变转速变载荷下滚动轴承故障的小波-HMM诊断

常规的谱分析等方法难以对滚动轴承变转速变载荷工况进行故障诊断，为此，采用具有时频局域特征的小波分析法。对变转速变载荷工况下滚动轴承的振动信号。用小波包分解法提取各频带的能量作为特征参数。再采用连续隐Markov模型（HMM）对滚动轴承的状态进行识别。试验证明，小波-HMM可以在变转速变载荷工况下以及未知转速情况下对滚动轴承的各种故障有效地进行诊断。

Wavelet-HMM Fault Diagnosis for Rolling Bearing with Variable Speeds and Loads

It is difficult to make the failure diagnosis with spectrum analysis methods in the condition of variable speed and load;the wavelet method of the time-frequency domain characters is adopted.The wavelet envelope decomposition method is adopted to extract energy in different frequency range as character parameters,in turn,continuous hidden Markov model(HMM) is adopted to identify the status of the rolling bearing.The experiment shows that the HMM wavelet can make the effective diagnosis for various faults of rolling bearings operating under the condition of variable speed and load or unknown speed.