Though the Discrete Wavelet Transform (DWT) has gained attention in the field of machining monitoring, the potential use of DWT-based classification techniques has not yet been fully explored. In this paper, linear discriminant analysis is used to post-process DWT output for on-line prediction of small drill bit breakage. Bit failure is characterized by two types of transients ("sawtooth" and "screeching") in the cutting force signal. To detect these transients, instead of traditional Fourier based methods the DWT is used, which is better suited to analysis of time-localized phenomena. Three index functions ("energy", "waviness" and "irregularity") are adopted to test for the presence of transients in the DWT expansion. The indices are used to perform linear discriminant analysis, thereby classifying the input signals by state (normal or prefailure). Experiments showed that the DWT-based linear discriminant analysis method can accurately identify impending breakage about 1-3 cycles prior to failure even when the cutting conditions change.
Key words: drill, breakage, prediction, Wavelet Transform, discriminant analysis, in-process monitoring