Disclosure of Invention
The invention aims to at least solve the technical problems that the rush repair period is too long and the rush repair process is repeated when the low-voltage distribution line of the distribution transformer area is in a manually managed lagging state in the prior art.
To this end, an object of the present invention is to propose a fault state machine modeling method based on a regularization method, comprising:
Defining various fault states possibly existing in the power system, and associating a self-healing strategy corresponding to each fault state;
determining events that may trigger transitions between the fault states;
Defining transition conditions between said fault states;
designing corresponding regular expressions for the fault state, the event and the transfer condition respectively;
The regular expression of the fault state, the regular expression of the event and the regular expression of the transfer condition are expressed in a graph form, and a self-healing fault machine state model is built;
And performing accuracy verification on the fault machine state model to obtain a final self-healing fault machine state model.
Further, the regular expression of the fault state, the regular expression of the event and the regular expression of the transfer condition are expressed in a graph form, and a self-healing fault machine state model is constructed, which comprises the following steps:
And constructing a self-healing fault state machine model of a directed graph by using the regular expression of the fault state, the regular expression of the event and the regular expression of the transfer condition, wherein each node in the directed graph represents one fault state, and the edges in the directed graph represent the event and the transfer condition.
Further, a transition condition between the fault states is defined, the transition condition comprising:
The transition between the fault states is performed under the conditions of a specific fault state and a specific event.
Further, defining various fault states possibly existing in the power system, and associating a self-healing strategy corresponding to each fault state with each fault state, wherein the self-healing strategy comprises the following steps:
and (3) deeply analyzing the behavior characteristics of the power system, and defining various possible fault states of the power system according to analysis results.
Further, the behavior characteristics of the power system are deeply analyzed, and various possible fault states of the power system are defined according to analysis results, including:
Voltage fluctuations, current imbalance, and device operating state changes.
Further, the behavior characteristics of the power system are deeply analyzed, various fault states possibly existing in the power system are defined, each fault state is associated with a corresponding self-healing strategy, and the behavior characteristics comprise:
Voltage fluctuations, current imbalance, and device operating state changes.
Further, the behavior characteristics of the power system are deeply analyzed, various fault states possibly existing in the power system are defined, each fault state is associated with a corresponding self-healing strategy, and the fault states comprise:
Normal operation, warning, light failure, severe failure, and system recovery.
Further, the behavior characteristics of the power system are deeply analyzed, various fault states possibly existing in the power system are defined, and each fault state is associated with a corresponding self-healing strategy, and the self-healing strategy comprises:
Adjust power distribution, isolate faulty lines, or start up backup power.
Further, performing accuracy verification on the fault machine state model to obtain a final self-healing fault machine state model, including:
And verifying the accuracy of the fault state machine model through actual operation or simulation test, and obtaining a final fault state machine model if a verification result meets the requirements.
The invention provides a fault state machine fault processing method based on a regularization method, which realizes the construction of a fault state machine by using the fault state machine modeling method based on the regularization method, and comprises the following steps:
The power system receives an event, and a fault state machine obtains a transfer condition according to the event and a fault state of the power system;
The fault state machine judges the fault state to which the power system needs to be transferred according to the transfer condition;
And the fault state machine distributes a self-healing strategy corresponding to the power system according to the fault state to which the power system needs to be transferred, so as to realize automatic identification and maintenance of the power system fault.
The invention discloses a fault state machine modeling method and a fault processing method based on a regularization method, which have the following beneficial effects:
In self-healing fault state machine modeling, the advantage of the regularization method is mainly expressed in two aspects, namely, firstly, the behavior mode of the system can be briefly described, the workload of manual coding is reduced, and the efficiency of model construction is improved. Second, the legibility and maintainability of regular expressions makes understanding and modifying state machine models more intuitive. In addition, regular expressions provide rich matching rules and logic operations, and can handle complex patterns, so that behavior changes of the system under different fault conditions can be accurately captured.
The invention combines the conciseness of the regular expression and the intuitiveness of the state machine, can effectively establish and simplify the self-healing fault model, can effectively describe the behavior mode of the self-healing of the low-voltage system fault, and provides a brief and efficient modeling method for the research of the system fault diagnosis and the fault self-healing strategy.
