Detection algorithm of sub⁃surface crack damage in ultrasonic vibration assisted cutting of monocrystalline silicon

被引：0
|
作者：
Cheng G. [1 ,2 ]
Hao Z.-P. [1 ]
Zhang Z. [2 ]
机构：
[1] School of Mechatronic Engineering, Changchun University of Technology, Changchun
[2] College of Humanities and Information, Changchun University of Technology, Changchun
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2022年 / 52卷 / 05期
关键词：
Crack damage detection; Machine vision; Monocrystalline silicon; Sub-surface; Ultrasonic vibration;
D O I：
10.13229/j.cnki.jdxbgxb20210166
中图分类号：
学科分类号：
摘要：
In order to reduce the sub-surface damage of machined parts, a sub-surface crack detection algorithm based on machine vision for ultrasonic vibration assisted cutting of monocrystalline silicon is proposed. A set of monocrystalline silicon surface image acquisition device was set up. A appropriate light source was selected to collect the crack damage image with high resolution. Gaussian kernel and image entropy were used to extract the crack damage feature points and feature scales, and the crack features and the second-order guided junction of Gaussian function were combined for convolution processing, which was used for crack damage detection. The maximum value under multiple feature scales was used as the detection result. The experimental results show that the detection accuracy of the designed detection algorithm based on machine vision can reach more than 0.9, and the detection effect is good. © 2022, Jilin University Press. All right reserved.
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页码：1016 / 1021
页数：5
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