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Method of Fault Detection Based on ANFIS Nonlinear Observer Using Continu ous Wavelet Transform

FENG Jian, ZHANG Hua-guang, LUN Shu-xian, WANG Zhan-shan(School of Information Science & Engineering, Northeastern University, Sh enyang 110004, China. Correspondent: FENG Jian, E-mail: fjneu?@?163.com)  
A novel method of fault detection was proposed based on ANFIS nonlinear observer using continuous wavelet transform. This method is a combination of signal anal ysis and mathematical model. By the denoising function of wavelet transform and the offline learning function of ANFIS, the input and output nonlinear dynamic c haracteristic of system was obtained. The series of output prediction error, gen erated from the real output and ANFIS observer estimated output, was calculated in real time and transformed by Mexican Hat wavelet as a residual error to execu te logical judge of its extrema and detect occurrence of defaults exactly. This method has good sharpness of response to faults and robustness to noise. Key words:?ANFIS; nonlinear observer; wavelet transform; fault detection; residual error; l ogical judge
【Fund】: 国家自然科学基金资助项目(60274017);; 教育部博士学科点专项科研基金资助项目(9914518);; 沈阳市自然科学基金资助项目(1022033 01 07)
【CateGory Index】: TP277
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