Abstract：Aiming at the problem that the early weak fault features of harbor crane bearings are easily submerged by strong noise, an algorithm based on generalized likelihood ratio (GLR) and variational modal decomposition (VMD) is proposed by combining the advantages of GLR and VMD. A fault index ratio of fault frequency (RFF) based on envelope spectrum is proposed according to the above algorithm because the traditional envelope spectrum detection and fault identification depends on professional knowledge. The proposed method is validated by simulation experiment signals and real data, and compared with other VMD optimization methods. The results show that the proposed algorithm can accurately extract the fault features of rolling bearings under high noise and strong interference signals, and the proposed fault index RFF can realize weak fault diagnosis.
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