机械科学与技术2024，Vol.43Issue(5)：832-836,5.DOI:10.13433/j.cnki.1003-8728.20220292
数控机床电动主轴WPD-TSNE-SVM模型故障诊断
Fault Diagnosis of CNC Machine Tool Electric Spindle with WPD-TSNE-SVM Model
摘要
Abstract
In order to improve the fault diagnosis efficiency of motorized spindle of NC machine tool,a WPD-TSNE-SVM combined model was designed.The main shaft vibration signal is decomposed by using the wavelet packet method,and the dimensionality reduction process of sample set TSNE is completed,and the fault classification of reconstructed features is completed via SVM.The mixed feature space vector of NC machine tool spindle signal was constructed,and the fault diagnosis was analyzed.The results show that the training sample data of TSNE method form regular distribution characteristics,and nonlinear SVM multi-fault classifier is used to achieve the accurate fault classification of wavelet packet mixed features.The nonlinear SVM diagnosis method based on the radial basis kernel function can achieve the higher accuracy.This method can diagnose the running faults of bearings,obtain higher maintenance efficiency,and ensure the running stability of CNC machine tool spindle.关键词
数控机床/电动主轴/故障诊断/小波包分解Key words
CNC machine tool/electric spindle/fault diagnosis/wavelet packet decomposition分类
机械制造引用本文复制引用
李坤宏,江桂云,朱代兵..数控机床电动主轴WPD-TSNE-SVM模型故障诊断[J].机械科学与技术,2024,43(5):832-836,5.基金项目
重庆市科技计划(应用开发重大)(cstc2015yykfC40001) （应用开发重大）
