A chatter online prediction method and system software in high-speed grinding of camshaft

Chatter is a self-induced vibration that results in poor surface quality in the high-speed camshaft grinding process. Accurate and timely chatter prediction is very important for chatter suppression. Consequently, an online chatter prediction method and chatter software system for intelligent manufacturing are urgently required. This paper proposes a novel strategy to predict the chatter for the high-speed grinding process of the camshaft. In this method, the vibration signals acquired by the sensor are decomposed by variational mode decomposition. The backpropagation neural networks model is used to predict grinding chatter. High-speed grinding experiments with different conditions were performed to evaluate the effectiveness of the proposed method. Finally, the vibration state prediction system is developed promptly for chatter prediction. The results show that the proposed method is suitable for chatter prediction in the high-speed grinding process of camshaft, and the correct rate of chatter prediction is 96.4%.