CN102607643B - Overheat fault diagnosis and early warning method for electrical equipment of traction substation of electrified railway - Google Patents
Overheat fault diagnosis and early warning method for electrical equipment of traction substation of electrified railway Download PDFInfo
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Abstract
本发明公开了一种电气化铁路牵引变电站电气设备过热故障诊断及预警方法。该故障预警系统由无线传感器、集中器、计算机等部分组成。其中无线传感器包括无线温度传感器、无线温湿度传感器以及无线电流传感器分别实现对电气设备温度、环境温境湿度及输电线电流的测量;集中器实现整个牵引变电站内各无线传感器监测点数据的接收,并将收集的数据上传至计算机;计算机完成监测数据的采集、存储,并根据采集的数据完成电气设备过热故障的智能诊断及预警。该系统能够为电气化铁路牵引变电站的运行和检修提供科学依据,确保铁路供电安全。
The invention discloses an overheating fault diagnosis and early warning method for electrical equipment in an electrified railway traction substation. The fault warning system is composed of wireless sensors, concentrators, computers and other parts. The wireless sensors include wireless temperature sensors, wireless temperature and humidity sensors, and wireless current sensors to measure the temperature of electrical equipment, ambient temperature and humidity, and transmission line current; the concentrator realizes the reception of data from each wireless sensor monitoring point in the entire traction substation. And upload the collected data to the computer; the computer completes the collection and storage of monitoring data, and completes the intelligent diagnosis and early warning of electrical equipment overheating faults based on the collected data. The system can provide a scientific basis for the operation and maintenance of electrified railway traction substations and ensure the safety of railway power supply.
Description
技术领域technical field
本发明涉及一种故障诊断及预警系统及方法,特别涉及一种电气化铁路牵引变电站电气设备过热故障诊断及预警方法。The invention relates to a fault diagnosis and early warning system and method, in particular to a fault diagnosis and early warning method for electrical equipment overheating in traction substations of electrified railways.
背景技术Background technique
牵引变电站内存在大量的高压隔离开关、互感器、断路器、变压器以及高压开关柜等电气设备,其接头数量众多,这些电气设备担负着电力变换及输送的重要任务,但是在长时间连续运行的情况下常常会因接头处接触不良、老化或表面氧化等原因造成接触点阻值增大,进而出现温升导致发热过多而烧坏等情况,如果这些发热部位的温度没有得到及时有效的监测,最终可能导致设备损坏,从而引发停电甚至火灾事故的发生,对电气化铁路的运行带来的极大的安全隐患。因此应当采取必要的检测措施了解各电气设备当前运行状态,根据设备实时运行状态数据并结合历史数据分析其变化趋势,从而达到减少供电系统事故隐患,降低事故发生率,缩短故障查找、检修时间,确保供电系统安全可靠运行的目的。There are a large number of electrical equipment such as high-voltage isolating switches, transformers, circuit breakers, transformers, and high-voltage switchgears in the traction substation. Under normal circumstances, the resistance of the contact point increases due to poor contact at the joint, aging or surface oxidation, etc., and then the temperature rise causes excessive heat and burns out. If the temperature of these heat-generating parts is not monitored in time and effectively , which may eventually lead to equipment damage, resulting in power outages or even fire accidents, which will bring great safety hazards to the operation of electrified railways. Therefore, necessary detection measures should be taken to understand the current operating status of each electrical equipment, and its change trend should be analyzed according to the real-time operating status data of the equipment and combined with historical data, so as to reduce the hidden danger of accidents in the power supply system, reduce the incidence of accidents, and shorten the time for fault finding and maintenance. The purpose of ensuring the safe and reliable operation of the power supply system.
