Bearing fault diagnosis method under strong noise variable speed condition based on energy weight method

Abstract

The invention relates to a bearing fault diagnosis method under a strong noise variable speed condition based on an energy weight method. The method comprises the steps: extracting a vibration signalorder through employing a time-frequency ridge feature point linear interpolation and masking algorithm method according to a time-frequency representation graph based on Gabor transformation; performing instantaneous frequency estimation and secondary fitting on the vibration signal by using a local extremum search algorithm and the extracted order; carrying out equal-angle resampling on the vibration signal by utilizing a key phase time scale method according to the fitted instantaneous frequency; performing Hilbert-Huang transformation of CEEMDAN on the resampled isometric domain signal toobtain an order-frequency spectrum of the signal; extracting an impact energy occurrence position in the order-frequency spectrum, and then carrying out binaryzation on the order-frequency spectrum; acquiring an energy weight order sequence capable of reflecting impacts through multi-scale binary spectrum analysis, and carrying out power spectrum analysis on the energy weight order sequence to obtain fault-related impact components. The influence of strong noise and variable rotating speed on vibration signal analysis can be eliminated, and the accuracy of rolling bearing fault diagnosis is improved.

Description

technical field [0001] The invention belongs to the technical field of fault detection, and in particular relates to a bearing fault diagnosis method under the condition of strong noise and variable speed based on an energy weight method. Background technique [0002] With the proposal of "Manufacturing 2025", more and more attention has been paid to industrial production. Rolling bearings are important components of common equipment in industrial production, and their health status is related to production efficiency, operating costs, and production safety. With the diversification, complexity and enlargement of modern industrial equipment, the application occasions of rolling bearings are becoming more and more extensive. [0003] The actual use scene of rolling bearings is often in a complex environment, and there is relatively complex vibration interference between rolling bearings or between different components of the bearing itself. Therefore, the collected vibration...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a bearing fault diagnosis method under the condition of strong noise and variable speed based on the energy weight method, which solves the problem that the vibration signal of the rolling bearing often shows non-stationary characteristics under the condition of high noise and variable speed operation, which makes the traditional The fault diagnosis method is difficult to achieve accurate judgment of the fault state under the condition of variable speed

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