Sound generation mechanism for milling processes with varied parameters from force and vibration aspects

Abstract

Audible sound signals have shown broad application prospects in the online monitoring of tool wear states due to their non-invasive nature. However, the collection and noise reduction of sound signals are often complex, which results in relatively low prediction accuracy in practical applications. Therefore, a clear understanding of the sound generation mechanism in milling processes is essential for improving monitoring reliability. This paper designed multi-condition milling experiments to capture milling sound, spindle vibration, workpiece vibration, and milling force signals. The sound generation mechanism was analyzed from both time and frequency domains perspectives, with particular emphasis on vibration and force characteristics. The results indicate that milling sound increases with the milling parameters, with spindle speed ( n ) having the most significant impact, followed by feed rate ( f ) and milling width ( a p ), while milling depth ( a e ) has the least effect. The frequency distributions of sound, vibration, and force signals are similar, with a concentration in the 0∼2500 Hz range and energy peaks at the TPF and its harmonics.