CAJ | 학술논문

结合谐波小波包和相关向量机设计了滚动轴承故障诊断方法，以实现轴承正常状态、内圈故障、滚动体故障及外圈故障状态的诊断。首先，利用谐波小波包对轴承的振动信号进行多层分解，根据各频段的小波分解系数计算各个频带能量，归一化之得到特征向量；其次，对传统的OAO－RVM模型进行简化，改进为新的OAO－RVM多模式分类模型；最后，利用滚动轴承试验台的振动数据对设计方法进行了验证。结果表明，设计的诊断方法在识别的准确率及算法计算效率方面均比传统的支持向量机诊断方法好。
결합해파소파포화상관향량궤설계료곤동축승고장진단방법，이실현축승정상상태、내권고장、곤동체고장급외권고장상태적진단。수선，이용해파소파포대축승적진동신호진행다층분해，근거각빈단적소파분해계수계산각개빈대능량，귀일화지득도특정향량；기차，대전통적OAO－RVM모형진행간화，개진위신적OAO－RVM다모식분류모형；최후，이용곤동축승시험태적진동수거대설계방법진행료험증。결과표명，설계적진단방법재식별적준학솔급산법계산효솔방면균비전통적지지향량궤진단방법호。
A fault diagnosis method for rolling bearings is designed based on harmonic wavelet package and Relevance Vector Machine (RVM),the diagnosis are realized for normal state,inner ring fault,rolling element fault and outer ring fault of bearings.Firstly,the multiple-level decomposition for vibration signals of bearings is carried out by using harmonic wavelet package.The energy in various frequency bands is computed according to wavelet decomposition coef-ficients for every frequency band,and the feature vector is obtained after normalization.Secondly,the traditional OAO-RVM model is simplified and improved to new OAO-RVM multi-mode classification model.Finally,the design method is verified by using vibration data from test rig for rolling bearings.The results show that the identification accu-racy and algorithm computational efficiency of designed diagnosis method are better than those of traditional support vec-tor machine diagnosis method.