Maintain Voltage Phenomenon Mechanism, Based On Fractal And Wavelet Spark

Although electro discharge machining (EDM) is widely used in manufacture in nowadays, to a great extent, studies on this is only concentrating on the application fields such as machine tool design, process analysis etc. What's worse, the analysis of discharge principle, particularly the available information in the field of small clearance liquid medium low voltage discharge machining, is insufficient; neither the complete theory. Sustaining voltage phenomenon, one of the significant characteristics of sparkle discharge as well as an obstacle of micromachining, has not been reported yet on its mechanism study. However, this paper will introduce some latest theories such as fractal theory and wavelet system into the traditional discharge analysis; and combine which with the experiment of non-sustaining voltage RC pulse power supply to make a further research on the inherent mechanism of this phenomenon and establish the energy model of sparkle discharge basing on the analysis of literatures at home and abroad.Firstly, this paper has designed and completed the RC pulse power supply discharging experiment of needle-board electrode in liquid after consulting sufficient information. Combine with the traditional gas discharging theory; it also analyzes the process of discharge, and from which, the internal cause of sustaining voltage is revealed.Secondly, referring to the NPW model and WZ model which fit the dielectric breakdown in fractal growth theory; discovering a better algorithm through the improvement of the two models, verifies the logicalness of the new algorithm with the simulation of discharge path of RC pulse power supply in MATLAB and the comparison with the pictures token in experiment,Thirdly, generates signals of sustaining voltage and discharge signals of RC pulse power supply by the decomposition by Haar wavelet systems, furthermore, draws a conclusion by the comparison of the energy distributions of the two signals-on the whole, both of the two signals are distributed at low frequency. However, when being transformed by the wavelet component in revolution of a certain level, energy of the former one generally presents a normal distribution while the latter one is still distributed uniformly. Finally, grasping the starting point of the different energy distribution of two discharge signals, introduces variables such as probability density function, Haar wavelet scaling function as well as the fractal growth units, so as to construct the energy model of sparkle discharge.