中国机械工程2017，Vol.28Issue(7)：823-829,7.DOI:10.3969/j.issn.1004-132X.2017.07.011
基于假设检验和支持向量机的旋转机械故障诊断方法
Fault Diagnosis Method Based on Hypothesis Testing and SVM for Condition Diagnosis of Rotating Machinery
摘要
Abstract
A fault diagnosis method was proposed based on adaptive statistic test filter (STF) and SVM for condition diagnosis of rotating machinery to extract weak fault features and identify fault types.STF was based on the statistic of the hypothesis testing in the frequency domain to evaluate similarity among reference signals (noise signal) and original signals,and remove the components of high similarity.The optimal level of significance a was obtained by using particle swarm optimization(PSO).To evaluate the performances of the STF,evaluation factor IpqWaS also defined.Finally,a sequential diagnosis method,using sequential inference and SVM was also proposed,by which the conditions of rolling bearings might be identified sequentially.Practical examples of fault diagnosis for structural faults often occurring in the shafts,such as unbalance,misalignment states were shown to verify that the method is effective.关键词
特征提取/假设检验/显著性水平/支持向量机Key words
feature extraction/hypothesis testing/level of significance/support vector machine(SVM)分类
机械制造引用本文复制引用
赵宇,李可,宿磊,陈鹏..基于假设检验和支持向量机的旋转机械故障诊断方法[J].中国机械工程,2017,28(7):823-829,7.基金项目
国家科技支撑计划资助项目(2015BAF16B02) （2015BAF16B02）
