Method for diagnosing bearing fault

Abstract

The invention relates to a method for diagnosing a bearing fault, which comprises the following steps of: (1) acquiring a vibration acceleration signal of a bearing by using an acceleration transducer; (2) acquiring a form spectrum of the vibration acceleration signal by adopting a morphologic closing computation mode; (3) determining parameters of a morphologic structural unit according to the form spectrum in the step (2), and extracting a fault impact sequence; and (4) observing whether an obvious peak is present at a fault characteristic frequency on the form spectrum in the step (2), or observing whether the extracted impact sequence in the step (3) has obvious periodicity and corresponds to the corresponding fault characteristic frequency to judge whether a rotating machine has a fault. By the method, signals are not required to be filtered, and a window effect is avoided. The method is simple and has better adaptability, and the parameters are not needed to be determined in advance. Impact pulses generated due to the bearing fault can be directly extracted, other unrelated information is eliminated, and the method has obvious physical significance. The structure is simple, the computing speed is high, and real-time monitoring can be realized.

Description

technical field [0001] The invention relates to a mechanical state monitoring and fault diagnosis method, in particular to a diagnosis method for extracting the fault impact of a rolling bearing. Background technique [0002] Rolling bearings are key components of rotating machinery and also vulnerable parts. It is of great engineering significance to carry out condition monitoring and fault diagnosis on rolling bearings. When there is a defect in a rolling bearing, periodic shocks will occur when the damaged point comes into contact with other components. How to effectively extract impact features from vibration acceleration signals is a key issue for judging the location of rolling bearing defects and the degree of damage. Traditional rolling bearing fault diagnosis methods include spectrum analysis, envelope demodulation, and time-frequency analysis. However, spectrum analysis needs to use more orthogonal simple harmonic trigonometric functions to approximate the impac...

AI Technical Summary

Problems solved by technology

However, the envelope demodulation must first perform band-pass filtering or high-pass filtering on the vibration signal. If the filter parameters are not selected properly, the extraction of shock features may fail.

Time-frequency analysis, such as wavelet and Wegener distribution, etc., are fault diagnosis methods with relatively high accuracy. Difficult in engineering practice

Images