Tool condition monitoring based on fractal and wavelet analysis by acoustic emission

Authors:
Wanqing Song;Jianguo Yang;Chen Qiang
Affiliations:
College of Mechanical Engineering, Donghua University, Shanghai, P.R. China;College of Mechanical Engineering, Donghua University, Shanghai, P.R. China;Computer Center, Shanghai University of Engineering and Science, shanghai, China
Venue:
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Year:
2007

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Abstract

In this article, a technique based on the acoustic emission (AE) signal fractal and wavelet analysis are proposed for tool condition monitoring. it is difficult to obtain an effective result by these raw acoustic emission data. The local characterize of frequency band, which contains the main energy of AE signals, is depicted by the wavelet multi-resolution analysis, fractal dimension can describe the complexity of time series. It is found that the fault signal can effectively be extracted by wavelet transform and fractal dimension. Experimental results prove that this method is effectively.