噪声与振动控制2025，Vol.45Issue(2)：112-117,125,7.DOI:10.3969/j.issn.1006-1355.2025.02.018
基于改进JSOA-SVM的地铁站台门故障诊断
Fault Diagnosis of Metro Platform Doors Based on Improved JSOA-SVM
摘要
Abstract
In order to accurately diagnose the fault of Metro platform doors and to solve the problem of parameter se-lection in fault diagnosis of support vector machine(SVM),the jumping spider optimization algorithm(JSOA)was used to optimize the parameters of SVM to promote its diagnostic performance.In view of the shortcomings of JSOA,such as easy to fall into local optimization and slow rate of convergence,A multi-strategy Improved Jumping Spider Optimization Algo-rithm(IJSOA)was proposed to optimise the SVM for platform door fault diagnosis.Firstly,Teager energy operator,varia-tional mode decomposition(VMD)and refine composite multi-scale fuzzy entropy(RCMFE)were utilized to extract signal features.Secondly,the optimized JSOA algorithm was utilized to find the optimal parameter combination for SVM and con-struct the diagnostic model.Finally,the extracted feature vectors were input into the diagnostic model to achieve fault diag-nosis for the platform doors.The results show that the average recognition rate of the proposed method is 97.77%,which is more accurate than other methods and it can effectively improve the classification effect of fault diagnosis.关键词
故障诊断/地铁站台门系统/变分模态分解(VMD)/跳蛛优化算法(JSOA)/支持向量机(SVM)Key words
fault diagnosis/metro platform door system/variational mode decomposition(VMD)/jumping spider opti-mization algorithm(JSOA)/support vector machine(SVM)分类
机械制造引用本文复制引用
王若凡,朱松青,杨柳,郝飞,徐涛..基于改进JSOA-SVM的地铁站台门故障诊断[J].噪声与振动控制,2025,45(2):112-117,125,7.基金项目
国家自然科学基金青年科学基金资助项目(52005248) （52005248）
江苏省高等学校基础科学资助项目(自然科学)研究重大项目资助(23KJA460009) （自然科学）
大学生科技创新基金资助项目(TB202317007) （TB202317007）
