Papers by Author: Guo Fa Li

Abstract: A dynamic intelligent prediction control system is built in slender cylindrical grinding. Elman network is used in the dynamic size prediction control model, and 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 dynamic prediction accuracy. Moreover, a surface roughness equation with vibration data is proposed. Based the equation, the surface roughness dynamic fuzzy neural network prediction subsystem is built. Experiment verifies that the developed prediction control system is feasible and has high prediction and control accuracy.

Abstract: A real-time model of two-direction grinding force for external plunge grinding process has been built based on the research of grinding system dynamics equation. The two-direction grinding force can be measured on-line by a force cell sensor developed in this paper. And the grinding depth and grinding force, which depend on grinding time, were dynamic simulated by computer simulation. The experimental results are in good agreement with the simulation results, proved the real-time model’s exactitude. The real-time models showed in this paper not only can predict and evaluate grinding behave and quality, but also provide the precondition for grinding optimum, intelligential control, and virtual grinding research etc.