信。数据存储系统可以存储服务器104需要处理的数据。数据存储系统可以集成在服务器104上，也可以放在云上或其他网络服务器上。服务器104从终端102处获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据；融合调度数据、操作控制数据和保护信号数据中的异构数据，得到设备运行状态模型；根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，生成各设备对应的连接关系图以及状态变化预测信息；将连接关系图以及状态变化预测信息输入至设备运行状态模型，得到初始操作信息校核信息；根据操作控制数据和保护信号数据中的实时数据，生成调整设别操作信息；根据初始操作信息校核信息以及调整设别操作信息，确定电网系统的操作信息自动校核信息。其中，终端102可以但不限于是各种个人计算机、笔记本电脑、智能手机、平板电脑、物联网设备和便携式可穿戴设备，物联网设备可为智能音箱、智能电视、智能空调、智能车载设备等。便携式可穿戴设备可为智能手表、智能手环、头戴设备等。服务器104可以用独立的服务器或者是多个服务器组成的服务器集群来实现。A method for automatically checking the operation information of a device startup provided in an embodiment of the present application can be applied in an application environment as shown in FIG. 1 . Among them, the terminal 102 communicates with the server 104 through a network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on a cloud or other network server. The server 104 obtains the dispatching data, operation control data, and protection signal data corresponding to each device in the power grid system from the terminal 102; integrates the heterogeneous data in the dispatching data, operation control data, and protection signal data to obtain the device operation status model; generates the connection relationship diagram and state change prediction information corresponding to each device according to the real-time data and historical data in the dispatching data, operation control data, and protection signal data; inputs the connection relationship diagram and the state change prediction information into the device operation status model to obtain the initial operation information verification information; generates the adjustment device identification operation information according to the real-time data in the operation control data and the protection signal data; determines the automatic verification information of the operation information of the power grid system according to the initial operation information verification information and the adjustment device identification operation information. The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.
在一个实施例中，如图2所示，提供了一种设备启动的操作信息自动校核方法，以该方法应用于图1中的服务器为例进行说明，包括以下步骤：In one embodiment, as shown in FIG. 2 , a method for automatically checking operation information started by a device is provided, and the method is described by taking the application of the method to the server in FIG. 1 as an example, including the following steps:
步骤202，获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据。Step 202: Obtain dispatch data, operation control data, and protection signal data corresponding to each device in the power grid system.
其中，调度数据可以是在电力系统中，各种设备（如发电机、变压器、输电线路等）在运行和管理过程中所生成和使用的数据信息。这些数据包括设备的运行状态、负荷情况、发电量、故障记录、维护计划等，通常由电力调度中心实时监控和记录，用于优化电网运行，确保电力供应的可靠性和稳定性，并进行故障诊断和预防维护。Among them, dispatch data can be data information generated and used by various equipment (such as generators, transformers, transmission lines, etc.) in the operation and management process of the power system. These data include the operating status, load conditions, power generation, fault records, maintenance plans, etc. of the equipment, which are usually monitored and recorded in real time by the power dispatch center to optimize the operation of the power grid, ensure the reliability and stability of power supply, and perform fault diagnosis and preventive maintenance.
其中，操作控制数据可以是在电力系统中，用于控制和操作各种设备（如发电机、变压器、开关、断路器等）的数据信息。这些数据包括开关状态、控制命令、设定参数、自动化控制指令等，通过这些数据。Among them, the operation control data can be data information used to control and operate various equipment (such as generators, transformers, switches, circuit breakers, etc.) in the power system. These data include switch status, control commands, set parameters, automation control instructions, etc.
其中，保护信号数据可以是在电力系统中，用于监测和保护各种设备（如发电机、变压器、输电线路等）的数据信息。这些数据包括电流、电压、功率、温度等实时监测值，以及故障检测信号、告警信息和保护装置的动作记录等。当电力设备出现异常或故障时，保护信号数据会触发保护装置自动采取措施，如断开电路或隔离故障区域，以防止设备损坏和扩大故障范围。Among them, protection signal data can be data information used to monitor and protect various equipment (such as generators, transformers, transmission lines, etc.) in the power system. These data include real-time monitoring values such as current, voltage, power, temperature, as well as fault detection signals, alarm information, and action records of protection devices. When power equipment is abnormal or fails, the protection signal data will trigger the protection device to automatically take measures, such as disconnecting the circuit or isolating the fault area, to prevent equipment damage and expand the scope of the fault.
具体地，从电网系统中各设备的传感器和监控系统中获取调度数据、操作控制数据和保护信号数据。这些数据包括设备的运行状态、调度计划、操作指令以及保护装置的状态和报警信息。通过数据采集终端，将实时数据传输至数据中心，并结合历史数据进行存储和处理。在数据中心，利用数据融合技术对这些异构数据进行统一处理和分析，确保数据的准确性和一致性。Specifically, dispatch data, operation control data, and protection signal data are obtained from the sensors and monitoring systems of each device in the power grid system. These data include the operating status of the equipment, dispatch plans, operation instructions, and the status and alarm information of the protection device. Through the data acquisition terminal, real-time data is transmitted to the data center and stored and processed in combination with historical data. In the data center, data fusion technology is used to uniformly process and analyze these heterogeneous data to ensure the accuracy and consistency of the data.
步骤204，融合调度数据、操作控制数据和保护信号数据中的异构数据，得到设备运行状态模型。Step 204: The heterogeneous data in the scheduling data, the operation control data and the protection signal data are integrated to obtain a device operation status model.
其中，设备运行状态模型可以是用数学、物理和计算方法构建的模型，用于描述和模拟设备在不同运行条件下的状态和行为。这个模型综合了设备的运行参数、历史数据、环境因素等，通过模拟和分析，可以预测设备的性能、诊断故障、优化操作和维护策略。Among them, the equipment operation status model can be a model built using mathematical, physical and computational methods to describe and simulate the status and behavior of the equipment under different operating conditions. This model integrates the equipment's operating parameters, historical data, environmental factors, etc. Through simulation and analysis, it can predict equipment performance, diagnose faults, and optimize operation and maintenance strategies.
具体地，对调度数据、操作控制数据和保护信号数据进行预处理，包括数据清洗、格式转换和时间同步等步骤，以确保数据的一致性和完整性。接着，利用数据融合算法，将这些异构数据整合在一起，提取设备运行的关键特征和参数。通过机器学习模型或基于物理机制的模型，对这些融合数据进行训练和建模，生成反映设备实际运行状态的设备运行状态模型，其中设备运行状态模型能够准确描述设备在不同操作条件下的性能和行为。Specifically, the dispatch data, operation control data and protection signal data are preprocessed, including data cleaning, format conversion and time synchronization, to ensure data consistency and integrity. Then, the data fusion algorithm is used to integrate these heterogeneous data and extract the key characteristics and parameters of equipment operation. These fused data are trained and modeled through machine learning models or models based on physical mechanisms to generate equipment operation status models that reflect the actual operation status of the equipment. The equipment operation status model can accurately describe the performance and behavior of the equipment under different operating conditions.
步骤206，根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，生成各设备对应的连接关系图以及状态变化预测信息。Step 206, generating a connection relationship diagram corresponding to each device and state change prediction information based on the real-time data and historical data in the dispatching data, operation control data and protection signal data.
