CN114661787A - Itemset mining method and device - Google Patents
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Abstract
Description
Translated fromChinese技术领域technical field
本发明涉及数据挖掘技术领域，尤其涉及一种项集挖掘方法及装置。The present invention relates to the technical field of data mining, in particular to an itemset mining method and device.
背景技术Background technique
为了发现不同数据项之间的关联规则，需要进行目标数据项集的挖掘。项集(英文：Itemsets)是由至少一个数据项构成的集合，用于表征数据库中内在的一种关联规则。HUIM(High-Utility Itemsets Mining，高效用项集挖掘)作为一种常见的数据挖掘方式，用于从数据库中挖掘出由不同数据项组成的效用值较高的项集。在现有的基于HUIM的算法中，根据不同数据项各自对应的效用值，计算数据库中各个项集对应的效用值，当该项集对应的效用值大于或等于预设效用值时，确定该项集为高效用项集并进行挖掘，从而实现从数据库中挖掘出高效用的项集。In order to discover the association rules between different data items, it is necessary to mine the target data item set. An item set (English: Itemsets) is a collection composed of at least one data item, which is used to represent an inherent association rule in the database. HUIM (High-Utility Itemsets Mining), as a common data mining method, is used to mine itemsets with high utility value composed of different data items from the database. In the existing HUIM-based algorithm, the utility value corresponding to each item set in the database is calculated according to the corresponding utility value of different data items. When the utility value corresponding to the item set is greater than or equal to the preset utility value, the The itemsets are high-utility itemsets and are mined, so as to mine high-utility itemsets from the database.
随着现代网络技术的发展，数据成指数增长，对海量数据进行必要的挖掘和处理，为用户提供有价值的信息，以此指导用户做出相应的技术决策和经营管理显得尤为重要。关联分析通常用来描述数据中强关联特征的模式，即发现隐藏在大型数据集中的因果联系，其应用包括在生物医学领域找出具有相关功能的基因组、在网页挖掘中识别用户一起访问的网页、在地球科学中理解地球气候系统不同元素之间的因果联系、在购物数据中挖掘用户的购物习惯等With the development of modern network technology, data grows exponentially, it is particularly important to mine and process massive data to provide users with valuable information, so as to guide users to make corresponding technical decisions and business management. Association analysis is often used to describe patterns of strongly correlated features in data, that is, to discover causal links hidden in large data sets. Its applications include finding genomes with related functions in the biomedical field, and identifying web pages that users visit together in web mining. , Understand the causal connection between different elements of the Earth's climate system in geoscience, mine users' shopping habits in shopping data, etc.
但现有技术中，不能及时挖掘出大货车行驶过程中的故障规律，使得大货车在复杂和环境多变情况下行驶时，可能产生导致大货车故障预警不及时、不准确的问题。However, in the prior art, the failure rule during the driving process of the large truck cannot be dug out in time, so that when the large truck is driving in complex and changing environment, the problem of untimely and inaccurate fault warning of the large truck may occur.
发明内容SUMMARY OF THE INVENTION
本发明提供了一种项集挖掘方法及装置，以解决上述背景技术中提出的问题。The present invention provides an itemset mining method and device to solve the above-mentioned problems in the background art.
为了实现上述目的，本发明采用了如下技术方案：In order to achieve the above object, the present invention adopts the following technical solutions:
一种项集挖掘方法，包括以下步骤：An itemset mining method, comprising the following steps:
第一步，首先采集大货车的车辆行驶数据和故障类型，得到具有故障类标记的大货车故障类型数据集；The first step is to first collect the vehicle driving data and fault types of the large truck, and obtain a large truck fault type data set with fault class labels;
第二步，根据大货车每次相同类型故障发生时的行驶数据，得到具有故障类标记的行驶数据集；In the second step, according to the driving data of the large truck every time the same type of fault occurs, a driving data set with fault class labels is obtained;
第三步，确定行驶数据集集合中每个类型参数数据的频繁概率，并按照频繁概率将大货车行驶数据集集集合中的类型参数数据进行排序；The third step is to determine the frequent probability of each type of parameter data in the driving data set, and sort the type parameter data in the large truck driving data set according to the frequent probability;
第四步，根据大货车行驶数据集所包括高频繁概率的类型参数数据，确定大货车行驶故障规律。The fourth step is to determine the driving failure rule of the large truck according to the type parameter data with high frequent probability included in the large truck driving data set.
