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《Control and Decision》 2007-09
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Method of signal singularity detection based on wavelet canceling noise and blind source separation

FENG Jian,ZHANG Hua-guang(a.College of Information Science and Engineering,b.Key Laboratory of Process Industry Automation of Ministry of Education,Northeastern University,Shenyang 110004,China.)  
Signal singularity detection in industrial process fault diagnosis is studied.The blind source separation algorithm combined with wavelet canceling noise is used to extract source signal.Based on the analysis of the relationship among Lipschitz exponent,wavelet transform maximum and signal singularity,the selection methods of scale and the threshold of wavelet are analyzed.The example shows that the method has better ability of noise canceling in comparing with other methods.It can also detect the characteristic singularity of the analyzed signal effectively.
【Fund】: 国家自然科学基金项目(60325311 60572070);; 中国博士后科学基金项目(20060400962);; 辽宁省自然科学基金项目;; 教育部流程工业综合自动化重点实验室基金项目(PAL200503)
【CateGory Index】: TP274
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