The invention utilizes a regular method to describe the behavior mode of the system, and further designs a fault state machine meeting the low-voltage self-healing control requirement. The invention has the advantages of simplifying the modeling process of the fault state machine and improving the accuracy of the model, and provides a new modeling tool for fault diagnosis and recovery of a complex system. The self-healing fault state machine constructed by the regular method can accurately identify the fault state, guide the self-healing process of the system, improve the stability and reliability of the system, improve the rush repair speed when the low-voltage fault of the transformer area occurs, and save the manpower.
Detailed Description
Various aspects and features of the present invention are described herein with reference to the accompanying drawings.
It should be understood that various modifications may be made to the embodiments of the application herein. Therefore, the above description should not be taken as limiting, but merely as exemplification of the embodiments. Other modifications within the scope and spirit of the invention will occur to persons of ordinary skill in the art.
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with a general description of the invention given above, and the detailed description of the embodiments given below, serve to explain the principles of the invention.
These and other characteristics of the invention will become apparent from the following description of a preferred form of embodiment, given as a non-limiting example, with reference to the accompanying drawings.
It is also to be understood that, although the invention has been described with reference to some specific examples, a person skilled in the art will certainly be able to achieve many other equivalent forms of the invention, having the characteristics as set forth in the claims and hence all coming within the field of protection defined thereby.
The above and other aspects, features and advantages of the present invention will become more apparent in light of the following detailed description when taken in conjunction with the accompanying drawings.
Specific embodiments of the invention will be described hereinafter with reference to the accompanying drawings, in which, however, it is to be understood that the embodiments so applied are merely examples of the invention, which may be practiced in various ways. Well-known and/or repeated functions and constructions are not described in detail to avoid obscuring the invention in unnecessary or unnecessary detail. Therefore, specific structural and functional details disclosed herein are not intended to be limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present invention in virtually any appropriately detailed structure.
Examples
As shown in fig. 1, the present embodiment provides a fault state machine modeling method based on a regularization method, including:
Step S1, deeply analyzing the behavior characteristics of a power system, defining various fault states possibly existing in the power system, and associating a self-healing strategy corresponding to each fault state;
Step S2, determining an event which possibly triggers transition between the fault states;
step S3, defining transition conditions between the fault states;
S4, designing corresponding regular expressions for the fault state, the event and the transfer condition respectively;
s5, representing the regular expression of the fault state, the regular expression of the event and the regular expression of the transfer condition in a graph form, and constructing a self-healing fault machine state model;
and S6, performing accuracy verification on the state model of the fault machine to obtain a final self-healing state model of the fault machine.
With respect to the step S1, the behavior characteristics of the power system are deeply analyzed, various fault states possibly existing in the power system are defined, and each fault state is associated with a self-healing strategy corresponding to the fault state:
The behavioral characteristics include:
voltage fluctuation, current imbalance, equipment operation state change and the like;
defining the various fault conditions that may exist for the power system is identifying the various fault conditions that may exist for the power system, which generally involves a thorough understanding of the power system functions and components, which may be explicit, i.e., obvious fault conditions, or implicit, i.e., potential problems or impending faults.
Based on the analysis of the behavioral characteristics, possible fault states of the system are defined, such as "normal operation", "warning", "light fault", "serious fault", and "system recovery", etc.
A State of failure (State) is a description of the power system at a particular moment in time, representing a particular function or State of the system. In a fault state machine, these states may be different conditions such as normal system operation, partial faults, critical faults, or complete shutdown. Events (events) are triggers that trigger state transitions, which may be external inputs, changes in internal conditions, or the occurrence of a failure of the system itself. The transition condition (Transition Condition) defines under what circumstances the system transitions from one state to another, which is typically related to the triggering of an event and the current state of the system.
According to another embodiment of the present invention, on the basis of the step S1, the behavior characteristics of the power system are further analyzed, various fault states that may exist in the power system are defined, and for each fault state, a self-healing policy corresponding to the fault state is associated, where the self-healing policy includes:
Adjust power distribution, isolate faulty lines, or start up backup power.
