Research of Gear Fault Detection in Morphological Wavelet Domain

For extracting mutation information from gear fault signal and achieving a valid fault diagnosis, a gear fault diagnosis method based on morphological mean wavelet transform was designed. Morphological mean wavelet transform is a linear wavelet in the framework of morphological wavelet. Decomposing...

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Bibliographic Details
Published in:Journal of physics. Conference series 2016-02, Vol.679 (1), p.12035
Main Authors: Hong, Shi, Fang-jian, Shan, Bo, Cong, Wei, Qiu
Format: Article
Language:English
Subjects:
Fault detection
Fault diagnosis
Fourier transforms
Morphology
Mutation
Operators
Physics
Synthesis
Time-frequency analysis
Wavelet transforms
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Summary:For extracting mutation information from gear fault signal and achieving a valid fault diagnosis, a gear fault diagnosis method based on morphological mean wavelet transform was designed. Morphological mean wavelet transform is a linear wavelet in the framework of morphological wavelet. Decomposing gear fault signal by this morphological mean wavelet transform could produce signal synthesis operators and detailed synthesis operators. For signal synthesis operators, it was just close to orginal signal, and for detailed synthesis operators, it contained fault impact signal or interference signal and could be catched. The simulation experiment result indicates that, compared with Fourier transform, the morphological mean wavelet transform method can do time-frequency analysis for original signal, effectively catch impact signal appears position; and compared with traditional linear wavelet transform, it has simple structure, easy realization, signal local extremum sensitivity and high denoising ability, so it is more adapted to gear fault real-time detection.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/679/1/012035