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《Journal of the China Railway Society》 2007-01
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Fault Diagnosis of I.C. Engines Based on Optimal Recursive Wavelets and Improved ART2 Network

ZHU Yun-fang ~(1),DAI Chao-hua ~(2),CHEN Wei-rong~(2)(1.Department of Computer & Communication Eng.,Southwest Jiaotong Univesity E'mei Campus,E'mei 614202,China;2.Institute of Electrification & Automation,Southwest Jiaotong Univesity,Chengdu 610031,China)  
The angular vibration of the crankshaft is viewed as an important tool of fault diagnosis of I.C.engines.For overcoming the shortcomings of the longer data window and poor real-time characteristics in conventional wavelet transforms,a general method of recursive mother wavelets is introduced.Recursive wavelet transforms are not restricted by the data window,and can extract the transient information in real-time.Moreover,the steps to optimize its time-frequency performance are proposed.Besides,the angular vibration signals of crankshafts of I.C.engines are decomposed using recursive wavelets and the features are extracted.In view of the fact that the traditional ART2 network loses the amplitude information of input patterns and is sensitive to the sequence of input patterns,an improved ART2 is presented by introducing average filtering and relational functions into weight adjustment.The modified ART2 has higher convergent speed,is more robust,and more insensitive to the pattern sequence.Finally,it is used in fault recognition of I.C.engines.The results show that recursive wavelets are practical in analyzing I.C.engine condition signals.The time consumed by the modified ART2 accounts only for less than 3% of that by the traditional ART2,and the recognition rate of the improved ART2 is up to 100%.
【CateGory Index】: TP277
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