其中，连接关系图可以是用图形化方式表示系统中各个元素之间连接和关系的图表。它展示了不同组件、节点或设备之间的相互连接和依赖关系，通过节点和连接线条直观地描绘出系统的结构和布局。连接关系图广泛应用于网络架构、电力系统、数据库设计等领域，帮助理解系统的整体架构、分析复杂的关系和优化系统设计。Among them, the connection diagram can be a diagram that graphically represents the connections and relationships between various elements in the system. It shows the interconnections and dependencies between different components, nodes or devices, and intuitively depicts the structure and layout of the system through nodes and connecting lines. Connection diagrams are widely used in network architecture, power system, database design and other fields to help understand the overall architecture of the system, analyze complex relationships and optimize system design.
其中，状态变化预测信息可以是基于当前状态数据和历史趋势，对设备、系统或过程未来可能的状态变化进行预测的数据信息。通过分析传感器数据、操作记录、环境条件等，使用预测模型和算法，可以提前识别潜在问题、预估性能变化、安排维护计划或调整操作策略。Among them, state change prediction information can be data information that predicts the possible future state changes of equipment, systems or processes based on current state data and historical trends. By analyzing sensor data, operation records, environmental conditions, etc., using prediction models and algorithms, potential problems can be identified in advance, performance changes can be estimated, maintenance plans can be arranged, or operation strategies can be adjusted.
具体地，从调度数据、操作控制数据和保护信号数据中提取实时数据和历史数据，并对其进行分析和处理，确定实时数据和历史数据分别对应的实时状态数据和历史状态数据。接着，利用图算法构建设备的连接关系图，明确各设备之间的相互关系和影响路径。在此基础上，应用时间序列分析和机器学习算法，综合实时状态数据和历史状态数据对设备的运行状态输入至模型中进行建模和训练，预测设备在不同运行条件下的状态变化。最终，生成各设备的状态变化预测信息，展示设备未来的运行趋势和可能出现的故障。Specifically, real-time data and historical data are extracted from dispatch data, operation control data, and protection signal data, and analyzed and processed to determine the real-time status data and historical status data corresponding to the real-time data and historical data, respectively. Then, the connection relationship diagram of the equipment is constructed using the graph algorithm to clarify the mutual relationship and influence path between the equipment. On this basis, time series analysis and machine learning algorithms are applied to integrate the real-time status data and historical status data to input the operating status of the equipment into the model for modeling and training, and predict the state changes of the equipment under different operating conditions. Finally, the state change prediction information of each device is generated to show the future operation trend and possible failures of the equipment.
步骤208，将连接关系图以及状态变化预测信息输入至设备运行状态模型，得到初始操作信息校核信息。Step 208: input the connection relationship diagram and the state change prediction information into the equipment operation state model to obtain initial operation information verification information.
其中，初始操作信息校核信息可以是对系统或设备在操作时输入的基础信息进行核对和验证的初始数据信息。校核过程确保设定的参数、配置和操作步骤准确无误，符合设计规范和操作要求。The initial operation information verification information may be initial data information for checking and verifying the basic information input during operation of the system or device. The verification process ensures that the set parameters, configurations, and operation steps are accurate and meet the design specifications and operation requirements.
具体地，将生成的设备连接关系图和状态变化预测信息的实时数据以及历史数据输入到设备运行状态模型中，以提供全面的运行状态背景。设备运行状态模型结合连接关系图中各个不同的点的实时数据以及历史数据，利用预测信息对设备的当前和未来状态进行评估，通过对比实时数据和预测数据，设备运行状态模型能够识别潜在的异常和偏差，生成初始操作信息校核信息。其中初始操作信息校核信息包括对当前操作的合理性检查和未来操作建议Specifically, the generated real-time data and historical data of the equipment connection diagram and state change prediction information are input into the equipment operation status model to provide a comprehensive operation status background. The equipment operation status model combines the real-time data and historical data of different points in the connection diagram, and uses the prediction information to evaluate the current and future status of the equipment. By comparing the real-time data and the prediction data, the equipment operation status model can identify potential anomalies and deviations and generate initial operation information verification information. The initial operation information verification information includes the rationality check of the current operation and future operation suggestions.
步骤210，根据操作控制数据和保护信号数据中的实时数据，生成调整设别操作信息。Step 210, generating adjustment device operation information according to the real-time data in the operation control data and the protection signal data.
其中，调整设别操作信息可以是对系统或设备在实际操作时输入的数据信息，用于调整初始操作信息校核信息，以更适应当前的应用场景。Among them, the adjustment of device operation information can be data information input into the system or device during actual operation, which is used to adjust the initial operation information verification information to better adapt to the current application scenario.
具体地，从操作控制数据和保护信号数据中提取实时数据进行解析和处理，识别设备的当前运行状态和操作行为。利用实时数据的动态分析方法，结合操作控制数据中的设备的操作规范和保护逻辑，生成调整设别操作信息。此调整设别操作信息包括实际对设备的当前操作状态、运行参数以及保护动作记录，Specifically, real-time data is extracted from the operation control data and protection signal data for analysis and processing to identify the current operating status and operation behavior of the equipment. The dynamic analysis method of real-time data is used, combined with the operation specifications and protection logic of the equipment in the operation control data, to generate adjustment equipment identification operation information. This adjustment equipment identification operation information includes the current operating status, operating parameters and protection action records of the actual equipment.
步骤212，根据初始操作信息校核信息以及调整设别操作信息，确定电网系统的操作信息自动校核信息。Step 212, determining the automatic calibration information of the operation information of the power grid system based on the initial operation information calibration information and the adjustment device operation information.
其中，操作信息自动校核信息可以是使用调整设别操作信息对初始操作信息校核信息进行调整后的校核信息，用于实际应用中对电网系统中各个继电器的进行调整。Among them, the automatic verification information of the operation information can be the verification information after adjusting the initial operation information verification information using the adjustment device operation information, which is used to adjust each relay in the power grid system in actual applications.
具体地，将初始操作信息校核信息与调整设别操作信息进行比对，识别出两者之间的差异和潜在的操作异常。然后，应用校核算法，对比分析两者之间的差异和潜在的操作异常，评估设备操作的准确性和一致性。通过对差异数据的进一步分析，确定是否存在需要调整的操作策略或参数。最终，生成电网系统的操作信息自动校核信息，提供详细的校核结果和建议。Specifically, the initial operation information verification information is compared with the adjusted operation information to identify the differences and potential operation anomalies between the two. Then, the verification algorithm is applied to compare and analyze the differences and potential operation anomalies between the two to evaluate the accuracy and consistency of equipment operation. Through further analysis of the difference data, it is determined whether there are operation strategies or parameters that need to be adjusted. Finally, the automatic verification information of the operation information of the power grid system is generated, providing detailed verification results and suggestions.
上述一种设备启动的操作信息自动校核方法中，通过获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据；融合调度数据、操作控制数据和保护信号数据中的异构数据，得到设备运行状态模型；根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，生成各设备对应的连接关系图以及状态变化预测信息；将连接关系图以及状态变化预测信息输入至设备运行状态模型，得到初始操作信息校核信息；根据操作控制数据和保护信号数据中的实时数据，生成调整设别操作信息；根据初始操作信息校核信息以及调整设别操作信息，确定电网系统的操作信息自动校核信息。In the above-mentioned method for automatic verification of operation information initiated by a device, the dispatching data, operation control data and protection signal data corresponding to each device in the power grid system are obtained; the heterogeneous data in the dispatching data, operation control data and protection signal data are integrated to obtain the device operation status model; the connection relationship diagram and state change prediction information corresponding to each device are generated according to the real-time data and historical data in the dispatching data, operation control data and protection signal data; the connection relationship diagram and state change prediction information are input into the device operation status model to obtain initial operation information verification information; the adjustment device identification operation information is generated according to the real-time data in the operation control data and the protection signal data; the automatic verification information of the operation information of the power grid system is determined according to the initial operation information verification information and the adjustment device identification operation information.
