The article presents the scientific rationale for the approach to the development of an adaptive management system for the electric discharge machining process based on artificial intelligence principles to achieve the required surface quality of the workpiece. A three-layer neural network for controlling the process of electric discharge machining and a block diagram of the research bench to study the efficiency of electric discharge machining with the use of the developed adaptive control system are described.
Similar content being viewed by others
References
Yu. G. Kabaldin, S. V. Bilenko, and S. V. Seryi, Dynamic Process Management Technology in Machining Systems Based on Artificial Intelligence, Koms.-na-Amure Gos. Tekhn. Univ., Komsomolsk-on-Amur (2003).
M. K. Mitskevich, A. I. Bushin, I. A. Bakuto, et al., Electrical Discharge Machining of Materials, I. G. Nekrashevich (ed.), Nauka i Tekhnika, Minsk (1988).
A. L. Lifshitz, A. T. Kravets, I. S. Rogachev, and A. B. Sosenko, Electropulse Metal Machining, Mashinostroyenie, Moscow (1967).
B. N. Zolotykh and R. R. Melder, Physical Principles of Electrical Discharge Machining, Mashinostroenie, Moscow (1977).
Author information
Authors and Affiliations
Corresponding author
Additional information
Translated from Khimicheskoe i Neftegazovoe Mashinostroenie, No. 3, pp. 21–24, March, 2016.
Rights and permissions
About this article
Cite this article
Erenkov, O.Y., Sarilov, M.Y. Adaptive Control System of the Electric Discharge Machining Process. Chem Petrol Eng 52, 182–186 (2016). https://doi.org/10.1007/s10556-016-0172-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10556-016-0172-y