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Surface Roughness Assessment of Micro-EDM by Wavelet Analysis Based on Goodness of Fit Test

机译:基于拟合试验良善的小波分析对微EDM的表面粗糙度评估

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The surface topography errors of Micro-EDM are mainly composed of surface roughness, surface waveness and so on, which have influence on the workpiece's functions and performances in various degrees. Thus, how to pick up these errors without distortion is quite important for evaluating the surface topography. It is well known that Wavelet Transform has good time-frequency localization properties, which is especially suitable for image processing. Therefore, in this paper, a wavelet method for surface roughness of Micro-EDM is presented, in which, the time of wavelet decomposition is determined by Pearson Chi-square goodness of fit test. Furthermore, the results of simulation and experiments show that the proposed methods can separate Micro-EDM's surface roughness well, meanwhile, using the mean and variance of ideal surface as accuracy requirements of the reference surface could help the separation have a certain certainty and precision.
机译:微EDM的表面形貌误差主要由表面粗糙度,表面挥发性等组成,这对工件的功能和各种程度的性能产生影响。因此,如何在没有失真的情况下拾取这些误差对于评估表面形貌非常重要。众所周知,小波变换具有良好的时频定位特性,特别适用于图像处理。因此,在本文中,提出了一种用于微EDM的表面粗糙度的小波方法,其中,小波分解的时间由Pearson Chi-Square的配合测试确定。此外,模拟和实验结果表明,该方法可以利用井分离微EDM的表面粗糙度,同时使用理想表面的平均值和方差作为参考表面的精度要求,可以帮助分离具有一定的确定性和精度。

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