The principle of second generation wavelet for milling cutter breakage detection

Performance degradation or failure of manufacturing equipment will badly influence machining quality. Because of discontinuousness of the milling process, dynamic signals produced in the milling process become non-stationary. This paper indicates that the essence of SGW (second generation wavelet) transform in non-stationary signal processing is the mathematics principle of inner product transform of a dynamic signal with basis functions. Namely, by means of the inner product operation of a signal with basis functions containing scale function and wavelet function, signal decomposition and reconstruction are obtained. Acoustic emission signals generated in the milling processes of a CNC machine were analyzed by using the basis functions of SGW which are oscillation, decay and compact support. The features of end milling cutter breakage have been extracted, and the influences on machining surface quality have been identified effectively, which provide scientific bases for fault diagnosis, error tracing and quality control.