作为本技术方案的进一步改进方案：通过设置在大货车上的多个传感器，获取设定区域、设定时间段内大货车的行驶数据。As a further improvement of the technical solution, the driving data of the large truck in a set area and a set time period are acquired through a plurality of sensors arranged on the large truck.
作为本技术方案的进一步改进方案：行驶数据包括车辆发生故障时各零部件的相关参数数据和车辆环境数据。As a further improvement of the technical solution: the driving data includes relevant parameter data of each component and vehicle environment data when the vehicle fails.
作为本技术方案的进一步改进方案：车辆环境数据包括车辆的振动幅度与频率，车辆周围空气的温度与湿度，车辆位置处的海拔高度。As a further improvement of the technical solution: the vehicle environment data includes the vibration amplitude and frequency of the vehicle, the temperature and humidity of the air surrounding the vehicle, and the altitude at the location of the vehicle.
作为本技术方案的进一步改进方案：各零部件的相关参数数据包括发动机油量、发动机冷却液液面高度、制动液液面高度、离合器总泵液面高度、皮带振动幅度、轮胎气压、蓄电池电池状态等。As a further improvement plan of this technical solution: the relevant parameter data of each component include engine oil volume, engine coolant level, brake fluid level, clutch master cylinder level, belt vibration amplitude, tire pressure, battery battery status, etc.
作为本技术方案的进一步改进方案：行驶数据为故障发生时前三个小时内的行驶数据。As a further improvement of the technical solution: the driving data is the driving data within the first three hours when the fault occurs.
本发明实施例还提供了一种项集挖掘装置，包括：The embodiment of the present invention also provides an itemset mining device, including:
第一数据处理模块，用于采集大货车的车辆行驶数据和故障类型，得到具有故障类标记的大货车故障类型数据集；a first data processing module, used for collecting vehicle driving data and fault types of the large truck, and obtaining a large truck fault type data set with fault type marks;
第二数据处理模块，用于根据大货车每次相同类型故障发生时的行驶数据，得到具有故障类标记的行驶数据集；The second data processing module is configured to obtain a driving data set with fault class labels according to the driving data of the large truck every time the same type of fault occurs;
第三数据处理模块，用于确定行驶数据集集合中每个类型参数数据的频繁概率，并按照频繁概率将大货车行驶数据集集集合中的类型参数数据进行排序；The third data processing module is used to determine the frequent probability of each type of parameter data in the driving data set, and sort the type parameter data in the large truck driving data set according to the frequent probability;
第四评估预测模块，用于根据大货车行驶数据集所包括高频繁概率的类型参数数据，确定大货车行驶故障规律。The fourth evaluation and prediction module is used for determining the driving failure rule of the large truck according to the type parameter data with high frequent probability included in the driving data set of the large truck.
本发明实施例还提供了一种终端设备，包括处理器、存储器以及存储在所述存储器中且被配置为由所述处理器执行的计算机程序，所述处理器执行所述计算机程序时实现上述任一项所述的项集挖掘方法。An embodiment of the present invention further provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the above when executing the computer program The itemset mining method of any one.
本发明实施例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包括存储的计算机程序，其中，在所述计算机程序运行时控制所述计算机可读存储介质所在设备执行上述任一项所述的项集挖掘方法。Embodiments of the present invention further provide a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, wherein, when the computer program runs, a device on which the computer-readable storage medium is located is controlled to perform any of the above-mentioned tasks. The itemset mining method described in one item.
