The transient impact components in vibration signal, which are the major information for\nbearing fault severity recognition, are often interfered with by ambient noise. Meanwhile, for bearing\nfault severity recognition, the frequency band selection methods which are employed to pre-process\nthe contaminated vibration signal only select the partial frequency band of the vibration signal and\ncause information loss of other frequency band. Aiming at this issue, this paper proposes a novel fault\nseverity recognition method based on Huffman coding, which can retain all the information of the\nfrequency band, and is applied for the first time to bearing fault severity recognition. Specifically, the\naverage coding length of Huffman coding (ACLHC) of the original vibration signal is first calculated\nto reduce the noise and highlight the impact components of the signal. Then, the ACLHC is encoded\nby symbolic aggregate approximation (SAX) to reflect the modulation information of bearing. Finally,\nthe Lempel-Ziv indicator (LZ indicator) of the symbol sequence is calculated to reflect the fault\nseverity. The proposed method is verified by the bearing datasets under different working conditions.\nCompared with the methods based on frequency band selection, the proposed method effectively\nrecognizes the fault severity of bearing for more working conditions.
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