Online chatter detection in robotic machining based on adaptive variational mode decomposition

Chatter is the main problem that limits application of industrial robots in field machining process. It critically important to establish an adaptive chatter detection solution for robot process and realize online chatter. However, different from machine tool chatter, robotic more complex be detected due variable stiffness characteristics weaker normal robot, existing literature has less research on this problem. This paper presents a comprehensive Firstly, order detect avoid mode mixing variational decomposition (VMD) process, (AVMD) method based kurtosis instantaneous frequency proposed, which realizes selection parameter. Secondly, optimal parameters are calculated by using genetic algorithm. By optimizing discrete step length parameter, it greatly reduces optimization time. Last but not least, approximate entropy, energy proposed entropy drift coefficient extracted distinguish stable state. Simulation experimental results show can meet real-time requirements occurrence effectively.