与现有技术相比，本发明的有益效果是：Compared with the prior art, the beneficial effects of the present invention are:
本发明实施例提供了一种项集挖掘方法，从获取的大量车辆故障数据中，挖掘出行驶数据与故障类之间的隐藏关系，能够及时并有效地确定车辆发生故障的零部件，确定故障类型及故障原因，防止故障恶化而产生重大事故，显著提高了故障诊断准确率。The embodiment of the present invention provides an itemset mining method, which can mine the hidden relationship between the driving data and the fault category from a large amount of obtained vehicle fault data, so as to timely and effectively determine the parts of the vehicle that have failed, and determine the fault. Types and causes of failures, preventing major accidents from worsening failures, and significantly improving the accuracy of fault diagnosis.
上述说明仅是本发明技术方案的概述，为了能够更清楚了解本发明的技术手段，并可依照说明书的内容予以实施，以下以本发明的较佳实施例并配合附图详细说明如后。本发明的具体实施方式由以下实施例及其附图详细给出。The above description is only an overview of the technical solution of the present invention. In order to understand the technical means of the present invention more clearly, and implement it according to the content of the description, the preferred embodiments of the present invention are described in detail below with the accompanying drawings. Specific embodiments of the present invention are given in detail by the following examples and the accompanying drawings.
附图说明Description of drawings
此处所说明的附图用来提供对本发明的进一步理解，构成本申请的一部分，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。在附图中：The accompanying drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the attached image:
图1是本发明提供的一种终端设备的一个优选实施例的结构示意图。FIG. 1 is a schematic structural diagram of a preferred embodiment of a terminal device provided by the present invention.
具体实施方式Detailed ways
以下结合附图对本发明的原理和特征进行描述，所举实例只用于解释本发明，并非用于限定本发明的范围。在下列段落中参照附图以举例方式更具体地描述本发明。根据下面说明和权利要求书，本发明的优点和特征将更清楚。需说明的是，附图均采用非常简化的形式且均使用非精准的比例，仅用以方便、明晰地辅助说明本发明实施例的目的。The principles and features of the present invention will be described below with reference to the accompanying drawings. The examples are only used to explain the present invention, but not to limit the scope of the present invention. The invention is described in more detail by way of example in the following paragraphs with reference to the accompanying drawings. The advantages and features of the present invention will become apparent from the following description and claims. It should be noted that, the accompanying drawings are all in a very simplified form and in inaccurate scales, and are only used to facilitate and clearly assist the purpose of explaining the embodiments of the present invention.
需要说明的是，当组件被称为“固定于”另一个组件，它可以直接在另一个组件上或者也可以存在居中的组件。当一个组件被认为是“连接”另一个组件，它可以是直接连接到另一个组件或者可能同时存在居中组件。当一个组件被认为是“设置于”另一个组件，它可以是直接设置在另一个组件上或者可能同时存在居中组件。本文所使用的术语“垂直的”、“水平的”、“左”、“右”以及类似的表述只是为了说明的目的。It should be noted that when a component is referred to as being "fixed to" another component, it can be directly on the other component or there may also be a centered component. When a component is considered to be "connected" to another component, it may be directly connected to the other component or there may be a co-existence of an intervening component. When a component is considered to be "set on" another component, it may be directly set on the other component or there may be a co-existing centered component. The terms "vertical," "horizontal," "left," "right," and similar expressions are used herein for illustrative purposes only.
除非另有定义，本文所使用的所有的技术和科学术语与属于本发明的技术领域的技术人员通常理解的含义相同。本文中在本发明的说明书中所使用的术语只是为了描述具体的实施例的目的，不是旨在于限制本发明。本文所使用的术语“及/或”包括一个或多个相关的所列项目的任意的和所有的组合。Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terms used herein in the description of the present invention are for the purpose of describing specific embodiments only, and are not intended to limit the present invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
本发明实施例中，一种项集挖掘方法，包括以下步骤：In an embodiment of the present invention, an itemset mining method includes the following steps:
第一步，首先采集大货车的车辆行驶数据和故障类型，得到具有故障类标记的大货车故障类型数据集；The first step is to first collect the vehicle driving data and fault types of the large truck, and obtain a large truck fault type data set with fault class labels;
第二步，根据大货车每次相同类型故障发生时的行驶数据，得到具有故障类标记的行驶数据集；In the second step, according to the driving data of the large truck every time the same type of fault occurs, a driving data set with fault class labels is obtained;
第三步，确定行驶数据集集合中每个类型参数数据的频繁概率，并按照频繁概率将大货车行驶数据集集集合中的类型参数数据进行排序；The third step is to determine the frequent probability of each type of parameter data in the driving data set, and sort the type parameter data in the large truck driving data set according to the frequent probability;
第四步，根据大货车行驶数据集所包括高频繁概率的类型参数数据，确定大货车行驶故障规律。The fourth step is to determine the driving failure rule of the large truck according to the type parameter data with high frequent probability included in the large truck driving data set.
