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Application of constrained independent component analysis and empirical mode decomposition to diagnose synchronous multiple bearing faults
Constrained independent component analysis
Empirical mode decomposition
Concurrent multiple bearing fault
Support vector machine
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This study investigates the diagnosis of multiple faults that occur concurrently in the bearing through empirical mode decomposition and constrained independent component analysis. The vibration measurements are first decomposed into several intrinsic modal functions through the empirical mode decomposition method. The intrinsic mode functions that present obvious amplitude modulation phenomenon are selected to synthesize a new signal. The constrained independent component analysis is employed to extract the signal component which is highly correlated to the bearing fault features. The fast Fourier transform is utilized to obtain the frequency-domain features of the faulted signal, and the extracted features are compared with the one derived from the theoretical characteristics. The time-domain and frequency-domain characteristics of this independent component are quantified for the intelligent diagnosis through the support vector machine classifier.
|Appears in Collections:||機械工程學系所|
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