Feature Extraction of Gear Fault Signal Based on Sobel Operator and WHT | Zendy

Jianhua Cai | Zendy; Weiwen Hu | Zendy

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Feature Extraction of Gear Fault Signal Based on Sobel Operator and WHT

Author(s) -

Jianhua Cai,

Weiwen Hu

Publication year - 2013

Publication title -

shock and vibration

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.418

H-Index - 45

eISSN - 1875-9203

pISSN - 1070-9622

DOI - 10.1155/2013/367045

Subject(s) - sobel operator , hough transform , signal (programming language) , artificial intelligence , noise (video) , wigner distribution function , feature extraction , feature (linguistics) , pattern recognition (psychology) , fault (geology) , computer vision , computer science , algorithm , operator (biology) , mathematics , edge detection , image processing , image (mathematics) , physics , linguistics , philosophy , biochemistry , chemistry , repressor , quantum mechanics , seismology , geology , transcription factor , quantum , gene , programming language

Taking Wigner-Ville distribution of gear fault signal as a picture, Sobel operator was applied for edge detection of picture and then Hough transform was used to extract signal feature. Some simulated and measured signals have been processed to demonstrate the effectiveness of new method, which was compared with traditional Wigner-Hough transform and SPWD-Hough transform. The results show that the proposed method can suppress cross term which is produced from using Wigner-Ville distribution to analyze multi-component signal, especially under the condition of low signal to noise ratio. The improved Wigner-Hough transform can effectively suppress the influence of noise and has a good real-time performance because its algorithm is fast. The proposed method provides an effective method to determine the state of gear accurately.

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