基于小波能谱熵和改进ELM的转辙机故障预测  

Switch machine based on wavelet energy spectrum entropy and improved ELM fault prediction

作　　者：刘伯鸿[1] 王萌萌 LIU Bo-hong;WANG Meng-meng(School of Automation&Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,Gansu,China)

机构地区：[1]兰州交通大学自动化与电气工程学院,甘肃兰州730070

出　　处：《云南大学学报（自然科学版）》2022年第3期497-504,共8页Journal of Yunnan University(Natural Sciences Edition)

基　　金：国家自然科学基金(61661027).

摘　　要：为了进一步提高铁道转辙机故障预测精度和维修效率,提出了一种基于小波能谱熵和改进极限学习机(Extreme Learning Machine,ELM)的转辙机故障预测方法.首先,将采集到的转辙机功率数据用完备集合经验模态分解方法进行预处理;然后,计算各个固有模态函数的小波能谱熵值,通过核主元分析原理方法将多维特征数据降至1维,构建转辙机的退化性能指标,得出失效阈值;最后,利用自适应鲸鱼优化算法对ELM预测模型的权值和阈值进行全局寻优,以获得最优的预测模型,实现对转辙机故障趋势的预测.用Matlab软件对新方法进行实例分析,并与支持向量机和ELM模型进行对比.仿真结果表明,与传统预测模型相比,基于改进ELM模型均方误差更接近于0,决定系数更接近于1,表明该模型预测精度更高,性能更佳,证明了该方法应用于转辙机故障预测的可行性.In order to further improve the fault prediction accuracy and maintenance efficiency of switch machine,a fault prediction method of switch machine based on wavelet energy spectrum entropy and improved Extreme Learning Machine(ELM)is proposed.Firstly,the collected power data of switch machine is preprocessed with Complementary Ensemble Empirical Mode Decomposition(CEEMD)method.Then the wavelet energy spectrum entropy of each IMF component is calculated,the multidimensional characteristic data is reduced to one dimension by KPCA method,and the degradation performance index of switch machine is constructed,and the failure threshold is obtained.Finally,the weight and threshold of ELM prediction model are calculated by Adaptive Whale Optimization Algorithm(AWOA)in order to obtain the optimal prediction model,the fault trend of switch machine can be predicted.Matlab software is used to analyze the method,and compared with Support Vector Machine(SVM)and ELM model.The simulation results show that,compared with the traditional prediction model,the improved ELM model has higher prediction accuracy and better performance,which proves the feasibility of applying this method to the fault prediction of switch machine,and provides theoretical support for the realization of intelligent fault prediction of switch machine and on-site maintenance.

关 键 词：转辙机 小波能谱熵 退化性能指标 自适应鲸鱼优化算法 极限学习机 故障预测 

分 类 号：U284.92[交通运输工程—交通信息工程及控制]