具体的，通过设置在大货车上的多个传感器，获取设定区域、设定时间段内大货车的行驶数据。Specifically, through a plurality of sensors arranged on the large truck, the driving data of the large truck in the set area and the set time period are acquired.
具体的，行驶数据包括车辆发生故障时各零部件的相关参数数据和车辆环境数据。Specifically, the driving data includes relevant parameter data of each component and vehicle environment data when the vehicle fails.
具体的，车辆环境数据包括车辆的振动幅度与频率，车辆周围空气的温度与湿度，车辆位置处的海拔高度。Specifically, the vehicle environment data includes the vibration amplitude and frequency of the vehicle, the temperature and humidity of the air surrounding the vehicle, and the altitude at the location of the vehicle.
具体的，各零部件的相关参数数据包括发动机油量、发动机冷却液液面高度、制动液液面高度、离合器总泵液面高度、皮带振动幅度、轮胎气压、蓄电池电池状态等。Specifically, the relevant parameter data of each component includes engine oil volume, engine coolant level, brake fluid level, clutch master cylinder level, belt vibration amplitude, tire air pressure, battery status, and the like.
具体的，行驶数据为故障发生时前三个小时内的行驶数据。Specifically, the driving data is the driving data within the first three hours when the fault occurs.
一种项集挖掘装置，包括：An itemset mining device, comprising:
第一数据处理模块，用于采集大货车的车辆行驶数据和故障类型，得到具有故障类标记的大货车故障类型数据集；a first data processing module, used for collecting vehicle driving data and fault types of the large truck, and obtaining a large truck fault type data set with fault type marks;
第二数据处理模块，用于根据大货车每次相同类型故障发生时的行驶数据，得到具有故障类标记的行驶数据集；The second data processing module is configured to obtain a driving data set with fault class labels according to the driving data of the large truck every time the same type of fault occurs;
第三数据处理模块，用于确定行驶数据集集合中每个类型参数数据的频繁概率，并按照频繁概率将大货车行驶数据集集集合中的类型参数数据进行排序；The third data processing module is used to determine the frequent probability of each type of parameter data in the driving data set, and sort the type parameter data in the large truck driving data set according to the frequent probability;
第四评估预测模块，用于根据大货车行驶数据集所包括高频繁概率的类型参数数据，确定大货车行驶故障规律。The fourth evaluation and prediction module is used for determining the driving failure rule of the large truck according to the type parameter data with high frequent probability included in the driving data set of the large truck.
请参阅图1，图1是本发明提供的一种终端设备的一个优选实施例的结构示意图。所述终端设备包括处理器、存储器以及存储在所述存储器中且被配置为由所述处理器执行的计算机程序，所述处理器执行所述计算机程序时实现上述任一实施例所述的项集挖掘方法。Please refer to FIG. 1 , which is a schematic structural diagram of a preferred embodiment of a terminal device provided by the present invention. The terminal device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, when the processor executes the computer program, the items described in any of the above embodiments are implemented Set mining methods.
优选地，所述计算机程序可以被分割成一个或多个模块/单元(如计算机程序1、计算机程序2、……)，所述一个或者多个模块/单元被存储在所述存储器中，并由所述处理器执行，以完成本发明。所述一个或多个模块/单元可以是能够完成特定功能的一系列计算机程序指令段，该指令段用于描述所述计算机程序在所述终端设备中的执行过程。Preferably, the computer program can be divided into one or more modules/units (eg computer program 1, computer program 2, ...), the one or more modules/units are stored in the memory, and Executed by the processor to complete the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.
