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《Transducer and Microsystem Technologies》 2006-06
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Acoustic emission cutting tool state distinguishing based on wavelet analysis

CHEN Xiao-zhi,LI Bei-zhi,YANG Jian-guo(College of Mechanical Engineering,Donghua University,Shanghai 200051,China)  
A method based on wavelet analysis of acoustic emission(AE) cutting tool state distinguishes and analysis is presented.The local characterize of the frequency band which contains the signal main energy is depicted by the multiplayer wavelet decomposition,and the strangeness of signal is represented by wavelet decomposition coefficient 2—norm.The physical relationship between the statistic and tool state is built up.Its validity is proved by the turning experiments.The nethod can preferably distinguish tool state,and it has a preferable theory foundation and maneuverability.
【Fund】: 上海市自然科学基金资助项目(02ZF14003)
【CateGory Index】: TG71
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