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Ling Zhao, Xin Chi, Pan Li and Jiawei Ding
A rolling bearing vibration signal fault feature enhancement method based on adaptive complete ensemble empirical mode decomposition with adaptive noise algorithm (CEEMDAN) and maximum correlated kurtosis deconvolution (MCKD) is proposed to address the i...
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Lingli Cui, Jianxi Du, Na Yang, Yonggang Xu and Liuyang Song
Vibration analysis is one of the main effective ways for rolling bearing fault diagnosis, and a challenge is how to accurately separate the inner and outer race fault features from noisy compound faults signals. Therefore, a novel compound fault separati...
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Zheng Li, Anbo Ming, Wei Zhang, Tao Liu, Fulei Chu and Yin Li
In order to extract and enhance the weak fault feature of rolling element bearings in strong noise conditions, the Empirical Wavelet Transform (EWT) is improved and a novel fault feature extraction and enhancement method is proposed by combining the Maxi...
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