目前国内外主要采用的电气设备温度监测技术有两大类:一是采用红外技术(红外测温计或红外成像仪)以人工巡检方式来进行温度检测;二是通过布置有线传感器网络,如采用光纤进行温度检测。但这些方法都无法满足牵引变电站的温度监测需求。主要是因为:牵引变电站不同于一般变电站,其供电线路段有火车通过时,相关电气设备才有电流通过,设备过热故障隐患才能显现出来,而在没有火车通过时,由于电气设备负载电流很小,此时即使监测相关设备温度也无法发现故障隐患。红外技术测温由于是人工检测,无法实现实时在线检测,对设备内部的温度也无法测量并且存在较大误差,因此无法实现过热故障的及时、准确发现,光纤测温技术由于布线复杂不利于大规模应用,而且很容易受到污染从而导致测温准确性大幅度下降。At present, there are two main types of electrical equipment temperature monitoring technologies used at home and abroad: one is to use infrared technology (infrared thermometer or infrared imager) to detect temperature by manual inspection; the other is to arrange wired sensor networks, such as Optical fiber is used for temperature detection. However, none of these methods can meet the temperature monitoring requirements of traction substations. The main reason is that traction substations are different from general substations. When there is a train passing through the power supply line section, the relevant electrical equipment has current passing through, and the hidden danger of equipment overheating failure can be revealed. When there is no train passing, the load current of the electrical equipment is very small At this time, even if the temperature of the relevant equipment is monitored, hidden troubles cannot be found. Because infrared technology temperature measurement is manual detection, real-time online detection cannot be realized, and the temperature inside the device cannot be measured and there are large errors, so it is impossible to realize timely and accurate detection of overheating faults. Optical fiber temperature measurement technology is not conducive to large-scale due to complex wiring. Large-scale applications, and are easily contaminated, resulting in a significant drop in temperature measurement accuracy.
近年来基于无线传感器的测温技术开始得到了广泛的应用。但其在变电站电气设备监控方面存在以下局限性:检测对象仅为被监测点的温度,通过简单的设定一个温度阈值,确定是否出现了电气设备过热故障。根据常识,我们知道在不同的环境温度和湿度下,同样的电气设备温度往往表示不同的过热故障结果,不同的线路电流也会导致不同的运行温度结果,因此是否出现过热故障,不仅仅与被测点的设备温度有关,还与环境温度、环境湿度以及线路电流有关,是一个综合判断的结果。In recent years, temperature measurement technology based on wireless sensors has been widely used. However, it has the following limitations in the monitoring of electrical equipment in substations: the detection object is only the temperature of the monitored point, and it is determined whether an electrical equipment overheating fault occurs by simply setting a temperature threshold. According to common sense, we know that under different ambient temperature and humidity, the same electrical equipment temperature often indicates different overheating fault results, and different line currents will also lead to different operating temperature results, so whether there is an overheating fault is not only related to the The temperature of the equipment at the measuring point is related to the ambient temperature, ambient humidity and line current, which is the result of a comprehensive judgment.
发明内容Contents of the invention
本发明所要解决的技术问题是提供一种电气化铁路牵引变电站电气设备过热故障诊断及预警方法,通过无线传感器实现对电气设备温度、环境温度、环境湿度和线路电流进行在线检测,建立基于最小二乘支持向量机(least squaressupport vector machines简称LSSVM)的故障诊断及预警模型,从而实现对电气设备过热故障的准确诊断和预警,为电气设备的可靠运行提供依据,大幅度的减少故障发生率。The technical problem to be solved by the present invention is to provide a method for diagnosing and early warning of electrical equipment overheating faults in traction substations of electrified railways. The online detection of electrical equipment temperature, ambient temperature, ambient humidity and line current is realized through wireless sensors, and the method is established based on least squares Support vector machine (least square support vector machines referred to as LSSVM) fault diagnosis and early warning model, so as to realize accurate diagnosis and early warning of electrical equipment overheating faults, provide a basis for reliable operation of electrical equipment, and greatly reduce the incidence of failure.
