Affiliations: [a] School of Mechanical Engineering, Xi’an Technological University, Xi’an, China
| [b] School of Mechanical Engineering, Longdong University, Qingyang, China
| [c] Shaanxi Key Laboratory of Non-Traditional Machining, Xi’an Technological University, Xi’an, China
Correspondence:
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Corresponding author. Baoji Ma, School of Mechanical Engineering, Xi’an Technological University, E-mail: mabaojee@163.com.
Abstract: The electrochemical discharge machining process is affected by many factors, so the machining process is difficult to be qualitatively analyzed. In order to further understand the characteristics of the electrochemical discharge machining process and better master the machining skills, based on the image features, this article uses the SVM algorithm to build an electrochemical discharge machining system, and uses image feature recognition technology to effectively control the electrochemical discharge machining process. Moreover, this article analyzes the laser back-wet etching process mechanism and discusses the material removal mechanism of electrochemical discharge machining according to the three processes of bubble generation, gas layer formation, and spark discharge removal material. In addition, this article analyzes the system performance according to the actual situation and displays the results through statistical methods. The research results show that the electrochemical discharge machining system based on image features and SVM algorithm constructed in this paper has a good effect, and it can be applied to the management and control of the electrochemical discharge machining process.
