Due to its special modulation mechanism with multiple units (eg. shafts, gears, etc.) under various conditions, the related fault information of gear fault would distribute in a broad frequency band. In this manner, it is not easy about accurately detecting the early-stage gear fault by detecting the fault frequency in a limited frequency band. In this paper, a new spectral analysis, called multiscale sparse spectrum (MSS), is proposed to achieve fault frequency detection in a sound way. The overall frequency information about the raw signal is firstly sensed by a series of frequency-window function, which can be reached by short-frequency Fourier transform. Then, according to orthogonal matching pursuit, harmonic atoms are further employed to sparsely mine the modulation components from these multiscale pseudo mono-components. Finally, MSS is proposed to synthesize the existing harmonic-related components. Furthermore, a synthesized sparse spectrum (SSS) is obtained by searching the frequency-frequency ridge from MSS. Compared with EMD and fast-kurtogram analysis, the results show the effectiveness of the proposed method of gear fault detection.

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