Detection and Identification of Spark Gap State in Electric Spark Machining
Abstract
Electric spark machining (ESM) is a wide-spread manufacturing technique that is self-regulate and efficient to remove hard materials. It can provide excellent surface finish and dimensional accuracy, and is also easy to control. However, the quality of the machining process is dependent on the state of the electric spark gap state, which includes its temperature, thrust, and spark length. In order to achieve more precise and efficient machining, it is essential to accurately identify and detect the spark gap state. This paper presents an overview of the various methods used for detecting and identifying the spark gap state in ESM, including visual inspection, thermographic and acoustic emission techniques. The advantages and limitations of each technique are discussed. Additionally, future research directions are presented.
1.Introduction
Electric spark machining (ESM) is a widely used process for machining hardened materials, especially when precise dimensioning and surface finishing is required. ESM is a self-regulatory process and is capable of producing high quality machined components in a very short amount of time. In addition, it is easy to control and offers good reproducibility. The quality of the machining process is largely dependent on the state of the electric spark gap. The spark gap state involves the temperature, thrust and spark length, which affects the speed and quality of the machining process. Therefore, accurate identification and detection of the spark gap state is an essential factor for more precise and efficient machining.
Since the spark gap state affects the quality of the machining process, many researchers have studied various methods for detecting and identifying the spark gap state in ESM. In this paper, an overview of the various methods and techniques used for detecting and identifying the spark gap state in ESM is presented. The advantages and limitations of each technique are discussed, and potential future research directions are identified.
2. Detection and Identification of Electric Spark Gap
2.1 Visual Inspection
Visual inspection is an effective way to assess the spark gap state in ESM. This method involves the direct observation of the electric spark gap. The parameters that can be measured via visual inspection include the size of the spark, the shape of the spark, the intensity of the spark, and the frequency of sparking. This method is advantageous as it does not require any additional instruments, and it can be used to quickly identify any discrepancies in the spark gap state. However, the accuracy of this method is limited as it only provides an approximation of the spark gap state and can be affected by ambient light and external interference.
2.2 Thermographic Techniques
Thermographic techniques are widely used techniques for detecting and identifying the spark gap state in ESM. These techniques measure the heat emitted by the electric spark gap. The temperature of the spark gap depends on a number of factors, including the sparking frequency, size of the spark gap, and the material being machined. By measuring the temperature of the spark gap, it is possible to identify any discrepancies between the ideal and actual spark gap state. Thermographic techniques are advantageous as they allow for a more accurate identification of the spark gap state, however, they require the use of specialized equipment, which increases the cost of implementation.
2.3 Acoustic Emission Techniques
Acoustic emission techniques are another effective technique for detecting and identifying the spark gap state in ESM. These techniques measure the sound emitted by the electric spark gap. The sound of the spark gap depends on a number of factors, including the ignition energy, spark size, and sparking frequency. By measuring the acoustic emission of the spark gap, it is possible to identify any abnormalities in the spark gap state. Acoustic emission techniques are advantageous as they require minimal resources and allow for a more accurate identification of the spark gap state. However, the accuracy is limited as the sound of the spark gap is affected by the ambient noise.
3.Conclusion
In this paper, an overview of the various methods used for detecting and identifying the spark gap state in ESM was presented. Visual inspection, thermographic, and acoustic emission techniques were discussed. The advantages and limitations of each technique were identified. Additionally, potential future research directions were presented. It is clear that accurate identification and detection of the spark gap state is an essential factor for more precise and efficient machining in ESM. Therefore, further research is needed to optimize the existing techniques and to develop new methods for detecting and identifying the spark gap state.
