結合經驗模態分解與振動模態分析於軸承振動之損壞診斷

Combining the Empirical Mode Decomposition with the Vibration Mode Analysis in the Defect Diagnosis of Bearing Vibrations

在本文中，將利用經驗模態分解法(empirical mode decomposition)濾除軸承振動訊號之高頻共振模態，再以振動模態分析法(vibration mode analysis)估測其殘餘訊號，可獲致軸承振動之低頻模態包絡訊號，最後其包絡頻譜可用以診斷軸承損壞。首先，針對經驗模態分解法採用四次多項式函數來估測極值包絡線，以獲致包含兩個高頻模態之第一條固有模態函數(intrinsic mode function)；其次，再針對濾除第一條固有模態函數後之殘餘訊號，進行振動模態分析以估測軸承振動之兩低頻模態的包絡訊號；最後，可利用兩低頻模態之包絡頻譜診斷軸承之運作狀態。經由模擬與實驗分析證實，此結合經驗模態分解與振動模態分析之演算法，可有效地運用於軸承振動之損壞診斷。

In this paper, a signal processing method of combining the empirical mode decomposition with the vibration mode analysis is proposed. The empirical mode decomposition is applied to filter out the high-frequency modes of a bearing vibration, then, the residue signal is analyzed by the vibration mode analysis to derive the envelope signals of the bearing vibration in the low-frequency modes. Accordingly, the envelope spectra are applied in the defect diagnosis of the bearing vibration. First, in the empirical mode decomposition a fourth order polynomial function is applied to estimating envelopes for the extreme locations of the bearing vibration, and to deriving the first intrinsic mode function which would contain two high-frequency modes. Secondly, the vibration mode analysis is applied to estimating two envelope signals of the low-frequency modes for the residual signal which is derived from the bearing vibration with filtering out the first intrinsic mode function. Finally, by estimating the vibration spectra for the envelope signals the running condition of the bearing could be diagnosed. From the simulated and empirical studies, the algorithm of combining the empirical mode decomposition with the vibration mode analysis is proved to be effective in the defect diagnosis of bearing vibrations.