为实现上述目的,本发明采用以下技术手段:To achieve the above object, the present invention adopts the following technical means:
电气化铁路牵引变电站电气设备过热故障诊断及预警系统,其特征在于:主要由无线传感器、集中器及计算机组成,其中无线传感器包括用于测量电气设备温度的无线温度传感器、用于测量环境温湿度的无线环境温湿度传感器、用于测量线路电流的无线电流传感器;集中器负责收集无线传感器数据并上传至计算机,计算机根据上传的数据利用最小二乘支持向量机过热故障预警模型实现电气设备过热故障的智能诊断与在线预警。The electric railway traction substation electrical equipment overheating fault diagnosis and early warning system is characterized in that it is mainly composed of wireless sensors, concentrators and computers, wherein the wireless sensors include wireless temperature sensors for measuring the temperature of electrical equipment, and for measuring ambient temperature and humidity. Wireless environmental temperature and humidity sensors, wireless current sensors used to measure line current; the concentrator is responsible for collecting wireless sensor data and uploading it to the computer, and the computer uses the least squares support vector machine overheating fault early warning model to realize the overheating fault detection of electrical equipment according to the uploaded data. Intelligent diagnosis and online early warning.
所述无线温度传感器在每个需要进行过热故障监控的电气设备上安装一只;所述无线环境温湿度传感器在具有共同环境特征的区域各安装一只;所述无线电流传感器在每条具有共同电流特征的线路上各安装一只;One of the wireless temperature sensors is installed on each electrical equipment that requires overheating fault monitoring; one of the wireless environmental temperature and humidity sensors is installed in each area with common environmental characteristics; the wireless current sensor is installed on each of the common environmental characteristics. Install one on each line with current characteristics;
所述各种无线传感器均以基于ZIGBEE技术的CC2430芯片为核心;所述无线温度传感器采用DS18B20感应电气设备温度;所述无线温湿度传感器采用DHT21感应环境温湿度;所述无线电流传感器采用感应式线圈获得电流信号;The various wireless sensors are based on the CC2430 chip based on ZIGBEE technology as the core; the wireless temperature sensor uses DS18B20 to sense the temperature of electrical equipment; the wireless temperature and humidity sensor uses DHT21 to sense the temperature and humidity of the environment; the wireless current sensor uses an inductive The coil obtains the current signal;
一种电气化铁路牵引变电站电气设备过热故障诊断及预警方法,包括以下步骤:A method for diagnosing and early warning of overheating faults of electrical equipment in traction substations of electrified railways, comprising the following steps:
(1)无线传感器测量电气设备监测点温度T设备、环境温度T环境、环境湿度H环境和线路电流I线路,然后将这些数据传输给集中器;(1) The wireless sensor measures the electrical equipment monitoring point temperature T equipment , ambient temperature T environment , ambient humidity H environment and line current I line , and then transmits these data to the concentrator;
(2)集中器接收到无线传感器传输的数据后,将这些数据以以太网传送至计算机,然后将上述数据的上报周期作为响应数据包返回至相应的传感器;(2) After the concentrator receives the data transmitted by the wireless sensor, it transmits the data to the computer via Ethernet, and then returns the reporting cycle of the above data as a response data packet to the corresponding sensor;
(3)计算机接收到集中器发送的上报数据后,首先进行存储,然后根据数据类型按照如下规则进行处理:如果数据为环境温度、环境湿度或者线路电流,则不做处理;如果数据为电气设备温度,则根据电气设备的温度数据确定测点位置,然后从计算机中调出环境温度数据、环境湿度数据,以及线路电流数据,组成测量数据{T设备,T环境,H环境,I线路};(3) After the computer receives the reported data sent by the concentrator, it first stores it, and then processes it according to the following rules according to the data type: if the data is ambient temperature, ambient humidity or line current, it will not be processed; if the data is electrical equipment Temperature, the position of the measuring point is determined according to the temperature data of the electrical equipment, and then the ambient temperature data, ambient humidity data, and line current data are called out from the computer to form measurement data {T equipment , T environment , H environment , I line };
(4)将步骤(3)获得的测量数据{T设备,T环境,H环境,I线路}输入建立的最小二乘支持向量机过热故障预警模型,得到故障诊断及预警结果。(4) Input the measurement data obtained in step (3) {T equipment , T environment , H environment , I line } into the established least squares support vector machine overheating fault early warning model to obtain fault diagnosis and early warning results.