通过获取并融合电网系统中设备的调度数据、操作控制数据和保护信号数据，建立设备运行状态模型，生成设备连接关系图和状态变化预测信息，从而实现了对设备运行状态的精确监控和动态预测。基于实时和历史数据进行校核，有效提升了操作信息的准确性和及时性，减少了由于人工校核带来的错误风险和延迟问题。最终，通过自动校核操作信息，实现了电网系统操作的智能化管理，提高对设备启动的操作信息校核的效率，进而大幅提高了电网运行的安全性、稳定性和效率，能够迅速应对并预防潜在故障，保障电力供应的连续性和可靠性。By acquiring and integrating the dispatching data, operation control data and protection signal data of the equipment in the power grid system, establishing the equipment operation status model, generating the equipment connection relationship diagram and state change prediction information, it is possible to achieve accurate monitoring and dynamic prediction of the equipment operation status. Verification based on real-time and historical data effectively improves the accuracy and timeliness of operation information and reduces the risk of errors and delays caused by manual verification. Ultimately, by automatically verifying the operation information, the intelligent management of the power grid system operation is realized, and the efficiency of the operation information verification of the equipment startup is improved, thereby greatly improving the safety, stability and efficiency of the power grid operation, and being able to quickly respond to and prevent potential failures, ensuring the continuity and reliability of power supply.
在一个实施例中，如图3所示，根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，生成各设备对应的连接关系图以及状态变化预测信息，包括：In one embodiment, as shown in FIG3 , a connection relationship diagram corresponding to each device and state change prediction information are generated according to real-time data and historical data in the scheduling data, operation control data, and protection signal data, including:
步骤302，根据调度数据中的实时数据以及历史数据，生成初始设备连接关系图。Step 302: Generate an initial device connection relationship diagram based on the real-time data and historical data in the scheduling data.
其中，初始设备连接关系图可以是未被验证的连接关系图。The initial device connection relationship diagram may be an unverified connection relationship diagram.
具体地，从调度数据中提取实时数据和历史数据，并进行预处理以确保数据的完整性和一致性。同时利用图数据库技术，将各设备的交互信息和依赖关系进行建模，构建未被赋予意义的设备连接关系图。通过分析调度数据中实时数据和历史数据的设备通信和操作记录，识别设备之间的连接和相互作用，确定实时数据和历史数据在未被赋予意义的设备连接关系图节点和边的属性，生成一个具有动态更新的初始设备连接关系图。Specifically, real-time data and historical data are extracted from the scheduling data and preprocessed to ensure the integrity and consistency of the data. At the same time, the interactive information and dependency relationships of each device are modeled using graph database technology to construct a meaningless device connection relationship graph. By analyzing the device communication and operation records of real-time data and historical data in the scheduling data, the connections and interactions between devices are identified, and the attributes of the nodes and edges of the real-time data and historical data in the meaningless device connection relationship graph are determined, generating an initial device connection relationship graph with dynamic updates.
步骤304，根据调度数据中的实时数据，对初始设备连接关系图的连接关系进行跟新，得到设备对应的连接关系图。Step 304, updating the connection relationship of the initial device connection relationship diagram according to the real-time data in the scheduling data, and obtaining the connection relationship diagram corresponding to the device.
具体地，持续从调度数据中提取实时数据实时数据对初始设备连接关系图进行动态更新，分析新的调度信息，识别新增或变化的设备交互和依赖关系。通过图数据库技术和增量更新算法，实时调整设备之间的连接关系，添加新的连接、修改现有连接的属性或删除失效的连接。最终，生成一个准确反映当前设备状态和相互关系的设备的连接关系图Specifically, the real-time data is continuously extracted from the scheduling data to dynamically update the initial device connection relationship diagram, analyze new scheduling information, and identify new or changed device interactions and dependencies. Through graph database technology and incremental update algorithms, the connection relationship between devices is adjusted in real time, adding new connections, modifying the properties of existing connections, or deleting invalid connections. Ultimately, a connection relationship diagram of devices that accurately reflects the current device status and relationships is generated.
步骤306，将调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据输入至电网系统的设备状态实时预测模型，得到状态变化预测信息。Step 306: input the real-time data and historical data in the dispatching data, operation control data and protection signal data into the real-time prediction model of the equipment status of the power grid system to obtain the status change prediction information.
其中，设备状态实时预测模型可以是用于实时监测和预测电网设备（如发电机、变压器、输电线路等）实时运行状态的数学和计算模型。通过整合实时传感器数据、历史运行数据和环境条件等，模型能够预测设备的未来状态、识别潜在故障和性能下降。Among them, the real-time prediction model of equipment status can be a mathematical and computational model used to monitor and predict the real-time operating status of power grid equipment (such as generators, transformers, transmission lines, etc.) in real time. By integrating real-time sensor data, historical operating data, and environmental conditions, the model can predict the future status of the equipment and identify potential failures and performance degradation.
具体地，从调度数据、操作控制数据和保护信号数据中收集实时数据和历史数据后，输入到电网系统的设备状态实时预测模型中，设备状态实时预测模型利用机器学习和时间序列分析算法，对设备的实施运行模式和历史运行模式进行训练，并结合实时数据和历史数据进行动态预测。通过设备状态实时预测模型的计算，生成设备状态变化的预测信息，其中设备状态变化的预测信息包括未来可能的状态变化趋势和潜在的故障预警。Specifically, after collecting real-time data and historical data from dispatch data, operation control data, and protection signal data, they are input into the real-time prediction model of the equipment status of the power grid system. The real-time prediction model of the equipment status uses machine learning and time series analysis algorithms to train the implementation operation mode and historical operation mode of the equipment, and combines real-time data and historical data for dynamic prediction. Through the calculation of the real-time prediction model of the equipment status, the prediction information of the equipment status change is generated, where the prediction information of the equipment status change includes possible future status change trends and potential fault warnings.
本实施例中，通过生成和动态更新设备连接关系图，以及将实时和历史数据输入设备状态实时预测模型并获取状态变化预测信息，该方法显著提升了电网系统的监控和管理能力。具体而言，初始设备连接关系图为设备间的交互关系提供了清晰的全局视图，动态更新确保关系图始终反映最新的系统状态。结合设备状态实时预测模型，能够准确预测设备状态变化，提前识别潜在风险和故障。这种整合方法不仅提高了电网系统的运行可靠性和稳定性，还增强了其响应速度和维护效率，为智能化电网管理提供了强有力的支持。In this embodiment, by generating and dynamically updating the device connection relationship diagram, and inputting real-time and historical data into the real-time prediction model of device status and obtaining state change prediction information, the method significantly improves the monitoring and management capabilities of the power grid system. Specifically, the initial device connection relationship diagram provides a clear global view of the interaction relationship between devices, and dynamic updates ensure that the relationship diagram always reflects the latest system status. Combined with the real-time prediction model of device status, it is possible to accurately predict changes in device status and identify potential risks and faults in advance. This integration method not only improves the operational reliability and stability of the power grid system, but also enhances its response speed and maintenance efficiency, providing strong support for intelligent power grid management.
