Gear Fault Diagnosis based on Feature Fusion and Sparse Representation - Wang Jiangping; Duan Tengfei (Jixie chuandong)
A kind of the mechanical fault diagnosis method based on feature fusion and sparse representation is proposed. The energy of every subband of gear vibration signal is extracted with wavelet packet decomposition,and the energy constitutes original feature vector. The feature fusion is implemented with KPCA,and the dimension reduction of original feature vector is used as the input of classification based on sparse representation. The experiment demonstrates that the different fault type of gear is detected by the presented method.