所述最小二乘支持向量机过热故障预警模型按照以下步骤建立:The least squares support vector machine overheating fault early warning model is established according to the following steps:
(1)确定核函数种类:以径向基函数作为核函数,其中,x为当前输入数据,xn为训练样本集,δ为径向基函数的宽度参数;(1) Determine the type of kernel function: radial basis function As a kernel function, where x is the current input data, x n is the training sample set, and δ is the width parameter of the radial basis function;
(2)采用标准搜索算法确定模型的超参数{δ2,γ},其中,γ为正则化参数;(2) Use the standard search algorithm to determine the hyperparameters {δ 2 ,γ} of the model, where γ is the regularization parameter;
(3)以样本数据库中的样本作为训练数据集,对模型进行训练,获得模型参数{αn,b},其中,αn为拉格朗日算子(又称支持因子),b为偏置值;(3) Use the samples in the sample database as the training data set to train the model and obtain the model parameters {α n ,b}, where α n is the Lagrangian operator (also known as the support factor), and b is the partial set value;
(4)得到故障诊断模型: (4) Get the fault diagnosis model:
在进行故障诊断之前,首先,对获取的数据进行归一化处理;Before fault diagnosis, firstly, normalize the acquired data;
计算机根据故障诊断的结果对电气设备温度数据的上报周期进行调整;所述线路电流的上报采用实时召唤方式,即当计算机接收到无线电气设备的温度数据后,召唤线路电流数据;The computer adjusts the reporting period of the temperature data of the electrical equipment according to the result of the fault diagnosis; the reporting of the line current adopts a real-time calling method, that is, when the computer receives the temperature data of the wireless electrical equipment, it calls the line current data;
最小二乘支持向量机过热故障预警模型在收集到新故障样本达到一定数量后,对模型进行更新训练。After the least squares support vector machine overheating fault early warning model has collected a certain number of new fault samples, the model is updated and trained.
与现有技术相比,本发明电气化铁路牵引变电站电气设备过热故障诊断及预警系统及方法至少具有以下优点:本发明采用了无线传感器实现电气设备温度的测量,有效解决了高压设备难以在线实时检测的问题;采用多种信息综合诊断及预警,可有效消除因环境温度、湿度以及线路载流量的变化而引起的电气设备温度变化,从而实现过热故障的准确诊断,为供电安全提供了可靠保障。Compared with the prior art, the system and method for overheating fault diagnosis and early warning of electrical equipment in electrified railway traction substations have at least the following advantages: the invention uses wireless sensors to measure the temperature of electrical equipment, which effectively solves the problem that high-voltage equipment is difficult to detect online in real time The use of a variety of information comprehensive diagnosis and early warning can effectively eliminate the temperature changes of electrical equipment caused by changes in ambient temperature, humidity and line carrying capacity, thereby realizing accurate diagnosis of overheating faults and providing a reliable guarantee for power supply safety.
附图说明Description of drawings
图1是本发明牵引变电站电气设备过热故障在线诊断及预警系统结构示意图;Fig. 1 is a schematic structural diagram of the online diagnosis and early warning system for overheating faults of electrical equipment in traction substations of the present invention;
图2是无线温度传感器硬件结构图;Fig. 2 is a hardware structural diagram of a wireless temperature sensor;
图3是无线温度传感器软件工作流程图;Fig. 3 is a wireless temperature sensor software work flow chart;
图4是故障诊断及预警流程图。Figure 4 is a flowchart of fault diagnosis and early warning.
具体实施方式Detailed ways
下面结合附图对本发明电气化铁路牵引变电站电气设备过热故障诊断及预警系统及方法的一个实施例进行详细说明:An embodiment of the electrical equipment overheat fault diagnosis and early warning system and method of the electrified railway traction substation of the present invention will be described in detail below in conjunction with the accompanying drawings:
本发明对电气化铁路牵引变电站电气设备过热故障进行在线诊断及预警,其系统总体结构如图1所示,包括用于测量电气设备温度的无线温度传感器、用于测量环境温湿度的无线环境温湿度传感器、用于测量线路电流的无线电流传感器、用于收集传感器数据的集中器和用于故障诊断及统一监控的计算机。The present invention performs on-line diagnosis and early warning for overheating faults of electrical equipment in traction substations of electrified railways. Sensors, wireless current sensors for measuring line current, concentrators for collecting sensor data, and computers for fault diagnosis and unified monitoring.