在一个实施例中，如图4所示，将调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据输入至电网系统的设备状态实时预测模型，得到状态变化预测信息，包括：In one embodiment, as shown in FIG4 , real-time data and historical data in the dispatching data, operation control data and protection signal data are input into the real-time prediction model of the equipment state of the power grid system to obtain state change prediction information, including:
步骤402，根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，确定实时数据的实时数据处理框架以及历史数据的历史数据处理框架。Step 402, determining a real-time data processing framework for real-time data and a historical data processing framework for historical data based on real-time data and historical data in the scheduling data, operation control data and protection signal data.
其中，实时数据处理框架可以是用于处理和分析实时生成的数据的平台或系统。它能够快速接收、处理和分析数据流，以便及时响应和决策。Among them, the real-time data processing framework can be a platform or system for processing and analyzing data generated in real time. It can quickly receive, process and analyze data streams for timely response and decision-making.
其中，历史数据处理框架可以是用于存储、处理和分析已经收集的历史数据的平台或系统。它能够对大量过去的数据进行批量处理和复杂分析，帮助用户发现长期趋势、模式和异常。Among them, the historical data processing framework can be a platform or system for storing, processing and analyzing the collected historical data. It can perform batch processing and complex analysis on a large amount of past data, helping users discover long-term trends, patterns and anomalies.
具体地，设计初始的实时数据处理框架，该框架采用流式处理技术，实时接收和处理调度数据、操作控制数据和保护信号数据中的实时数据，自适应快速响应系统变化建模，进行实时分析和决策，得到实时数据处理框架。同理，设计初始的历史数据处理框架，采用批处理技术，定期汇总和存储调度数据、操作控制数据和保护信号数据中的实时数据，自适应进行深度分析和趋势预测建模，得到历史数据处理框架。Specifically, an initial real-time data processing framework is designed, which uses stream processing technology to receive and process real-time data in dispatching data, operation control data, and protection signal data, adaptively and quickly respond to system change modeling, and conduct real-time analysis and decision-making to obtain a real-time data processing framework. Similarly, an initial historical data processing framework is designed, which uses batch processing technology to regularly summarize and store real-time data in dispatching data, operation control data, and protection signal data, and adaptively conducts in-depth analysis and trend prediction modeling to obtain a historical data processing framework.
步骤404，根据实时数据处理框架，对调度数据、操作控制数据和保护信号数据中的实时数据进行优化，得到优化实时数据。Step 404, according to the real-time data processing framework, the real-time data in the scheduling data, the operation control data and the protection signal data are optimized to obtain optimized real-time data.
具体地，利用实时数据处理框架对调度数据、操作控制数据和保护信号数据中的实时数据进行预处理，包括数据清洗、去重和格式转换等步骤，接着，通过流式处理技术，实时接收并分析这些数据，并同时使用数据过滤和聚合算法，去除噪声和冗余信息，提取关键特征和有用信息。随后，应用优化算法对处理后的数据进行进一步优化，生成优化后的实时数据。Specifically, the real-time data processing framework is used to pre-process the real-time data in the dispatching data, operation control data and protection signal data, including data cleaning, deduplication and format conversion. Then, the streaming technology is used to receive and analyze the data in real time, and the data filtering and aggregation algorithms are used to remove noise and redundant information and extract key features and useful information. Subsequently, the optimization algorithm is applied to further optimize the processed data to generate optimized real-time data.
步骤406，根据历史数据处理框架，对调度数据、操作控制数据和保护信号数据中的历史数据进行优化，得到优化历史数据。Step 406: Optimize the historical data in the dispatching data, operation control data and protection signal data according to the historical data processing framework to obtain optimized historical data.
具体地，利用历史数据处理框架对调度数据、操作控制数据和保护信号数据中的历史数据进行预处理，包括数据清洗、去重、格式转换和时间对齐等步骤，接着，通过批处理技术，对大规模历史数据进行汇总和存储，采用数据挖掘和分析算法，去除冗余信息和异常值，提取关键特征和趋势信息。然后，应用优化算法对处理后的历史数据进行进一步优化，生成优化后的历史数据。Specifically, the historical data processing framework is used to pre-process the historical data in the dispatching data, operation control data and protection signal data, including data cleaning, deduplication, format conversion and time alignment. Then, the batch processing technology is used to aggregate and store large-scale historical data, and data mining and analysis algorithms are used to remove redundant information and outliers, and extract key features and trend information. Then, the optimization algorithm is applied to further optimize the processed historical data to generate optimized historical data.
步骤408，根据优化实时数据以及优化历史数据，修改电网系统的设备状态实时预测模型的参数，使得设备状态实时预测模型输出状态变化预测信息。Step 408, modifying the parameters of the real-time prediction model of the equipment status of the power grid system according to the optimized real-time data and the optimized historical data, so that the real-time prediction model of the equipment status outputs the state change prediction information.
具体地，将优化实时数据和优化历史数据输入设备状态实时预测模型，通过设备状态实时预测模型的初始输出数据，自适应地进行至少一轮调整设备状态实时预测模型的参数，其中在调整模型参数的过程中，利用优化算法（如梯度下降法）在训练过程中不断调整模型参数，以最小化预测误差。通过多轮迭代和交叉验证，确保模型参数的最佳配置，最终更新后的设备状态实时预测模型能够准确输出状态变化预测信息。Specifically, the optimized real-time data and optimized historical data are input into the real-time prediction model of the equipment status, and the parameters of the real-time prediction model of the equipment status are adaptively adjusted for at least one round through the initial output data of the real-time prediction model of the equipment status, wherein in the process of adjusting the model parameters, the optimization algorithm (such as the gradient descent method) is used to continuously adjust the model parameters during the training process to minimize the prediction error. Through multiple rounds of iteration and cross-validation, the optimal configuration of the model parameters is ensured, and the updated real-time prediction model of the equipment status can accurately output the prediction information of the state change.
本实施例中，通过构建实时数据处理框架和历史数据处理框架，对调度数据、操作控制数据和保护信号数据进行优化处理，并据此调整电网系统的设备状态实时预测模型的参数，该方法显著提升了电网系统的数据处理和预测能力。具体来说，优化后的实时数据和历史数据保证了数据输入的高质量，使预测模型能够更加精准地反映设备的运行状态和变化趋势。通过动态调整模型参数，增强了模型的适应性和准确性。这一整合优化流程不仅提高了电网系统的运行效率和可靠性，还增强了故障预测和风险管理能力。In this embodiment, by constructing a real-time data processing framework and a historical data processing framework, the dispatching data, operation control data and protection signal data are optimized and processed, and the parameters of the real-time prediction model of the equipment status of the power grid system are adjusted accordingly. This method significantly improves the data processing and prediction capabilities of the power grid system. Specifically, the optimized real-time data and historical data ensure the high quality of data input, so that the prediction model can more accurately reflect the operating status and change trend of the equipment. By dynamically adjusting the model parameters, the adaptability and accuracy of the model are enhanced. This integrated optimization process not only improves the operating efficiency and reliability of the power grid system, but also enhances the fault prediction and risk management capabilities.
在一个实施例中，如图5所示，在根据优化实时数据以及优化历史数据，修改电网系统的设备状态实时预测模型的参数，使得设备状态实时预测模型输出状态变化预测信息步骤之后，方法还包括：In one embodiment, as shown in FIG5 , after the step of modifying the parameters of the real-time prediction model of the device state of the power grid system according to the optimization real-time data and the optimization historical data so that the real-time prediction model of the device state outputs the state change prediction information, the method further includes:
步骤502，如果状态变化预测信息或/和连接关系图未能满足预设需求，则根据状态变化预测信息调整连接关系图，得到调整关系图。Step 502: If the state change prediction information and/or the connection relationship diagram fails to meet the preset requirements, the connection relationship diagram is adjusted according to the state change prediction information to obtain an adjusted relationship diagram.
