The paper presents a process controller aimed at improving the performance of the surface quality generated by traverse grinding process, avoiding the limitation caused by vibrations onset. Not many examples of grinding process control devoted to vibration control can be found in the specific literature and the innovation provided by the proposed controller consists in suppressing vibration occurrence by means of a robust approach that exploits both model-based and self-learning functionalities. The designed control system has two basic functions: the recognition of machining situation, as anomalous vibration or onset of chatter and the decision making about the control actions. In the studied case vibration are mainly caused by wheel regenerative chatter and therefore the main control variable that is controlled is the wheel velocity, which is tuned exploiting an adaptive Speed tuning Map computed from the controller by using an heuristic approach and learning methodology. Experimental tests has been carried out on a roll grinder to validate the control system and good performance is achieved after some training tests for the tuning of the controller parameters.
Advanced Process Control for Improving Surface finishing in Traverse Grinding
Leonesio M;Bianchi G
2015
Abstract
The paper presents a process controller aimed at improving the performance of the surface quality generated by traverse grinding process, avoiding the limitation caused by vibrations onset. Not many examples of grinding process control devoted to vibration control can be found in the specific literature and the innovation provided by the proposed controller consists in suppressing vibration occurrence by means of a robust approach that exploits both model-based and self-learning functionalities. The designed control system has two basic functions: the recognition of machining situation, as anomalous vibration or onset of chatter and the decision making about the control actions. In the studied case vibration are mainly caused by wheel regenerative chatter and therefore the main control variable that is controlled is the wheel velocity, which is tuned exploiting an adaptive Speed tuning Map computed from the controller by using an heuristic approach and learning methodology. Experimental tests has been carried out on a roll grinder to validate the control system and good performance is achieved after some training tests for the tuning of the controller parameters.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.