在一个牵引变电站内,对于每个需要进行过热故障监控的电气设备(如变压器、隔离开关、断路器、电流互感器等处的设备线夹、开关柜内的母排等)安装一只无线温度传感器;对于具有共同环境特征的区域各安装一只无线环境温湿度传感器,测量得到的环境温度和湿度数据结果供该区域内的所有电气设备监测点故障诊断共用,例如在牵引变电站室外安装一只环境温湿度传感器,其测量结果供所有室外电气设备过热故障诊断使用,高压室内安装一只环境温湿度传感器,其测量结果供所有在高压室内电气设备过热故障诊断使用;在每条具有共同电流特征的线路上各安装一只无线电流传感器,其数据结果供该条线路上的所有电气设备监测点故障诊断共用。In a traction substation, install a wireless temperature controller for each electrical equipment that needs to be monitored for overheating faults (such as equipment clamps at transformers, isolating switches, circuit breakers, current transformers, etc., busbars in switch cabinets, etc.) Sensors; install a wireless ambient temperature and humidity sensor in areas with common environmental characteristics, and the measured ambient temperature and humidity data results are shared by all electrical equipment monitoring points in the area for fault diagnosis. The ambient temperature and humidity sensor, its measurement results are used for overheating fault diagnosis of all outdoor electrical equipment. An environmental temperature and humidity sensor is installed in the high-voltage room, and its measurement results are used for all overheating fault diagnosis of electrical equipment in the high-voltage room; each line has a common current characteristic A wireless current sensor is installed on each line, and its data results are shared by all electrical equipment monitoring points on the line for fault diagnosis.
无线传感器完成电气设备监测点温度T设备、环境温度T环境、环境湿度H环境和线路电流I线路的测量;并将测量结果通过无线方式传送至集中器;集中器根据牵引变电站具体情况可以安装多个,例如在室外安装一只,负责室外传感器数据的收集;高压室内安装一只,负责高压室内传感器数据的收集。The wireless sensor completes the measurement of the electrical equipment monitoring point temperature T equipment , ambient temperature T environment , environmental humidity H environment and line current I line ; and transmits the measurement results to the concentrator by wireless; the concentrator can be installed according to the specific conditions of the traction substation. For example, one is installed outdoors, which is responsible for the collection of outdoor sensor data; one is installed in the high-pressure room, which is responsible for the collection of sensor data in the high-pressure room.
集中器接收到无线传感器数据后,将数据通过工业以太网传送至计算机,并将上述传感器的上报周期作为响应数据包返回至相应传感器。After the concentrator receives the wireless sensor data, it transmits the data to the computer through the industrial Ethernet, and returns the reporting period of the above sensor as a response data packet to the corresponding sensor.
计算机在接收到上报数据后,首先进行数据存储,然后根据数据类型按照如下规则进行处理:如果数据为环境温度、环境湿度或者线路电流,则不做处理;如果数据为电气设备温度,则执行过热故障诊断及预警程序,具体为:After the computer receives the reported data, it first stores the data, and then processes it according to the following rules according to the data type: if the data is ambient temperature, ambient humidity or line current, it will not be processed; if the data is the temperature of electrical equipment, perform overheating Fault diagnosis and early warning procedures, specifically:
计算机接收到电气设备温度数据,并完成数据存储后,首先执行数据匹配程序:根据接收到的电气设备温度数据,确定测点位置(即电气设备温度传感器ID),然后调出与该测点位置匹配的环境温湿度传感器ID、线路电流传感器ID,通过召唤方式获取线路电流,通过从历史数据库中查询最新数据获取环境温湿度数据,组成测量数据{T设备,T环境,H环境,I线路};After the computer receives the electrical equipment temperature data and completes the data storage, it first executes the data matching program: according to the received electrical equipment temperature data, determine the location of the measuring point (that is, the ID of the electrical equipment temperature sensor), and then call out the Match the ambient temperature and humidity sensor ID and the line current sensor ID, obtain the line current by calling, and obtain the environmental temperature and humidity data by querying the latest data from the historical database to form measurement data {T equipment , T environment , H environment , I line } ;
将获得的测量数据集输入建立好的LSSVM过热故障预警模型,获得故障诊断及预警结果,并将结果在监控软件界面上显示。Input the obtained measurement data set into the established LSSVM overheating fault early warning model, obtain fault diagnosis and early warning results, and display the results on the monitoring software interface.