具体地，对比状态变化预测信息和连接关系图两者与预设需求之间的关系，评估其准确性和可靠性。如果未能满足预设需求，分析变化预测信息或/和连接关系图中的异常以及与预设需求偏差，识别可能影响设备连接关系的因素。接着，根据这些分析结果，调整连接关系图的结构和属性，重新定义设备之间的连接和相互作用，得到调整后的连接关系图。Specifically, the relationship between the state change prediction information and the connection relationship diagram and the preset requirements is compared to evaluate their accuracy and reliability. If the preset requirements are not met, the abnormalities in the change prediction information and/or the connection relationship diagram and the deviation from the preset requirements are analyzed to identify factors that may affect the device connection relationship. Then, based on these analysis results, the structure and attributes of the connection relationship diagram are adjusted, and the connections and interactions between devices are redefined to obtain an adjusted connection relationship diagram.
步骤504，根据调整关系图，调整实时数据处理框架以及历史数据处理框架，返回执行根据实时数据处理框架，对调度数据、操作控制数据和保护信号数据中的实时数据进行优化，得到优化实时数据的步骤，直到状态变化预测信息和连接关系图均能满足预设需求。Step 504, according to the adjustment relationship diagram, adjust the real-time data processing framework and the historical data processing framework, return to execute according to the real-time data processing framework, optimize the real-time data in the scheduling data, operation control data and protection signal data, and obtain the step of optimizing the real-time data until the state change prediction information and the connection relationship diagram can meet the preset requirements.
具体地，根据调整连接关系图，重新评估和调整实时数据处理框架和历史数据处理框架的参数和处理流程，应用调整后的两个数据处理框架对调度数据、操作控制数据和保护信号数据中的实时数据和历史数据进行优化，生成新的优化实时数据和新的优化历史数据。将这些优化数据再次输入设备状态实时预测模型，迭代调整模型参数，生成更新的状态变化预测信息。重复这一过程，不断调整和优化，直到状态变化预测信息和连接关系图均满足预设需求。Specifically, according to the adjustment of the connection relationship diagram, the parameters and processing flow of the real-time data processing framework and the historical data processing framework are re-evaluated and adjusted, and the adjusted two data processing frameworks are applied to optimize the real-time data and historical data in the dispatching data, operation control data and protection signal data to generate new optimized real-time data and new optimized historical data. These optimized data are input into the real-time prediction model of the equipment status again, and the model parameters are adjusted iteratively to generate updated state change prediction information. Repeat this process, continuously adjust and optimize, until the state change prediction information and the connection relationship diagram meet the preset requirements.
本实施例中，通过迭代调整连接关系图和数据处理框架，确保状态变化预测信息和连接关系图满足预设需求，该方法显著提升了电网系统的适应性和精准性。具体而言，当状态变化预测信息或连接关系图未能满足预设需求时，及时根据预测信息调整连接关系图，并据此优化实时和历史数据处理框架，使数据处理更加精确和高效。重复这一过程，直到预测信息和连接关系图均达到预期标准。此方法不仅提高了系统的动态调整能力和故障预测准确性，还优化了数据处理流程和模型参数，增强了电网系统的整体运行效率和安全性。In this embodiment, the method significantly improves the adaptability and accuracy of the power grid system by iteratively adjusting the connection relationship diagram and the data processing framework to ensure that the state change prediction information and the connection relationship diagram meet the preset requirements. Specifically, when the state change prediction information or the connection relationship diagram fails to meet the preset requirements, the connection relationship diagram is adjusted in time according to the prediction information, and the real-time and historical data processing framework is optimized accordingly to make data processing more accurate and efficient. Repeat this process until both the prediction information and the connection relationship diagram meet the expected standards. This method not only improves the system's dynamic adjustment capability and fault prediction accuracy, but also optimizes the data processing process and model parameters, and enhances the overall operation efficiency and safety of the power grid system.
在一个实施例中，如图6所示，将连接关系图以及状态变化预测信息输入至设备运行状态模型，得到初始操作信息校核信息，包括：In one embodiment, as shown in FIG. 6 , the connection relationship diagram and the state change prediction information are input into the equipment operation state model to obtain the initial operation information verification information, including:
步骤602，根据连接关系图以及状态变化预测信息，确定设备操作曲线。Step 602: Determine the device operation curve according to the connection relationship diagram and the state change prediction information.
其中，设备操作曲线可以是反映设备在不同操作条件下性能和行为的图形表示。它通常以曲线形式展示设备的运行参数（如压力、温度、功率等）随时间或操作变量（如负荷、速度等）的变化趋势。通过分析设备操作曲线，可以评估设备的性能、识别最佳操作条件、诊断潜在问题，并优化操作策略。Among them, the equipment operation curve can be a graphical representation of the performance and behavior of the equipment under different operating conditions. It usually shows the change trend of the equipment's operating parameters (such as pressure, temperature, power, etc.) over time or operating variables (such as load, speed, etc.) in the form of a curve. By analyzing the equipment operation curve, the performance of the equipment can be evaluated, the optimal operating conditions can be identified, potential problems can be diagnosed, and the operating strategy can be optimized.
具体地，将连接关系图与状态变化预测信息进行综合分析，识别设备之间的相互依赖关系和状态变化趋势。接着，在相互依赖关系和状态变化趋势的基础上提取关键设备的运行参数和状态数据，利用时间序列分析和回归分析方法，绘制各设备在不同运行条件下的状态变化曲线。通过数据拟合和模型优化，生成反映设备操作规律和性能特征的操作曲线作为设备操作曲线。Specifically, the connection relationship diagram and the state change prediction information are comprehensively analyzed to identify the interdependence and state change trends between devices. Then, the operating parameters and state data of key devices are extracted based on the interdependence and state change trends, and the state change curves of each device under different operating conditions are drawn using time series analysis and regression analysis methods. Through data fitting and model optimization, an operation curve that reflects the operation rules and performance characteristics of the equipment is generated as the equipment operation curve.
步骤604，根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，确定理论操作曲线。Step 604, determining a theoretical operation curve according to real-time data and historical data in the dispatching data, operation control data and protection signal data.
其中，理论操作曲线可以是根据设备的设计参数和理论计算得到的理想运行曲线，用于表示设备在不同操作条件下应达到的性能和行为。它展示了设备在最佳工作状态下各运行参数（如压力、温度、功率等）的变化趋势。理论操作曲线用于对比实际操作曲线，以评估设备的运行效率、诊断偏差和优化操作。Among them, the theoretical operating curve can be an ideal operating curve obtained based on the design parameters and theoretical calculations of the equipment, which is used to represent the performance and behavior that the equipment should achieve under different operating conditions. It shows the changing trend of various operating parameters (such as pressure, temperature, power, etc.) of the equipment under the best working condition. The theoretical operating curve is used to compare the actual operating curve to evaluate the operating efficiency of the equipment, diagnose deviations and optimize operations.
具体地，将调度数据、操作控制数据和保护信号数据中提取实时数据和历史数据进行数据分析和建模技术，确定各设备在不同工况下的初始的理论操作曲线。使用时间序列分析、回归分析和机器学习算法，分析设备的历史运行数据，提取关键参数和特征对初始的理论操作曲线进行修正，生成反映设备理想运行状态的理论操作曲线。Specifically, real-time data and historical data are extracted from dispatch data, operation control data and protection signal data for data analysis and modeling technology to determine the initial theoretical operating curve of each device under different working conditions. Time series analysis, regression analysis and machine learning algorithms are used to analyze the historical operation data of the equipment, extract key parameters and features to correct the initial theoretical operating curve, and generate a theoretical operating curve that reflects the ideal operating state of the equipment.
