Real-time vision-assisted electrochemical machining with constant inter-electrode gap

Abstract

Electrochemical machining (ECM) has attracted increasing interest as an effective technique to realize high machining accuracy for difficult-to-machine conductive materials. The inter-electrode gap (IEG) has a direct effect on the ECM process performance in terms of process stability, machining accuracy, and surface quality. To understand the evolution of the IEG during the ECM process, in-situ observation and control of the IEG are required. This paper explores the use of visual assistance as a passive, in-line IEG measurement control technique to realize a consistent IEG throughout the ECM process. Here, a vision-assisted constant-IEG electrochemical machining process is proposed. The accuracy of this technique was confirmed via correspondence between the real-time IEG size and pixel data. A specially designed visual tracking and control system to implement a constant IEG in the ECM and a decision-making system to ensure process stability are presented. An experimental platform was designed and implemented, and a series of experiments were carried out on 3D structures of Inconel 718 alloy. The experimental results demonstrate that the proposed method can clearly identify IEG information from the machining region, and effectively restrict IEG fluctuation to a small value in ECM, which ultimately improved the machining accuracy and surface quality of the manufactured parts. Additionally, the machined surface presented preferential dissolution along the grain boundary and generated carbide and oxide products of Ti and Nb elements, because of enrichment of Ti and Nb elements and depletion of Cr, Fe, and Ni elements in the grain boundary regions.