基于路径重积分特征提取的轴承故障诊断  

Feature Extraction of Time Series Signal Path Signature and Its Application in Fault Diagnosis

作　　者：张浩然 马萍[1] 张宏立[1] 王聪[1] 李新凯 ZHANG Haoran;MA Ping;ZHANG Hongli;WANG Cong;LI Xinkai(School of Electrical Engineering,Xinjiang University,Urumqi 830017,China)

机构地区：[1]新疆大学电气工程学院,乌鲁木齐830017

出　　处：《组合机床与自动化加工技术》2024年第8期134-138,144,共6页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金资助项目(52065064,52267010);新疆维吾尔自治区自然科学基金资助项目(2022D01E33,2022D01C367)。

摘　　要：滚动轴承振动信号呈现非线性和非平稳特征,为充分挖掘滚动轴承振动信号的有效信息,提高故障诊断准确率,提出基于振动信号路径重积分(path signature, PS)的滚动轴承故障信号特征提取方法。首先,对一维故障振动信号进行时延重构,构成有限维路径空间;其次,对路径进行多重迭代积分得到高阶路径积分特征作为故障振动信号初始特征,利用主成分分析(principal component analysis, PCA)对其进行降维得到能充分表征故障信号本征信息的特征;最后,将不同故障信号基于路径重积分的故障特征构成故障特征集,输入到支持向量机(support vector machine, SVM)完成故障的识别和分类。实验结果表明,该方法在公开数据集上的10种故障类型诊断准确率达99.33%,对比其他几种方法,所提方法能快速准确地识别滚动轴承不同故障类型。The vibration signal of rolling bearing presents nonlinear and non-stationary characteristics.In order to fully exploit the effective information of the vibration signal of rolling bearings and improve the accuracy of fault diagnosis,a feature extraction method of rolling bearing fault signal based on path signature(PS)of vibration signal is proposed.Firstly,the one-dimensional fault vibration signal is delayed reconstructed to form a finite-dimensional path space.Secondly,the high-order path integral feature is obtained by multiple iterative integration of the path as the initial feature of the fault vibration signal,and the principal component analysis(PCA)is used to reduce the dimension to obtain the feature that can fully characterize the intrinsic information of the fault signal.Finally,the fault features of different fault signals based on path signature constitute the fault feature set,which is input into the support vector machine(SVM)to complete the fault identification and classification.The analysis results show that the accuracy of this method in diagnosing 10 types of faults on public datasets in 99.33%.Compared with other methods,the proposed method can quickly and accurately identify different fault types of rolling bearings.

关 键 词：路径空间 路径重积分 截断阶数 特征提取 故障诊断 

分 类 号：TH133.3[机械工程—机械制造及自动化] TG66[金属学及工艺—金属切削加工及机床]