步骤606，将设备操作曲线与理论操作曲线进行比对，得到初始操作信息校核信息。Step 606, comparing the equipment operation curve with the theoretical operation curve to obtain initial operation information verification information.
具体地，将设备操作曲线与理论操作曲线进行数据对齐和标准化处理，以确保两者在相同的时间和参数维度上具有可比性。接着，使用误差分析和偏差检测方法，对两条曲线进行比对，识别出实际操作与理论操作之间的差异。通过计算偏差值、误差范围和趋势分析，评估设备操作的准确性和一致性。最终，生成初始操作信息校核信息。Specifically, the equipment operation curve is aligned and standardized with the theoretical operation curve to ensure that the two are comparable in the same time and parameter dimensions. Then, the two curves are compared using error analysis and deviation detection methods to identify the differences between actual operation and theoretical operation. The accuracy and consistency of equipment operation are evaluated by calculating deviation values, error ranges, and trend analysis. Finally, initial operation information verification information is generated.
本实施例中，通过根据连接关系图和状态变化预测信息确定设备操作曲线，并将其与根据调度数据、操作控制数据和保护信号数据中的实时数据及历史数据确定的理论操作曲线进行比对生成初始操作信息校核信息，该方法显著提升了电网系统的操作精度和可靠性。具体来说，设备操作曲线反映了实际运行情况，而理论操作曲线则代表了理想运行状态，通过两者的比对，能够精准识别操作偏差和潜在问题。生成的初始操作信息校核信息为调整和优化操作策略提供了科学依据，减少了故障发生率，提升了系统的稳定性和安全性。In this embodiment, by determining the equipment operation curve according to the connection relationship diagram and the state change prediction information, and comparing it with the theoretical operation curve determined according to the real-time data and historical data in the dispatching data, operation control data and protection signal data to generate initial operation information verification information, this method significantly improves the operation accuracy and reliability of the power grid system. Specifically, the equipment operation curve reflects the actual operation situation, while the theoretical operation curve represents the ideal operation state. By comparing the two, operation deviations and potential problems can be accurately identified. The generated initial operation information verification information provides a scientific basis for adjusting and optimizing the operation strategy, reduces the occurrence of failures, and improves the stability and safety of the system.
在一个实施例中，如图7所示，方法还包括：In one embodiment, as shown in FIG7 , the method further includes:
步骤702，获取电网系统中各设备对应的综合拓扑结构、设备状态数据和环境数据。Step 702: Obtain the comprehensive topological structure, device status data and environmental data corresponding to each device in the power grid system.
其中，综合拓扑结构可以是在系统或网络中，通过综合考虑各个节点和连接关系形成的整体布局和配置图。它描绘了系统中各组件、设备或节点之间的相互连接和关系，包括物理和逻辑层面的架构。The comprehensive topology can be the overall layout and configuration diagram formed by comprehensively considering the various nodes and connection relationships in a system or network. It depicts the interconnections and relationships between the components, devices or nodes in the system, including the architecture at the physical and logical levels.
其中，设备状态数据可以是反映设备当前运行状况的各类数据信息，包括但不限于温度、压力、电流、电压、转速、负载、振动等参数。这些数据通过传感器和监控系统实时采集，提供设备的运行性能、健康状况和操作状态等关键信息，用于监控、诊断、维护和优化设备的运行，确保其安全、可靠、高效地工作。Among them, equipment status data can be various data information reflecting the current operating status of the equipment, including but not limited to parameters such as temperature, pressure, current, voltage, speed, load, vibration, etc. These data are collected in real time through sensors and monitoring systems, providing key information such as equipment performance, health status and operating status, which are used to monitor, diagnose, maintain and optimize the operation of the equipment to ensure its safe, reliable and efficient operation.
其中，环境数据可以是描述和反映电网系统在特定环境条件和状态的各类数据信息，包括温度、湿度、气压、风速、降雨量、空气质量、噪音水平等。这些数据通过传感器和监测系统实时采集，提供对环境变化和条件的详细记录和分析。Environmental data can be various data information that describes and reflects the specific environmental conditions and status of the power grid system, including temperature, humidity, air pressure, wind speed, rainfall, air quality, noise level, etc. These data are collected in real time through sensors and monitoring systems, providing detailed records and analysis of environmental changes and conditions.
具体地，收集电网系统中各设备的综合拓扑结构信息，包括设备的物理位置、连接关系和网络配置。接着，利用传感器和监控系统获取设备状态数据，如运行参数、故障记录和性能指标。与此同时，从环境监测系统中提取相关环境数据，包括温度、湿度、气压和其他环境因素。通过数据采集终端和网络传输，将这些数据整合到数据中心，进行统一存储和处理。最终形成一个包含设备拓扑结构、状态数据和环境数据的综合数据库。Specifically, the comprehensive topological information of each device in the power grid system is collected, including the physical location, connection relationship and network configuration of the device. Then, the device status data, such as operating parameters, fault records and performance indicators, are obtained using sensors and monitoring systems. At the same time, relevant environmental data, including temperature, humidity, air pressure and other environmental factors, are extracted from the environmental monitoring system. Through data acquisition terminals and network transmission, these data are integrated into the data center for unified storage and processing. Finally, a comprehensive database containing device topology, status data and environmental data is formed.
步骤704，将综合拓扑结构、设备状态数据和环境数据输入至潜在风险预测模型，得到潜在风险预测数据。Step 704, inputting the comprehensive topology structure, equipment status data and environmental data into the potential risk prediction model to obtain potential risk prediction data.
其中，潜在风险预测数据可以是通过分析当前数据和历史趋势，预测电网系统可能出现的风险和问题的数据信息。包括对设备故障、自然灾害等潜在风险的预估数据。这些预测数据通过模型和算法生成，帮助决策者提前识别和应对潜在风险。Among them, potential risk prediction data can be data information that predicts the risks and problems that may occur in the power grid system by analyzing current data and historical trends. It includes estimated data on potential risks such as equipment failures and natural disasters. These prediction data are generated through models and algorithms to help decision makers identify and respond to potential risks in advance.
具体地，将综合拓扑结构、设备状态数据和环境数据输入至潜在风险预测模型，潜在风险预测模型利用机器学习和大数据分析技术，在综合拓扑结构的基础上对设备的运行状态和环境条件进行全面评估和分析，识别出可能导致设备故障或异常的关键因素和风险模式，生成潜在风险预测数据，其中，潜在风险预测数据包含设备的风险等级、故障概率和预警信息。Specifically, the comprehensive topology structure, equipment status data and environmental data are input into the potential risk prediction model. The potential risk prediction model uses machine learning and big data analysis technology to comprehensively evaluate and analyze the operating status and environmental conditions of the equipment based on the comprehensive topology structure, identify key factors and risk patterns that may cause equipment failure or abnormality, and generate potential risk prediction data, where the potential risk prediction data includes the equipment's risk level, failure probability and warning information.
步骤706，利用潜在风险预测数据对操作信息自动校核信息进行优化，得到优化操作信息自动校核信息。Step 706, optimizing the automatic verification information of the operation information by using the potential risk prediction data to obtain optimized automatic verification information of the operation information.
