基于支持向量机的滚动轴承故障诊断研究  

Fault Diagnosis of Rolling Bearings Based on Supporting Vector Machine

作　　者：左红[1] 顾家铭 于锦禄[3] 

机构地区：[1]空军驻上海地区军事代表室,上海200233 [2]上海天安轴承厂,上海200233 [3]空军工程大学工程学院,西安710038

出　　处：《轴承》2008年第8期36-39,共4页Bearing

摘　　要：在分析支持向量机多分类算法和滚动轴承故障诊断特征向量的基础上,建立了基于支持向量机的滚动轴承故障诊断模型,并对模型进行了鲁棒性研究。对建立的数学模型进行了试验验证,结果表明,建立的诊断模型对轴承故障诊断具有良好的诊断效果。A rolling bearings fault diagnosis method based on SVM was founded based on the analysis of SVM arithmetic and rolling bearing vibration signal＇s eigenveetor. The model＇s diagnosis performance was validated by experiment data and the robust of diagnosis model was also investigated. The experiment results show that the diagnosis model has excellent diagnosis effeteness.

关 键 词：滚动轴承 故障诊断 支持向量机 特征向量 鲁棒性 

分 类 号：TH133.33[机械工程—机械制造及自动化] TH165.3