Chatter detection in turning process using sound signal and simple microphone

Abstract

Chatter is a problem that frequently found in the area of a machining process, which brings down machining productivity and surface quality. Therefore, reliable and intense chatter detection methods are needed to maintain machining quality. In this study, turning chatter detection approach by using sound signals and a simple microphone is proposed to get an accurate, simple, and low-cost detection method. For that purpose, an experimental set-up which consists of an operating turning machine, simple microphone, and Personal Computer (PC) with sound card was arranged. The chatter in the turning process was stimulated by applying artificial wear to the cutting tool. The sound signal data from normal and with chatter turning process were then grabbed by a simple microphone and PC with a sound card. The sound signals were then evaluated by Fast Fourier Transform (FFT) and Wavelet Transform (WT) for normal and chatter conditions. Both conditions data were then compared to get the characteristic of the sound signal in chatter. It is found that signals in the frequency domain, time-frequency and spectrogram have a significant magnitude spike in chatter condition. The results demonstrated that the proposed method could conscientiously identify the chatter.