A measurement method for roughness of micro-heterogeneous surface in deep hole

W. Liu, Xiuyan Zheng, Xinghua Jia, Li Fan, Shuangjun Liu, Zhenyuan Jia
{"title":"A measurement method for roughness of micro-heterogeneous surface in deep hole","authors":"W. Liu, Xiuyan Zheng, Xinghua Jia, Li Fan, Shuangjun Liu, Zhenyuan Jia","doi":"10.1109/ICICIP.2010.5564171","DOIUrl":null,"url":null,"abstract":"Due to the inherent limitations of structure and dimensional, it is difficult to measure the surface roughness of micro-heterogeneous surface in deep hole. In this paper, the microscopic image of micro-heterogeneous surface is obtained by the long working distance lenses of digital microscopic camera, firstly. Thereafter, two artificial neural network models, which take microscopic image features as the inputs, are presented to measure the surface roughness. Then, experiments on the microscopic image acquisition and roughness calibration are conducted. Finally, the analysis results indicate that the proposed measurement method is efficient and effective for evaluating the microcosmic surface roughness of micro-heterogeneous surface in deep hole.","PeriodicalId":152024,"journal":{"name":"2010 International Conference on Intelligent Control and Information Processing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Intelligent Control and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2010.5564171","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Due to the inherent limitations of structure and dimensional, it is difficult to measure the surface roughness of micro-heterogeneous surface in deep hole. In this paper, the microscopic image of micro-heterogeneous surface is obtained by the long working distance lenses of digital microscopic camera, firstly. Thereafter, two artificial neural network models, which take microscopic image features as the inputs, are presented to measure the surface roughness. Then, experiments on the microscopic image acquisition and roughness calibration are conducted. Finally, the analysis results indicate that the proposed measurement method is efficient and effective for evaluating the microcosmic surface roughness of micro-heterogeneous surface in deep hole.
深孔微非均匀表面粗糙度的测量方法
由于结构和尺寸的固有限制,深孔微非均质表面粗糙度的测量存在一定的困难。本文首先利用数码显微相机的长工作距离镜头获得了微非均匀表面的显微图像。在此基础上,提出了两种以微观图像特征为输入的人工神经网络模型来测量表面粗糙度。然后,进行了显微图像采集和粗糙度标定实验。最后,分析结果表明,所提出的测量方法对于评价深孔微非均匀表面的微观表面粗糙度是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信