EPJ Web Conf.
Volume 224, 2019IV International Conference “Modeling of Nonlinear Processes and Systems” (MNPS-2019)
|Number of page(s)||6|
|Section||Mechanical Engineering and Material Sciences|
|Published online||09 December 2019|
Dynamic Model of Electrical Discharge Machining and Algorithm of Extreme Control Through Acoustic Signal
Moscow State Technological University “STANKIN”, RU-127055, Moscow, Russia
2 College of Mechanical Engineering, University of Shanghai for Science & Technology, CN-200093, Shanghai, China
* e-mail: firstname.lastname@example.org
Published online: 9 December 2019
Electrical discharge machining (EDM) is one of the most accurate methods for machining conductive materials and has a number of important applications. In the EDM process the occurrence of electric charges between cathode and anode is accompanied by vibroacoustic signals, which can be used to develop highly efficient control and diagnostics systems. Experimental studies and modelling of the dynamic system of the EDM process carried out in this study show that parameters of acoustic signals can be used to estimate the current productivity and risks of the tool-electrode breakage and to optimize the tool feed rate. The obtained results of allows using acoustic signals in the control system of the tool electrode feed rate to prevent its breakage, and also setting the interelectrode gap to maximum productivity.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.