【作者】 陈欣；

【导师】 郭进；

【作者基本信息】 西南交通大学 ， 交通信息工程及控制， 2016， 硕士

【摘要】 轨道电路作为铁路信号系统中最重要、最关键的基础设备之一,在列控系统中占据着重要的地位,也是铁路信号设备中最容易发生故障的设备之一,是影响铁路运输效率和安全性能的关键性因素。然而,我国目前的故障诊断技术尚不完善,不能满足我国铁路运输事业快速发展的需求。因此,对于轨道电路故障进行高效、准确地诊断具有重要的研究意义。本论文主要是研究轨道电路的补偿电容断线和绝缘节破损两种故障,针对当前检测方式不够完善、缺乏先进有效的数据处理方法等情况,做了下面几个方面的工作：(1)阐述了ZPW-2000A型无绝缘轨道电路的结构,在此基础上,建立了基于二端口网络理论的轨道电路等效电路模型,并根据所建模型仿真得到的各设备电流电压值与模拟盘实验平台测试得到的数据作对比,验证所建模型的正确性；之后对轨道电路的常见故障做了分析,重点介绍了绝缘节破损和补偿电容断线两种故障,并利用MATLAB软件对补偿电容断线时、绝缘节破损时和轨道电路正常状态的机车信号感应电压幅值包络进行仿真,通过比较仿真结果,分析这两种故障对感应电压幅值包络的影响。(2)总结了故障特征提取的三种方法,选取适合无绝缘轨道电路故障特征提取的方法即小波理论,对小波理论知识加以说明,然后采用小波变换分解机车信号感应电压幅值信号曲线,从分解得到的细节信号中提取对故障诊断更敏感的特征参数,作为故障诊断模型的输入变量。(3)对支持向量机(SVM)的分类原理作了说明,建立了基于SVM的无绝缘轨道电路的故障诊断模型。之后从诊断模型参数的选取、输入数据的预处理、输出故障集的确定等方面阐述了故障诊断的过程,最后设计了随机选取和交叉验证两种确定模型参数的方法,并使用MATLAB工具对这两种方法进行仿真,分析对比两种仿真结果,结果表明基于交叉验证的SVM模型故障诊断结果比随机选取参数的方法要更准确。(4)概述了粒子群(PSO)算法的基础理论,在这些理论知识的基础上,提出了采用模拟退火(SA)算法与PSO算法相融合,针对SVM的参数难以选择的问题,提出了用SAPSO优化SVM的参数,采用SAPSO算法的全局搜索能力和局部搜索能力,得到参数的最优解,之后设计了SAPSO-SVM的无绝缘轨道电路故障诊断模型,最后通过MATLAB仿真得到SAPSO-SVM模型对轨道电路故障诊断的准确率,并与第四章中建立的模型作比较,得到结论：SAPSO-SVM方法的轨道电路故障诊断准确率最高。更多还原

【Abstract】 Track circuit is one of the most important and critical infrastructure for the railway signaling system. It occupies an important position in the train control system, but also is one of the most prone to failure devices in railway signaling equipment. It is a key factor that affects the rail transport efficiency and safety performance. However, the current of fault diagnosis technology is not perfect, still can’t meet the needs of the development of China’s railway transportation. Therefore, a scientific, efficient and accurate diagnosis has important significance for the track circuit fault.The track circuit compensation capacitor disconnection and insulation damaged section were mainly studied in this article. Depending on the current detection method is not perfect, extreme lack of advanced and effective data processing methods, etc, the main work of this article are as follows:(1) This article describes the structure and working principle of ZPW-2000A system, on this basis, established an equivalent model of two-port network theory for track circuit. Compared the current and voltage values obtained by simulating model and the test data from experimental platform, verifying the correctness of the built model, and then it analyzed the common track circuit faults, gave a key talk for insulation damage and compensation capacitor section break, simulated breakage compensation capacitor, insulating section breakage and the track circuit normal state of induced voltage curve by MATLAB. Compared the simulation results and analyzed the influence of these two fault on the locomotive signal induced voltage amplitude.(2) This article summarizes three fault feature extraction method, selects wavelet transform theory as the appropriate method of track circuit fault feature extraction, then decomposition the locomotive signal induced voltage amplitude signal curve based on wavelet transform theory, and the extraction of more sensitive characteristic parameters for fault diagnosis from the decomposition of the detail signal is used for input variables of fault diagnosis model.(3) The classification principle of support vector machine is explained, and the fault diagnosis model of the non-insulated track circuit based on S VM is established. And then the process of fault diagnosis is expounded from the aspects of the selection of parameters, the pretreatment of input data and the determination of output fault sets. Finally, it designs the random selection and cross validation two determine the parameter model method, and use MATLAB to simulate the two models, analysis and comparison of two kinds of simulation results.(4) This paper summarizes the basic theory of PSO algorithm, based on these theoretical knowledge, aiming at the problem that the parameters of support vector machine is difficult to be selected, simulated annealing (SA) algorithm and PSO algorithm integration, is proposed to optimize the parameters of SVM. By using the global search ability and local search ability of SAPSO, the optimization of the parameters c and g in SVM can be realized quickly, and the optimal solution of the parameters is obtained. The fault diagnosis model of the SAPSO-SVM non insulated track circuit is designed, and the accuracy of the SAPSO-SVM model to track circuit fault diagnosis is obtained by MATLAB simulation, and the simulation results are compared with the simulation results of SVM fault diagnosis model.更多还原