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Published in:
2015 | OriginalPaper | Chapter
A Bearing Fault Detection Method Base on Compressed Sensing
Authors : Zhang Xinpeng, Hu Niaoqing, Cheng Zhe
Published in: Engineering Asset Management - Systems, Professional Practices and Certification
Publisher: Springer International Publishing
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Abstract
For bearing fault detection in frequency domain, traditional methods estimate bearing fault condition based on mass data sampled by Nyquist sampling theorem, which will burden the storage. A new bearing fault detection method based on compressed sensing will be proposed in this paper in allusion to the problem mentioned above. The method presented here carried out compressive sampling and get a small set of incoherent projections, often the number of projections can be much smaller than the number of Nyquist rate samples. Then based on matching pursuit, the bearing condition will be estimated finally using these few measurements directly without ever reconstructing the signals involved. Sparsity of original signal is not demanded since the signal does not need to be recovered completely, which will also helped to expanded the method to other signals with similar characteristics in frequency domain. Related test will be achieved to verify the effectiveness of the method proposed in this paper.