An artificial neural network approach for pulse classification in electro chemical discharge machining (ECDM) – designing of neural network architecture

T. K.K.R. Mediliyegedara, Anjali K.M. De Silva, David K. Harrison, J. A. McGeough

Research output: Contribution to journalArticle

Abstract

This paper presents the pulse classification of the ECDM process using artificial neural networks (ANN). An Electro Discharge Machining (EDM) machine was modified by incorporating an electrolyte system and by modifying the control system. Gap voltage and working current waveforms were obtained. By observing the waveforms, pulses were classified into five groups. A feed forward neural network was trained to classify pulses. Various neural network architectures were considered by changing the number of neurons in the hidden layer. The trained neural networks were simulated. A quantitative analysis was performed to evaluate various neural network architectures.

Original languageEnglish
JournalInternational Journal of Manufacturing Science and Technology
Publication statusPublished - 1 Jan 2005

Keywords

  • electrochemical machining
  • pulse classification
  • ECM
  • neural network architecture

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