Rolling bearing fault diagnosis method based on variational Hilbert-Huang transform

Abstract

The invention discloses a rolling bearing fault diagnosis method based on variational Hilbert-Huang transform, and the method comprises the following steps: S1, carrying out processing of measurementdata of a rolling bearing through empirical mode decomposition to obtain a plurality of intrinsic mode functions IMFi; S2, screening the obtained IMFi by using a sensitivity criterion to obtain a sensitive mode containing rolling bearing fault information; S3, constructing each sensitive mode into a variational model taking the minimum sum of bandwidths as a target, and solving the variational model to obtain a plurality of finite bandwidth modes; S4, according to the signal characteristics, reconstructing the finite bandwidth modes according to a specified sequence to obtain rolling bearing fault components; S5, using Hilbert-Huang transform for detecting fault components, comparing the fault components with the theoretical fault characteristic frequency, and determining the fault position of the rolling bearing. Rolling bearing data are processed through variational Hilbert-Huang transform, and the effect of rolling bearing noise suppression is achieved.

Description

technical field [0001] The invention belongs to the field of bearing fault diagnosis and state recognition, and in particular relates to a rolling bearing fault diagnosis method based on variational Hilbert-Huang transformation. Background technique [0002] In the condition monitoring of rolling bearings, due to human factors and environmental factors, the monitoring signals often contain a lot of noise. The noise removal methods commonly used in the industry all have problems such as unclean noise removal and loss of effective signals to a certain extent. It will lead to low signal-to-noise ratio in the early faults, and the fault features are difficult to extract due to the noise cover. Hilbert-Huang transform is a commonly used and effective method for rolling bearing fault diagnosis, but because it is based on empirical mode decomposition, the modal aliasing and redundant modal problems will greatly affect the early fault diagnosis of rolling bearings. . Therefore, it...

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Problems solved by technology

[0003] The purpose of the present invention is to propose a rolling bearing fault diagnosis method based on variational Hilbert-Huang transform, through which the existing rolling bearing fault diagnosis method can make up for the The problem of insufficient accuracy of early fault detection provides a more effective and fast fault diagnosis method

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