Title :
Research of fault diagnosis based on matching pursuit and biomimetic pattern recognition
Author :
Wang Xiaozhe ; Wang Jinping
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
Consider of influences of noise in sampling signals comprehensively, a method of fault diagnosis which combines matching pursuit (MP) and biomimetic pattern recognition (BPR) is put forward in this paper. Firstly, the matching pursuit (MP) algorithm is used to select optimum wavelets in different SNR situations from the Laplace wavelet dictionary. Then the feature vector is extracted according to the operation result of waveform MP and super high dimensional detection feature spaces of biomimetic pattern recognition (BPR) are constructed. After that, the real-time detected partial discharge (PD) signals are cut, and the feature for each discharge pulse is extracted respectively, which realized the multiple fault recognition revolutionarily. Simulations show that the robustness and accuracy of fault pattern recognition is improved.
Keywords :
Laplace transforms; biomimetics; fault diagnosis; feature extraction; gas insulated switchgear; partial discharges; signal detection; signal sampling; wavelet transforms; BPR; Laplace wavelet dictionary; PD signals; biomimetic pattern recognition; discharge pulse; fault diagnosis; fault pattern recognition; feature vector extraction; high dimensional detection feature spaces; matching pursuit algorithm; multiple fault recognition; optimum wavelets; real-time detected partial discharge signals; sampling signals; waveform MP; Business process re-engineering; Fault diagnosis; Feature extraction; Gas insulation; Matching pursuit algorithms; Partial discharges; Vectors; GIS; SNR; biomimetic pattern recognition; partial discharge; waveform match pursuit;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
DOI :
10.1109/WCICA.2012.6359396