An Intelligent Control System for Grinding

Based on expert system, fuzzy logic, neural network and grinding theory, an intelligent control system for grinding process was proposed. The system is constructed by grinding parameter decision support system (DSS), size prediction control system ( SPCS) and roughness prediction control system ( RPCS). The initial grinding parameters are decided by the grinding parameter decision support system (DSS) based on neural network. Size prediction control system (SPCS) is constructed by fuzzy control subsystem, deformation control subsystem and size prediction subsystem. The first and the second derivative of the actual amount removed from the workpiece are added into the network input, which can greatly improve the size prediction accuracy. The roughness prediction control system ( RPCS) is made from surface roughness prediction subsystem and fuzzy neural network controller, which can adapt grinding parameters in process to decrease the surface roughness of machined parts when the roughness is not meeting requirements. The experiment of the external cylindrical grinding was implemented. The results showed that this intelligent control system was feasible, and could significantly increase the grinding quality.