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Acoustic emission method for tool condition monitoring based on wavelet analysis

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Abstract

It is believed that the acoustic emission (AE) signals contain potentially valuable information for tool wear and breakage monitoring and detection. However, AE stress waves produced in the cutting zone are distorted by the transmission path and the measurement systems and it is difficult to obtain an effective result by these raw acoustic emission data. In this article, a technique based on AE signal wavelet analysis is proposed for tool condition monitoring. The local characterize of frequency band, which contains the main energy of AE signals, is depicted by the wavelet multi-resolution analysis, and the singularity of the signal is represented by wavelet resolution coefficient norm. The feasibility for tool condition monitoring is demonstrated by the various cutting conditions in turning experiments.

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Acknowledgement

The work described in this paper was fully supported by the Natural Science Foundation of Shanghai, P. R. China (Project No. 02ZF14003).

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  1. College of Mechanical Engineering, Donghua University, 1882# west Yan’an Road, Shanghai, 200051, People’s Republic of China

    Xiaozhi Chen & Beizhi Li

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  1. Xiaozhi Chen
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  2. Beizhi Li
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Correspondence to Xiaozhi Chen.

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Chen, X., Li, B. Acoustic emission method for tool condition monitoring based on wavelet analysis. Int J Adv Manuf Technol 33, 968–976 (2007). https://doi.org/10.1007/s00170-006-0523-5

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  • DOI: https://doi.org/10.1007/s00170-006-0523-5

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