An Intelligent Pulse Classification System for the Process Control of the Electro Chemical Discharge Machining (ECDM) Process

Abstract

The performance of an Electro Chemical Discharge Machining (ECDM) process, in terms of surface finish and rate of machining is significantly influenced by the performance of the feed control system, the process control system, and the pulse generator. This paper presents the design stages of an Adaptive Neuro Fuzzy Inference System (ANFIS) for the Pulse Classification of the ECDM process. Inter-electrode gap signals such as voltage and working current waveforms were aquired and analysed. Five types of pulses were identified. An Adaptive Neuro Fuzzy Inference System (ANFIS) was developed to classify the pulses.