下面结合一个具体的应用实例加以说明:The following is combined with a specific application example to illustrate:
如图2所示,用于牵引变电站电气设备温度测量的无线传感器,采用基于ZIGBEE技术的CC2430芯片实现,该芯片内部集成了低功耗单片机、电源管理模块、模数转换模块、射频模块以及存储模块等,以一个芯片即可实现数据的采集、处理以及无线传输等工作。温度采集通过DS18B20实现,该温度芯片为数字式温度传感器,可通过数字总线方式获得温度数据,且其误差在±1.5℃内。通过该技术设计的无线传感器其通讯距离可达500米,完全满足电气设备温度监测的需求。As shown in Figure 2, the wireless sensor used to measure the temperature of electrical equipment in traction substations is implemented using the CC2430 chip based on ZIGBEE technology, which integrates a low-power microcontroller, power management module, analog-to-digital conversion module, radio frequency module and storage Modules, etc., can realize data collection, processing and wireless transmission with one chip. The temperature acquisition is realized by DS18B20, the temperature chip is a digital temperature sensor, and the temperature data can be obtained through the digital bus, and its error is within ±1.5°C. The wireless sensor designed by this technology has a communication distance of up to 500 meters, which fully meets the needs of electrical equipment temperature monitoring.
对于环境温湿度和线路电流测量的无线传感器,其硬件结构上唯一的不同之处在于所选用的前端传感器不同,其中测量环境温湿度采用DHT21,该传感器为数字信号输出的温湿度复合传感器,测量线路电流采用自制的感应式线圈获得电流信号。For the wireless sensor for environmental temperature and humidity and line current measurement, the only difference in its hardware structure is that the selected front-end sensor is different. Among them, DHT21 is used to measure the environmental temperature and humidity. The sensor is a temperature and humidity composite sensor with digital signal output. The line current adopts the self-made induction coil to obtain the current signal.
如图3所示,无线电气设备温度传感器,其工作流程为:首先判断休眠周期是否到,休眠周期到则进入到采集温度程序,并完成数据转换、滤波等处理程序,然后将采集结果发送至集中器并等待响应数据包;接收到集中器的响应数据包后判定是否为变更参数数据包(即是否变更上报周期),如果是则根据要求变更相应参数。无线电气设备温度传感器,其上报周期可根据过热故障程度自适应调整,一组典型值为:无故障时上报周期为30分钟,轻微故障时上报周期为10分钟,中度故障时上报周期为5分钟,严重故障时上报周期为1分钟。As shown in Figure 3, the working process of the wireless electrical equipment temperature sensor is as follows: firstly, it is judged whether the dormancy cycle is over, and when the dormancy cycle is reached, it enters into the temperature collection program, completes data conversion, filtering and other processing procedures, and then sends the collection results to The concentrator waits for the response packet; after receiving the response packet from the concentrator, it is determined whether it is a parameter change packet (that is, whether to change the reporting period), and if so, change the corresponding parameter according to the requirements. Wireless electrical equipment temperature sensor, its reporting period can be adaptively adjusted according to the degree of overheating fault. A typical set of values is: 30 minutes for no fault, 10 minutes for minor fault, and 5 for moderate fault minutes, and the reporting cycle is 1 minute for serious faults.
对于环境温湿度传感器,其上报周期可人工设置,典型值为30分钟上报一次,对于电流传感器,采用召唤方式获取。For environmental temperature and humidity sensors, the reporting period can be manually set, and the typical value is to report once every 30 minutes. For current sensors, it is obtained by summoning.
