Bearing fault diagnosis method based on ITD and improved morphological filtering

Abstract

The invention discloses a bearing fault diagnosis method based on ITD and improved morphological filtering, which is a bearing fault diagnosis method based on intrinsic time scale decomposition (ITD)and improved morphological filtering, and belongs to the field of mechanical fault diagnosis. The method includes the following steps: firstly, a bearing vibration signal is subjected to ITD to obtaina series of rotation components (Proper rotation, PR), the effective PR with rich fault information is screened out based on the criterion of kurtosis, and each effective component is subjected to improved morphological filtering-ACDIF to extract the impact component and then reconstruct the signal, and finally, spectrum analysis is used to extract fault features in the reconstructed signal. Themethod utilizes the advantages of the adaptive decomposition capability for the signal of the ITD method and the effective filtering and retaining of impact components of the ACDIF, thereby improvingthe accuracy of the filtering output. An ACDIF filter not only has a simple structure design but also can be applied to the fault diagnosis of vibration signals, and the signal impact characteristicsafter filtering with the method are completely preserved.

Description

technical field [0001] The invention belongs to the field of fault diagnosis of mechanical equipment, and relates to a method based on ITD and improved morphological filtering bearing Troubleshooting method . Background technique [0002] The condition monitoring and fault diagnosis of rolling bearings generally take the collected vibration signal as the analysis object, and the fault characteristics are obtained through signal analysis to realize the diagnosis. Due to the nonlinear vibration caused by the instability of the bearing working condition and the damage of the parts, most of the collected signals show nonlinear and non-stationary characteristics; at the same time, they are inevitably affected by various noises and signal modulation interference. Therefore, how to effectively suppress interference such as noise and extract fault features from complex vibration signals has become the key to fault detection. [0003] Time-frequency analysis is a common method fo...

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Problems solved by technology

[0006] The purpose of the present invention is to provide a bearing fault diagnosis method based on ITD and improved morphological filtering, aiming at the shortcomings of the single ITD decomposition noise reduction method and fault feature extraction technology in the prior art, and the fault signal is interfered by harmonics and random noise Severe characteristics and basic theory of morphology, improved vibration signal noise reduction and feature extraction technology, effectively filter harmonic interference, extract impact fault features under strong background noise, and realize equipment fault diagnosis

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