Abstract
This paper describes an application of the Discrete Wavelet Transform (DWT) to detecting tool failures in face milling operations. The wavelet transform uses an analyzing wavelet function which is localized in both frequency and time to detect subtle time localized small changes in the input signals. In this paper, the DWT is used to detect tool failures such as small chipping and breakage of an insert tip including eccentricity of the tool rotation center. The results indicate that the DWT can extract tool failures with much greater sensitivity than the FFT even when the amount of chipping is very small. In addition, the DWT enables the analyst to determine which insert tip failed, since it yields time localized signal information. On-line diagnosis of tool failures are demonstrated in both simulated and actual cutting force signals by using simple pattern recognition technique.
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