计算机获得电气设备监测点温度T设备、环境温度T环境、环境湿度H环境和线路电流I线路后,采用基于LSSVM的故障诊断模型进行过热故障诊断及预警,其工作流程如图4所示。After the computer obtains the electrical equipment monitoring point temperature Tequipment , ambient temperature Tenvironment , ambient humidity Henvironment , and line current Iline , the fault diagnosis model based on LSSVM is used for overheating fault diagnosis and early warning. The workflow is shown in Figure 4.
首先判定是进行故障模型训练还是进行故障诊断,模型训练在两种情况下进行,一是在初次建立模型时使用;二是随着运行时间的变长,收集新故障样本达到一定数量时(例如新收集10条故障样本)对模型进行更新训练。First of all, it is determined whether to carry out fault model training or fault diagnosis. Model training is carried out in two cases. One is to use it when the model is first established; the other is to collect new fault samples reaching a certain number as the running time becomes longer New collection of 10 fault samples) to update the model training.
故障诊断结果分为四类,分别为无故障、轻微故障、中度故障、中度故障和严重故障,其对应于LSSVM故障模型输出分别为0、1、2、3。在建立训练样本集过程中,T设备,T环境,H环境,I线路由在线监测系统自动获取,而对应的故障类型由运行人员根据经验和分析结果进行指定。The fault diagnosis results are divided into four categories, namely no fault, minor fault, moderate fault, moderate fault and severe fault, which correspond to the output of the LSSVM fault model as 0, 1, 2, and 3, respectively. In the process of establishing the training sample set, T equipment , T environment , H environment , and I line are automatically obtained by the online monitoring system, and the corresponding fault types are specified by the operator based on experience and analysis results.
进入模型训练程序后,首先确定核函数种类,选择径向基函数作为LSSVM的核函数,其中,x为当前输入数据,xn为训练的样本集,δ为径向基函数的宽度参数;然后采用LSSVM的Matlab数学工具箱中标准搜索算法确定LSSVM模型的超参数{δ2,γ},其中,γ为正则化参数;接着,以样本数据库中的样本作为训练数据集,对LSSVM模型进行训练,获得模型参数{αn,b},其中,αn为拉格朗日算子(又称支持因子),b为偏置值,即可得到故障诊断模型:
正常监控过程,模型进入故障诊断流程,首先将获取的数据进行归一化处理,然后采用训练好的模型获得故障诊断结果并将其显示到监控界面,同时根据故障严重程度确定是否更改无线电气设备温度传感器的上报周期参数,并将相关故障数据作为样本存入样本数据库,当新增样本数量达到10条时,则进入模型更新流程,对现有故障诊断模型进行更新。In the normal monitoring process, the model enters the fault diagnosis process. First, the acquired data is normalized, and then the trained model is used Obtain the fault diagnosis result and display it on the monitoring interface, and determine whether to change the reporting cycle parameters of the wireless electrical equipment temperature sensor according to the severity of the fault, and store the relevant fault data as samples in the sample database. When the number of new samples reaches 10 When , enter the model update process to update the existing fault diagnosis model.
本发明给出的牵引变电站电气设备过热故障在线诊断方法及预警方法,通过对监测点温度、所处位置电流大小、所处环境温度以及湿度等各方面数据的融合分析,给出故障诊断结果;使得诊断结果在各种环境以及输电状况的外部条件下均能满足准确诊断预警,很好地满足了牵引变电站监控的智能化的需求,确保了铁路供电安全。The online diagnosis method and early warning method for overheating faults of electrical equipment in traction substations provided by the present invention provide fault diagnosis results through the fusion analysis of various data such as the temperature of the monitoring point, the current size of the location, the ambient temperature and humidity of the location; The diagnosis results can meet the accurate diagnosis and early warning under various environments and external conditions of power transmission conditions, which satisfies the intelligent demand for traction substation monitoring and ensures the safety of railway power supply.
以上所述仅为本发明的一种实施方式,不是全部或唯一的实施方式,本领域普通技术人员通过阅读本发明说明书而对本发明技术方案采取的任何等效的变换,均为本发明的权利要求所涵盖。The above is only one embodiment of the present invention, not all or the only embodiment. Any equivalent transformation of the technical solution of the present invention adopted by those of ordinary skill in the art by reading the description of the present invention is the right of the present invention. covered by the requirements.
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