所述处理器可以是中央处理单元(Central Processing Unit，CPU)，还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等，通用处理器可以是微处理器，或者所述处理器也可以是任何常规的处理器，所述处理器是所述终端设备的控制中心，利用各种接口和线路连接所述终端设备的各个部分。The processor may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field Programmable Gate Array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may be any A conventional processor, which is the control center of the terminal equipment, uses various interfaces and lines to connect various parts of the terminal equipment.
所述存储器主要包括程序存储区和数据存储区，其中，程序存储区可存储操作系统、至少一个功能所需的应用程序等，数据存储区可存储相关数据等。此外，所述存储器可以是高速随机存取存储器，还可以是非易失性存储器，例如插接式硬盘，智能存储卡(SmartMedia Card，SMC)、安全数字(Secure Digital，SD)卡和闪存卡(Flash Card)等，或所述存储器也可以是其他易失性固态存储器件。The memory mainly includes a program storage area and a data storage area, wherein the program storage area can store an operating system, an application program required for at least one function, and the like, and the data storage area can store related data and the like. In addition, the memory may be a high-speed random access memory, and may also be a non-volatile memory, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, and a flash memory card ( Flash Card), etc., or the memory can also be other volatile solid-state storage devices.
需要说明的是，上述终端设备可包括，但不仅限于，处理器、存储器，本领域技术人员可以理解，图1的结构示意图仅仅是上述终端设备的示例，并不构成对上述终端设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件。It should be noted that the above-mentioned terminal equipment may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the schematic structural diagram of FIG. 1 is only an example of the above-mentioned terminal equipment, and does not constitute a limitation on the above-mentioned terminal equipment. More or fewer components than shown may be included, or some components may be combined, or different components.
本发明实施例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包括存储的计算机程序，其中，在所述计算机程序运行时控制所述计算机可读存储介质所在设备执行上述任一实施例所述的项集挖掘方法。Embodiments of the present invention further provide a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, wherein, when the computer program runs, a device on which the computer-readable storage medium is located is controlled to perform any of the above-mentioned tasks. The itemset mining method according to an embodiment.
本发明实施例提供了一种项集挖掘方法，从获取的大量车辆故障数据中，挖掘出行驶数据与故障类之间的隐藏关系，能够及时并有效地确定车辆发生故障的零部件，确定故障类型及故障原因，防止故障恶化而产生重大事故，显著提高了故障诊断准确率。The embodiment of the present invention provides an itemset mining method, which can mine the hidden relationship between the driving data and the fault category from a large amount of obtained vehicle fault data, so as to timely and effectively determine the parts of the vehicle that have failed, and determine the fault. Types and causes of failures, preventing major accidents from worsening failures, and significantly improving the accuracy of fault diagnosis.
以上所述，仅为本发明的较佳实施例而已，并非对本发明作任何形式上的限制；凡本行业的普通技术人员均可按说明书附图所示和以上所述而顺畅地实施本发明；但是,凡熟悉本专业的技术人员在不脱离本发明技术方案范围内，利用以上所揭示的技术内容而做出的些许更动、修饰与演变的等同变化，均为本发明的等效实施例；同时,凡依据本发明的实质技术对以上实施例所作的任何等同变化的更动、修饰与演变等，均仍属于本发明的技术方案的保护范围之内。The above descriptions are only preferred embodiments of the present invention, and do not limit the present invention in any form; any person of ordinary skill in the industry can smoothly implement the present invention as shown in the accompanying drawings and the above descriptions. However, all those skilled in the art who are familiar with the technical solutions of the present invention make use of the above-disclosed technical content to make some changes, modifications and equivalent changes of evolution, all of which are equivalent implementations of the present invention. At the same time, any alteration, modification and evolution of any equivalent changes made to the above embodiments according to the essential technology of the present invention still fall within the protection scope of the technical solutions of the present invention.
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