Rolling bearing fault voiceprint recognition method based on power regularization cepstrum coefficient

The invention discloses a rolling bearing fault voiceprint recognition method based on a power regularization cepstrum coefficient, relates to the technical field of measurement, and solves the technical problem of low bearing fault recognition accuracy under noise interference. The key point of the technical scheme is that the fault sound signal of the rolling bearing is identified by using the improved power regularization cepstrum coefficient feature, and compared with other common features, the calculated amount is only slightly increased, but the identification accuracy is higher; meanwhile, the improvement measure can still keep higher recognition accuracy in a noise environment, and has the advantage of high robustness. Normal operation of the rolling bearing is not affected, the sound signal sensor can be installed on the premise that the rolling bearing is not stopped and an original system is not transformed, fault recognition of the rolling bearing is achieved on the basis, and efficiency is higher