In the fault state machine, each fault state is associated with a set of predefined self-healing policies. When the system is in a certain fault state, corresponding self-healing strategies, such as adjusting power distribution, isolating a fault line or starting a standby power supply, are automatically executed. These strategies are designed based on the physical principles of operation of the power system and the understanding of failure modes by the skilled artisan, with the aim of minimizing the impact of the failure and restoring normal operation of the system. As shown in table 1 below:
TABLE 1 self-healing policy description
According to another embodiment of the present invention, on the basis of said step S2, events that may trigger a transition between said fault states are determined, including external events (e.g. user operations, environmental changes) and internal events (e.g. hardware faults, software errors).
According to another specific embodiment of the present invention, on the basis of the step S3, a transition condition between the fault states is defined, the transition condition including:
The transition between the fault states is performed under the conditions of a specific fault state and a specific event. This may involve complex logic decisions such as severity of the failure, availability of system resources, etc.
According to another embodiment of the present invention, on the basis of the step S4, a corresponding regular expression is designed for the fault state, the event and the transition condition, respectively:
and designing a corresponding regular expression for the fault state, wherein the regular expression describes the characteristic of entering the state by the system in a concise form. For example, a regular expression might describe that when the voltage fluctuation amplitude exceeds a certain threshold, the system will go from a "normal running" state to a "warning" state, as shown in Table 2 below:
table 2 fault state regularization
A corresponding regular expression is designed for the event, e.g., a regular expression of an event describes when a current fluctuation of a particular frequency is detected.
A corresponding regular expression is designed for the transition condition that describes that under certain conditions, depending on the particular event and the fault state in which the power system is currently located, the power system will experience a transition from a fault state, e.g. when a current fluctuation of a certain frequency is detected, the power system will transition from a "warning" fault state to a "light fault".
According to another specific embodiment of the present invention, on the basis of the step S5, the regular expression of the fault state, the regular expression of the event, and the regular expression of the transition condition are represented in a graph form, and the method includes:
Constructing a self-healing fault state machine model of a directed graph by using the regular expression of the fault state, the regular expression of the event and the regular expression of the transfer condition, wherein each node in the directed graph represents one fault state, and the edges in the directed graph represent the event and the transfer condition;
After the power system receives the triggering of the specific event, the state transition is automatically carried out according to the matching result of the regular expression, so that the transition and the rapid identification of the fault state are realized.
The traditional self-healing model is usually based on the theories of Petri network, finite state automaton and the like, but the construction and maintenance workload of the models is large, a large amount of manual coding is often needed when describing the state transition relation of a complex system, and the readability and maintainability of the models are poor. To solve these problems, the present study proposes a self-healing fault state machine modeling framework based on a canonical approach. The regular expression, which is a compact and powerful language, can effectively describe the behavior pattern of the system, and provides a new way for constructing a self-healing fault state machine.
According to another embodiment of the present invention, on the basis of the step S6, the accuracy verification is performed on the state model of the fault machine, to obtain a final self-healing state model of the fault machine, including:
And verifying the accuracy of the fault state machine model through actual operation or simulation test, and obtaining a final fault state machine model if a verification result meets the requirements.
According to another embodiment of the present invention, the present invention provides a method for processing a fault of a fault state machine based on a regularization method, where the constructing of the fault state machine is implemented by using the method for modeling a fault state machine based on the regularization method described in any one of the above, including:
The power system receives an event, and a fault state machine obtains a transfer condition according to the event and a fault state of the power system;
The fault state machine judges the fault state to which the power system needs to be transferred according to the transfer condition;
And the fault state machine distributes a self-healing strategy corresponding to the power system according to the fault state to which the power system needs to be transferred, so as to realize automatic identification and maintenance of the power system fault.
In self-healing fault state machine modeling, the advantage of the regularization method is mainly expressed in two aspects, namely, firstly, the behavior mode of the system can be briefly described, the workload of manual coding is reduced, and the efficiency of model construction is improved. Second, the legibility and maintainability of regular expressions makes understanding and modifying state machine models more intuitive. In addition, regular expressions provide rich matching rules and logic operations, and can handle complex patterns, so that behavior changes of the system under different fault conditions can be accurately captured.
The invention combines the conciseness of the regular expression and the intuitiveness of the state machine, can effectively establish and simplify the self-healing fault model, can effectively describe the behavior mode of the self-healing of the low-voltage system fault, and provides a brief and efficient modeling method for the research of the system fault diagnosis and the fault self-healing strategy.
