Rolling bearing weak fault diagnosis method based on PSO-VMD-MCKD

Abstract

The invention provides a rolling bearing weak fault diagnosis method based on PSO-VMD-MCKD, and the method comprises the steps: firstly optimizing a VMD algorithm through employing a PSO algorithm for a collected vibration signal, and selecting an optimal mode component based on a result obtained through the decomposition of a weak fault signal through VMD; secondly, according to a prominent frequency range in an envelope spectrum of the optimal modal component, determining an optimization range of T in an MCKD algorithm by PSO; the MCKD algorithm is optimized by using PSO, and then the fault impact component in the optimal component signal is enhanced based on the MCKD algorithm. And finally, extracting weak fault features of the bearing by the envelope spectrum, and comparing the weak fault features with the theoretical fault frequency to obtain a fault diagnosis result. According to the method, the problem that parameters are difficult to determine in the VMD and MCKD algorithms is solved, signal noise reduction is achieved through the VMD, the prominent fault frequency range is obtained, fault impact components are further enhanced through the MCKD, and weak fault diagnosis of the rolling bearing is more accurate.

Description

technical field [0001] The invention belongs to the field of rotating mechanical fault diagnosis, and in particular relates to a weak fault diagnosis method of a rolling bearing based on PSO-VMD-MCKD. Background technique [0002] Rolling bearing failure is one of the important factors affecting the normal operation of rotating machinery. Because the impact generated by the early failure of the bearing is very weak, it is easily disturbed by the system noise, and the vibration transmission path of the rolling bearing is complex, which makes the extraction of the fault characteristics very difficult. Therefore, how to effectively denoise the original fault signal of the rolling bearing and enhance the weak impact component in the signal is the key to the early fault diagnosis of such components. [0003] The fault signal of rolling bearing is a nonlinear and non-stationary signal. For this kind of signal, scholars have proposed a variety of processing methods. In recent yea...

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Problems solved by technology

[0004] Aiming at the problem that the early impact of rolling bearings is very weak, which is easily interfered by system noise, it is difficult to diagnose the weak faults of bearings, and the parameters of VMD algorithm and MCKD algorithm are difficult to determine; the invention proposes a method for diagnosing weak faults of rolling bearings based on PSO-VMD-MCKD

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