Enhancing Chatter Vibration Analysis in Turning Processes through Advanced Multiple-denoising Wavelet Techniques

This study investigated the natural frequency of a self-excited vibrating workpiece and cutting tool using a hammer impact test to acquire vibration data. Time-domain cutting vibration data were converted to the frequency domain using FFT. The workpiece signal exhibited a high amplitude, peaking at 392 Hz, while the cutting tool signal presented a peak at 930 Hz. Stability Lobe Diagrams were constructed to assess dynamic stability. Cutting experiments revealed an obvious relationship between spindle speed and signal amplitude, with higher speeds leading to larger amplitudes. Frequency analysis revealed a peak near the cutting tool's 900 Hz natural frequency. Smoother surface finishes were observed at 0.15 mm cutting depth, while 0.2 mm resulted in a wavy surface, indicating chatter. To investigate chatter frequency and reduce noise, a multiple-denoising method combined Bior 3.7 and DB10 wavelets to reduce amplitude and improve signal representation, especially for non-smooth features. The proposed method aimed to reduce the 900 Hz cutting tool’s natural frequency. Results showed a clear chatter frequency at 450-480 Hz for 0.2 mm depth cuts at spindle speeds of 500, 1,000, and 1,400 rpm. The proposed method exhibited high efficiency, achieving the higher signal-to-noise ratio and lower mean-square error than Bior 3.7 and DB10 wavelet denoising techniques.