Citation
Samin, R and Nuawi, M Z and Ariffin, MF and Rahim, SA and Haris, S M and Ghani, J A
(2024)
Chatter identification of vibration signals and surface roughness using wavelet transform and I-kaz™ statistical methods.
In: 7th International Conference on Noise, Vibration and Comfort (NVC 2023), 5-7 Dec. 2023, Kuala Lumpur, Malaysia. (pp. 1-8).
Abstract
The paper describes the method to identify chatter in low-cutting-speed operations. It is based on vibration and surface roughness measurements. Tool chatter is the self-excited relative motion between the cutting tool and work piece. Tool chatter leads to poor surface quality and tool wear. The LMS Scadas testing system and accelerometer were used to measure the vibration signals during the turning operation, and Marsuft Psi was used to measure the surface roughness. When various cutting parameter combinations, such as cutting speed, feed rate, and depth of cut, were employed throughout the machining process, chatter and vibrating phenomena occurred. After the recorded signals were analyzed using the wavelet transform (WT), a chatter index (CI) was produced to determine how severe the chatter was. According to the results analysis, the experimental study demonstrated the close relationship between the surface roughness values and the chatter index when evaluating chatter identification.
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