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| Single-channel blind source separation based on EMD and CICA and its application to gearbox multi-fault diagnosis |
| HAO Rujiang， AN Xuejun， SHI Yunlin |
| School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China |
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Abstract Considering that the traditional independent component analysis is too difficult to solve the problems of underdetermined blind source separation (BSS) in gearbox multi-fault diagnosis, a single-channel blind source separation method based on empirical mode decomposition (EMD) and constrained independent component analysis (CICA) was proposed.Gearbox multi-fault signal was collected by a single-channel acceleration sensor, and it was decomposed by the EMD method to achieve noise reduction and single channel expansion.By virtue of the characteristics of white noise and kurtosis value, the effective IMF components were selected, which was treated as input signals for the BBS.The target vibration signal was extracted by the CICA method to identify the fault feature.A case study on gearbox bearing and gear multi-fault simulations and experiments verifies the effectiveness and feasibility of the proposed method.
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Received: 19 July 2017
Published: 15 April 2019
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