MONITORING AND SELF-LEARNING FUZZY CONTROL FOR WIRE RUPTURE PREVENTION IN WIRE ELECTRICAL-DISCHARGE MACHINING

Wire breaking is a serious problem in the application of wire electric al discharge machining (WEDM). A WEDM sparking frequency monitoring an d control system based on the characteristics of the voltage waveform of WEDM is developed. A new self-learning fuzzy controller is proposed to control the sparking frequency at a safe level by regulating the p ulse off-time in real time for avoiding wire rupture and maintaining a state of high metal removal rate. The developed control strategy is t ested under the conditions of cutting a workpiece with continuous shar p angles, a change in workpiece height during machining process, and m achining with a high feed-rate. Experimental results show that this mo nitoring and control system can control the sparking frequency at a pr edetermined level without the risk of wire rupture.