摘要
研究小波奇异谱在轴承故障诊断中的应用问题,针对小波奇异谱熵无法有效实现故障诊断的不足,提出以最大小波奇异谱为特征的轴承故障诊断方法。该方法利用小波变换后的系数矩阵的最大奇异值作为故障诊断特征,并将试验结果与以小波奇异谱熵为特征的方法进行比较。结果表明,该方法在识别性能上有显著提高。试验从小波基、窗口宽度两个层面对该方法的诊断性能进行了分析,证明该方法具有较强的稳定性和鲁棒性。
To solve the problem that the wavelet singular spectrum entropy can not effectively discriminate the signals of inner and balling faults,this paper attempts to diagnose bearing faults by using the maximum wavelet singular spectrum of the bearing vibration signals.The maximum singular value of the wavelet matrix resulting from the multi-resolution analysis of the bearing vibration signal was used as the classification feature.A bearing fault diagnosis experiment was conducted and its results were compared with that of the wavelet singular-spectrum-entropy method.The effects of the wavelet base selection,window width on the proposed method were analyzed.The results show that the method is highly capable of bearing fault diagnosis and has better performances of stability and robustness.
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2010年第1期78-82,99,共5页
Journal of Vibration,Measurement & Diagnosis
关键词
故障诊断
小波变换
奇异谱
奇异谱熵
fault diagnosis wavelet transform singular spectrum singular spectrum entropy