其中，优化操作信息自动校核信息可以是经过优化后的操作信息自动校核信息，具有更高的效率和准确率。The optimized operation information automatic verification information may be optimized operation information automatic verification information, which has higher efficiency and accuracy.
具体地，将潜在风险预测数据与初始操作信息校核信息进行对比分析，识别出潜在风险和操作偏差。基于潜在风险和操作偏差，根据潜在风险预测数据调整和优化校核算法，重点关注高风险设备和区域，增强对关键操作参数的校核力度。通过迭代优化重新校核操作信息，得到优化操作信息自动校核信息，其中优化操作信息自动校核信息包含详细的操作调整建议和风险预警。Specifically, the potential risk prediction data is compared and analyzed with the initial operation information verification information to identify potential risks and operation deviations. Based on the potential risks and operation deviations, the verification algorithm is adjusted and optimized according to the potential risk prediction data, focusing on high-risk equipment and areas, and strengthening the verification of key operation parameters. Through iterative optimization and re-verification of operation information, the automatic verification information of optimized operation information is obtained, where the automatic verification information of optimized operation information contains detailed operation adjustment suggestions and risk warnings.
本实施例中，通过获取电网系统中各设备的综合拓扑结构、设备状态数据和环境数据，并将其输入潜在风险预测模型以生成潜在风险预测数据，再利用这些预测数据对操作信息自动校核信息进行优化，得到优化操作信息自动校核信息，该方法显著提高了电网系统的预测和预防能力。具体而言，综合拓扑结构使得电网的整体布局和连接关系更加明确，设备状态数据和环境数据提供了实时的运行和环境信息。通过潜在风险预测模型，能够提前识别和评估风险，优化操作信息自动校核信息，确保校核结果更加准确和及时。这样不仅减少了故障发生的概率，还优化了操作策略，提高了电网系统的整体运营效率和可靠性，确保电力供应的稳定和持续。In this embodiment, by obtaining the comprehensive topological structure, equipment status data and environmental data of each device in the power grid system, and inputting them into the potential risk prediction model to generate potential risk prediction data, and then using these prediction data to optimize the automatic verification information of the operation information, the optimized automatic verification information of the operation information is obtained. This method significantly improves the prediction and prevention capabilities of the power grid system. Specifically, the comprehensive topological structure makes the overall layout and connection relationship of the power grid clearer, and the equipment status data and environmental data provide real-time operation and environmental information. Through the potential risk prediction model, risks can be identified and assessed in advance, and the automatic verification information of the operation information can be optimized to ensure that the verification results are more accurate and timely. This not only reduces the probability of failure, but also optimizes the operation strategy, improves the overall operational efficiency and reliability of the power grid system, and ensures the stability and continuity of power supply.
应该理解的是，虽然如上的各实施例所涉及的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，如上的各实施例所涉及的流程图中的至少一部分步骤可以包括多个步骤或者多个阶段，这些步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤中的步骤或者阶段的至少一部分轮流或者交替地执行。It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.
基于同样的发明构思，本申请实施例还提供了一种用于实现上述所涉及的设备启动的操作信息自动校核方法的一种设备启动的操作信息自动校核装置。该装置所提供的解决问题的实现方案与上述方法中所记载的实现方案相似，故下面所提供的一个或多个设备启动的操作信息自动校核装置实施例中的具体限定可以参见上文中对于一种设备启动的操作信息自动校核方法的限定，在此不再赘述。Based on the same inventive concept, the embodiment of the present application also provides a device for automatically checking the operation information of a device startup for implementing the method for automatically checking the operation information of a device startup involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of the device for automatically checking the operation information of one or more devices startup provided below can refer to the limitations of the method for automatically checking the operation information of a device startup above, and will not be repeated here.
在一个实施例中，如图8所示，提供了一种设备启动的操作信息自动校核装置，包括：电网数据获取模块802、状态模型得到模块804、第一数据处理模块806、第二数据处理模块808、操作信息生成模块810和校核信息确定模块812，其中：In one embodiment, as shown in FIG8 , a device for automatically checking operation information started by a device is provided, comprising: a power grid data acquisition module 802, a state model acquisition module 804, a first data processing module 806, a second data processing module 808, an operation information generation module 810 and a check information determination module 812, wherein:
电网数据获取模块802，用于获取电网系统中各设备对应的调度数据、操作控制数据和保护信号数据；The power grid data acquisition module 802 is used to acquire the dispatching data, operation control data and protection signal data corresponding to each device in the power grid system;
状态模型得到模块804，用于融合调度数据、操作控制数据和保护信号数据中的异构数据，得到设备运行状态模型；The state model obtaining module 804 is used to integrate heterogeneous data in the scheduling data, operation control data and protection signal data to obtain a device operation state model;
第一数据处理模块806，用于根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，生成各设备对应的连接关系图以及状态变化预测信息；The first data processing module 806 is used to generate a connection relationship diagram corresponding to each device and state change prediction information according to the real-time data and historical data in the dispatching data, operation control data and protection signal data;
第二数据处理模块808，用于将连接关系图以及状态变化预测信息输入至设备运行状态模型，得到初始操作信息校核信息；The second data processing module 808 is used to input the connection relationship diagram and the state change prediction information into the equipment operation state model to obtain the initial operation information verification information;
操作信息生成模块810，用于根据操作控制数据和保护信号数据中的实时数据，生成调整设别操作信息；The operation information generating module 810 is used to generate the adjustment device operation information according to the real-time data in the operation control data and the protection signal data;
校核信息确定模块812，用于根据初始操作信息校核信息以及调整设别操作信息，确定电网系统的操作信息自动校核信息。The calibration information determination module 812 is used to determine the automatic calibration information of the operation information of the power grid system according to the calibration information of the initial operation information and the adjustment device operation information.
在一个实施例中，第一数据处理模块806，还用于根据调度数据中的实时数据以及历史数据，生成初始设备连接关系图；根据调度数据中的实时数据，对初始设备连接关系图的连接关系进行跟新，得到设备对应的连接关系图；将调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据输入至电网系统的设备状态实时预测模型，得到状态变化预测信息。In one embodiment, the first data processing module 806 is also used to generate an initial equipment connection relationship diagram based on the real-time data and historical data in the scheduling data; update the connection relationship of the initial equipment connection relationship diagram based on the real-time data in the scheduling data to obtain a connection relationship diagram corresponding to the equipment; input the real-time data and historical data in the scheduling data, operation control data and protection signal data into the real-time prediction model of the equipment status of the power grid system to obtain state change prediction information.
在一个实施例中，第一数据处理模块806，还用于根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，确定实时数据的实时数据处理框架以及历史数据的历史数据处理框架；根据实时数据处理框架，对调度数据、操作控制数据和保护信号数据中的实时数据进行优化，得到优化实时数据；根据历史数据处理框架，对调度数据、操作控制数据和保护信号数据中的历史数据进行优化，得到优化历史数据；根据优化实时数据以及优化历史数据，修改电网系统的设备状态实时预测模型的参数，使得设备状态实时预测模型输出状态变化预测信息。In one embodiment, the first data processing module 806 is also used to determine the real-time data processing framework of real-time data and the historical data processing framework of historical data based on the real-time data and historical data in the dispatching data, operation control data and protection signal data; optimize the real-time data in the dispatching data, operation control data and protection signal data according to the real-time data processing framework to obtain optimized real-time data; optimize the historical data in the dispatching data, operation control data and protection signal data according to the historical data processing framework to obtain optimized historical data; modify the parameters of the real-time prediction model of the equipment status of the power grid system based on the optimized real-time data and the optimized historical data, so that the real-time prediction model of the equipment status outputs state change prediction information.