The invention utilizes a regular method to describe the behavior mode of the system, and further designs a fault state machine meeting the low-voltage self-healing control requirement. The invention has the advantages of simplifying the modeling process of the fault state machine and improving the accuracy of the model, and provides a new modeling tool for fault diagnosis and recovery of a complex system. The self-healing fault state machine constructed by the regular method can accurately identify the fault state, guide the self-healing process of the system, improve the stability and reliability of the system, improve the rush repair speed when the low-voltage fault of the transformer area occurs, and save the manpower.
The embodiment of the disclosure further provides an electronic device, at least including a memory and a processor, where the memory stores a computer program, and the processor implements the foregoing fault state machine modeling method based on the regularization method when executing the computer program on the memory, and the method includes:
Step S1, deeply analyzing the behavior characteristics of a power system, defining various fault states possibly existing in the power system, and associating a self-healing strategy corresponding to each fault state;
Step S2, determining an event which possibly triggers transition between the fault states;
step S3, defining transition conditions between the fault states;
S4, designing corresponding regular expressions for the fault state, the event and the transfer condition respectively;
s5, representing the regular expression of the fault state, the regular expression of the event and the regular expression of the transfer condition in a graph form, and constructing a self-healing fault machine state model;
and S6, performing accuracy verification on the state model of the fault machine to obtain a final self-healing state model of the fault machine.
In some embodiments, a processor executing a computer program may be a processing device including more than one general purpose processing device, such as a microprocessor, central Processing Unit (CPU), graphics Processing Unit (GPU), or the like. More specifically, the processor may be a Complex Instruction Set Computing (CISC) microprocessor, a Reduced Instruction Set Computing (RISC) microprocessor, a Very Long Instruction Word (VLIW) microprocessor, a processor running other instruction sets, or a processor running a combination of instruction sets. The processor may also be one or more special purpose processing devices such as an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), a system on a chip (SoC), or the like.
The memory may be read-only memory (ROM), random-access memory (RAM), phase-change random-access memory (PRAM), static random-access memory (SRAM), dynamic random-access memory (DRAM), electrically erasable programmable read-only memory (EEPROM), other types of random-access memory (RAM), flash memory disk or other forms of flash memory, cache, registers, static memory, compact disc read-only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, or other magnetic storage devices, or any other possible non-transitory medium which can be used to store information or instructions that can be accessed by a computer device, and the like.
The electronic devices of the disclosed embodiments may include, but are not limited to, fixed terminal devices such as MCU controllers, servers, desktop computers, digital TVs, and the like, as well as mobile terminal devices such as in-vehicle devices (e.g., heads-up display devices), handheld devices (e.g., cell phones, tablet computers, and the like), wearable devices (e.g., smart watches, smart bracelets, and the like).
The disclosed embodiments also provide a computer readable storage medium storing a computer program which, when executed by a processor, implements a fault state machine modeling method based on a regularization method described above, including:
Step S1, deeply analyzing the behavior characteristics of a power system, defining various fault states possibly existing in the power system, and associating a self-healing strategy corresponding to each fault state;
Step S2, determining an event which possibly triggers transition between the fault states;
step S3, defining transition conditions between the fault states;
S4, designing corresponding regular expressions for the fault state, the event and the transfer condition respectively;
s5, representing the regular expression of the fault state, the regular expression of the event and the regular expression of the transfer condition in a graph form, and constructing a self-healing fault machine state model;
and S6, performing accuracy verification on the state model of the fault machine to obtain a final self-healing state model of the fault machine.
The computer-readable storage media of the embodiments of the present disclosure may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. In the disclosed embodiments, the computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device, such as the memory described above.
The computer programs of embodiments of the present disclosure may be organized into one or more computer-executable components or modules. Aspects of the disclosure may be implemented with any number and combination of such components or modules. For example, aspects of the present disclosure are not limited to the specific computer-executable instructions or the specific components or modules illustrated in the figures and described herein. Other embodiments may include different computer-executable instructions or components having more or less functionality than illustrated and described herein.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by persons skilled in the art that the scope of the disclosure referred to in this disclosure is not limited to the specific combinations of features described above, but also covers other embodiments which may be formed by any combination of features described above or equivalents thereof without departing from the spirit of the disclosure. Such as those described above, are mutually substituted with the technical features having similar functions disclosed in the present disclosure (but not limited thereto).