摘要
针对支持向量机(SVM)在车辆变速箱故障诊断中性能受参数影响较大的实际,在研究天牛须搜索(BAS)的基础上,提出基于改进天牛须搜索(IBAS)优化SVM的车辆变速箱故障诊断新方法。相比于BAS,IBAS对步长公式进行了修正,同时增加了高斯变异行为,使得算法前后期的搜索能力得到了平衡且具有跳出局部最优的能力,能够获得更优的SVM参数。车辆变速箱故障诊断结果表明,所提方法有效提高了故障诊断的精度,相比于其他几种方法效果更优。
fault diagnosis is greatly affected by parameters,a new method of vehicle gearbox fault diagnosis based on improved SVM is proposed based on the research of beetle antennae search(BAS). Compared with BAS,IBAS modified the step size formula and added Gaussian variation behavior,so that the search ability of the algorithm in the early and late period is balanced and has the ability to jump out of the local optimal,and better SVM parameters could be obtained. The results of gearbox fault diagnosis show that the proposed method can effectively improve the accuracy of fault diagnosis,and the results are better than those of other methods.
作者
乔文山
华晋
陈美宏
Qiao Wenshan;Hua Jin;Chen Meihong(College of Automotive Technology,Zhejiang Technical Institute of Economics,Hangzhou 310018,China;School of Mechatronics Engineering,Nanjing Forestry University,Nanjing 210037,China;Engineering Training Center,Nanjing Forestry University,Nanjing 210037,China)
出处
《机械传动》
北大核心
2022年第6期154-160,共7页
Journal of Mechanical Transmission
基金
江苏省国际合作资助项目(BZ2010060)
杭州亿校云信息技术有限公司横向课题(20231D274220009)。
关键词
天牛须搜索
支持向量机
变速箱
故障诊断
Beetle antennae search
Support vector machine
Gearbox
Fault diagnosis
