The main advantages of the electrochemical machining (ECM) process, such as high material removal rates and smooth, damage-free machined surface, are often offset by the poor dimensional control and process stability resulting from the complex and stochastic nature of the interelectrode gap (IEG) states. Full economic utilization of ECM will be realized only when reliable dimensional and process control systems are developed. This paper presents an ECM control model based on the basic ECM dynamics that accounts for the dynamic nature of the ECM process. The state space methodology is applied to transform it into the control model applicable to an ECM control system based on a digital computer. The simulations have been made for the model verification and controller design. A new approach is introduced to develop an indicator that detects or predicts the onset of random sparks based on ECM current signal analysis. ECM current and voltage signals have been acquired using a specially-built data acquisition circuit. The signals are digitized and analyzed with an IBM PC. The frequency analysis of the signal leads to a better insight of the physical mechanism of the ECM process. A comprehensive review of the state-of-the-art ECM research and development efforts in the areas of spark and short circuit detection and IEG control is also included in the paper.

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