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Intelligent Tool Condition Monitoring Based on Recursive Wavelet and ART2 Network

ZHU Yunfang1,DAI Chaohua2,CHEN Weirong2(1.Department of Computer & Communication Eng.,E'mei Branch,Southwest Jiaotong University,E'mei Sichuan 614202,China;2.Institute of Electrification & Automation,Southwest Jiaotong University,Chengdu Sichuan 610031,China)  
Real-time tool condition monitoring plays a very important role in the unmanned machining environment.Based on the SuperGaussian function,a general method of recursive mother wavelet was introduced, and an optimal method of wavelet construction was proposed.The time-frequency characteristics of recursive wavelet were analyzed.The AE signals of tool conditions were decomposed using a recursive wavelet from which the features are extracted and delivered to an ART2 network for fault recognition.The results show that recursive wavelet and ART2 network based tool condition monitoring is robust and real time.
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