CAJ | 학술논문

针对滚动轴承故障，提出了基于相关原则优化阈值的小波去噪和最小二乘支持向量机相结合进行滚动轴承故障诊断的方法，采用相关原则优化阀值的小波对轴承早期故障特征进行提取，运用能量-特征法提取出信号特征，然后利用最小二乘支持向量机多分类算法进行故障类型的识别。实验与仿真结果表明：基于相关原则优化阈值的小波变换和最小二乘支持向量机相结合的故障诊断方法能有效地诊断出滚动轴承的典型故障。
침대곤동축승고장，제출료기우상관원칙우화역치적소파거조화최소이승지지향량궤상결합진행곤동축승고장진단적방법，채용상관원칙우화벌치적소파대축승조기고장특정진행제취，운용능량-특정법제취출신호특정，연후이용최소이승지지향량궤다분류산법진행고장류형적식별。실험여방진결과표명：기우상관원칙우화역치적소파변환화최소이승지지향량궤상결합적고장진단방법능유효지진단출곤동축승적전형고장。
Aimed at the fault of roller bearing,the method of fault diagnosis of roller bearings based on correlative principles of optimum threshold plus wavelet noise elimination and Least Squares Support Vector Machine (LS-SVM)in combination was presented. Correlative principles of optimum threshold plus wavelet transformation was applied to extract the feature of fault of roller bearings at early stage,energy feature method was used for signal extraction. And then,the recognition of fault types were carried out by using LS-SVM classified algorithm. Testing and simulation results show that the fault diagnosis method based on correlative principles of optimum threshold plus wavelet transformation and LS-SVM in combination can diagnose typical faults of the roller bearing effectively.