Chatter Detection With Beat Effect Based on Beat Frequency Estimation

Abstract

Machining chatter is an unstable vibration that often results in poor surface quality, low productivity, and degraded machine tool life. Chatter detection is an important approach to timely avoid detrimental effects on the workpiece and machine tools. However, most chatter detection methods will lose effectiveness and even yield false alarms, when chatter is accompanied by the beat effect. The beat effect is a common phenomenon in the machining process, which results in severely modulated amplitude of chatter. In this article, the variable-scale wavelet packet entropy (VSWPE) is proposed to detect chatter with the beat effect based on beat frequency estimation. First, an optimal demodulation technique is presented to extract the chatter vibration component and its modulated instantaneous amplitude (IA) from measured signals contaminated with noise and periodic interference. Afterward, the beat frequency is estimated from the harmonically distorted IA by an interpolated discrete Fourier transform (DFT). Finally, the VSWPE is calculated for chatter detection at a variable scale that is adaptively computed by the beat frequency. Numerical simulations show that the beat frequency can be accurately estimated with computational efficiency. Moreover, machining tests under different cutting conditions demonstrate that the proposed chatter detection method can effectively detect chatter with the beat effect. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Automatic online chatter detection is crucial in order to allow operators to timely interfere with the process and avoid detrimental effects caused by chatter. However, the practical machining process is considerably complex especially for unstable scenarios, where the beat effect is likely to occur simultaneously. Traditional chatter detection methods neglect the presence of the beat effect, and they will give misleading results and even false alarms when the beat effect is present. This article seeks to accurately detect chatter with and without the beat effect in a unified framework. The proposed solution can be integrated into the machine tool system, hence, to enhance the productivity, reliability, and precision of the machining process.