在一个实施例中，第一数据处理模块806，还用于如果状态变化预测信息或/和连接关系图未能满足预设需求，则根据状态变化预测信息调整连接关系图，得到调整关系图；根据调整关系图，调整实时数据处理框架以及历史数据处理框架，返回执行根据实时数据处理框架，对调度数据、操作控制数据和保护信号数据中的实时数据进行优化，得到优化实时数据的步骤，直到状态变化预测信息和连接关系图均能满足预设需求。In one embodiment, the first data processing module 806 is also used to adjust the connection relationship diagram according to the state change prediction information to obtain an adjusted relationship diagram if the state change prediction information and/or the connection relationship diagram fail to meet the preset requirements; adjust the real-time data processing framework and the historical data processing framework according to the adjusted relationship diagram, and return to execute the step of optimizing the real-time data in the scheduling data, operation control data and protection signal data according to the real-time data processing framework to obtain optimized real-time data, until the state change prediction information and the connection relationship diagram can meet the preset requirements.
在一个实施例中，第二数据处理模块808，还用于根据连接关系图以及状态变化预测信息，确定设备操作曲线；根据调度数据、操作控制数据和保护信号数据中的实时数据以及历史数据，确定理论操作曲线；将设备操作曲线与理论操作曲线进行比对，得到初始操作信息校核信息。In one embodiment, the second data processing module 808 is also used to determine the equipment operation curve based on the connection relationship diagram and the state change prediction information; determine the theoretical operation curve based on the real-time data and historical data in the scheduling data, operation control data and protection signal data; compare the equipment operation curve with the theoretical operation curve to obtain initial operation information verification information.
在一个实施例中，校核信息确定模块812，还用于获取电网系统中各设备对应的综合拓扑结构、设备状态数据和环境数据；将综合拓扑结构、设备状态数据和环境数据输入至潜在风险预测模型，得到潜在风险预测数据；利用潜在风险预测数据对操作信息自动校核信息进行优化，得到优化操作信息自动校核信息。In one embodiment, the verification information determination module 812 is also used to obtain the comprehensive topology structure, device status data and environmental data corresponding to each device in the power grid system; input the comprehensive topology structure, device status data and environmental data into the potential risk prediction model to obtain potential risk prediction data; use the potential risk prediction data to optimize the automatic verification information of the operation information to obtain the optimized automatic verification information of the operation information.
上述一种设备启动的操作信息自动校核装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。Each module in the automatic verification device for operation information started by the above-mentioned device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.
在一个实施例中，提供了一种计算机设备，该计算机设备可以是服务器，其内部结构图可以如图9所示。该计算机设备包括通过系统总线连接的处理器、存储器和网络接口。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括非易失性存储介质和内存储器。该非易失性存储介质存储有操作系统、计算机程序和数据库。该内存储器为非易失性存储介质中的操作系统和计算机程序的运行提供环境。该计算机设备的数据库用于存储服务器数据。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机程序被处理器执行时以实现一种设备启动的操作信息自动校核方法。In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG9 . The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store server data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for automatically checking the operation information of a device startup is implemented.
本领域技术人员可以理解，图9中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。Those skilled in the art will understand that the structure shown in FIG. 9 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.
在一个实施例中，还提供了一种计算机设备，包括存储器和处理器，存储器中存储有计算机程序，该处理器执行计算机程序时实现上述各方法实施例中的步骤。In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.
在一个实施例中，提供了一种计算机可读存储介质，存储有计算机程序，该计算机程序被处理器执行时实现上述各方法实施例中的步骤。In one embodiment, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.
在一个实施例中，提供了一种计算机程序产品或计算机程序，该计算机程序产品或计算机程序包括计算机指令，该计算机指令存储在计算机可读存储介质中。计算机设备的处理器从计算机可读存储介质读取该计算机指令，处理器执行该计算机指令，使得该计算机设备执行上述各方法实施例中的步骤。In one embodiment, a computer program product or computer program is provided, the computer program product or computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps in the above-mentioned method embodiments.
需要说明的是，本申请所涉及的用户信息（包括但不限于用户设备信息、用户个人信息等）和数据（包括但不限于用于分析的数据、存储的数据、展示的数据等），均为经用户授权或者经过各方充分授权的信息和数据。It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、数据库或其它介质的任何引用，均可包括非易失性和易失性存储器中的至少一种。非易失性存储器可包括只读存储器（Read-OnlyMemory，ROM）、磁带、软盘、闪存、光存储器、高密度嵌入式非易失性存储器、阻变存储器（ReRAM）、磁变存储器（Magnetoresistive Random Access Memory，MRAM）、铁电存储器（Ferroelectric Random Access Memory，FRAM）、相变存储器（Phase Change Memory，PCM）、石墨烯存储器等。易失性存储器可包括随机存取存储器（Random Access Memory，RAM）或外部高速缓冲存储器等。作为说明而非局限，RAM可以是多种形式，比如静态随机存取存储器（Static Random Access Memory，SRAM）或动态随机存取存储器（Dynamic RandomAccess Memory，DRAM）等。本申请所提供的各实施例中所涉及的数据库可包括关系型数据库和非关系型数据库中至少一种。非关系型数据库可包括基于区块链的分布式数据库等，不限于此。本申请所提供的各实施例中所涉及的处理器可为通用处理器、中央处理器、图形处理器、数字信号处理器、可编程逻辑器、基于量子计算的数据处理逻辑器等，不限于此。Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对本申请专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请的保护范围应以所附权利要求为准。The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.
| Application Number | Priority Date | Filing Date | Title |
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| CN202410818243.XACN118572890B (en) | 2024-06-24 | 2024-06-24 | Method, device and computer equipment for automatically checking operation information of equipment startup |
| Application Number | Priority Date | Filing Date | Title |
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| CN202410818243.XACN118572890B (en) | 2024-06-24 | 2024-06-24 | Method, device and computer equipment for automatically checking operation information of equipment startup |
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| CN118572890Atrue CN118572890A (en) | 2024-08-30 |
| CN118572890B CN118572890B (en) | 2025-09-23 |
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| CN202410818243.XAActiveCN118572890B (en) | 2024-06-24 | 2024-06-24 | Method, device and computer equipment for automatically checking operation information of equipment startup |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116702481A (en)* | 2023-06-12 | 2023-09-05 | 中国南方电网有限责任公司 | Verification system for distributed energy model |
| CN117713091A (en)* | 2023-10-27 | 2024-03-15 | 国家电网有限公司华东分部 | D+1 day graphical verification method, device and equipment based on future ultra-short-term data |
| CN118157084A (en)* | 2024-03-13 | 2024-06-07 | 云南电网有限责任公司 | Automatic checking method and system for main transformer protection fixed value safety boundary |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116702481A (en)* | 2023-06-12 | 2023-09-05 | 中国南方电网有限责任公司 | Verification system for distributed energy model |
| CN117713091A (en)* | 2023-10-27 | 2024-03-15 | 国家电网有限公司华东分部 | D+1 day graphical verification method, device and equipment based on future ultra-short-term data |
| CN118157084A (en)* | 2024-03-13 | 2024-06-07 | 云南电网有限责任公司 | Automatic checking method and system for main transformer protection fixed value safety boundary |
| Publication number | Publication date |
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| CN118572890B (en) | 2025-09-23 |
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