基于图像处理的金属型材截面尺寸识别

I. M. Orak, Şaban Şeker
{"title":"基于图像处理的金属型材截面尺寸识别","authors":"I. M. Orak, Şaban Şeker","doi":"10.4236/jcc.2023.118008","DOIUrl":null,"url":null,"abstract":"In steel plants, estimation of the production system characteristic is highly critical to adjust the system parameters for best efficiency. Although the sys-tem parameters may be tuned very well, due to the machine and human factors involved in the production line some deficiencies may occur in product. It is important to detect such problems as early as possible. Surface defects and dimensional deviations are the most important quality problems. In this study, it is aimed to develop an approach to measure the dimensions of metal profiles by obtaining images of them. This will be of use in detecting the deviations in dimensions. A platform was introduced to simulate the real-time environment and images were taken from the metal profile using 4 laser light sources. The shape of the material is generated by combining the images taken from different cameras. Real dimensions were obtained by using image processing and mathematical conversion operations on the images. The re-sults obtained with small deviations from the real values showed that this method can be applied in a real-time production line.","PeriodicalId":67799,"journal":{"name":"电脑和通信(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sectional Dimensions Identification of Metal Profile by Image Processing\",\"authors\":\"I. M. Orak, Şaban Şeker\",\"doi\":\"10.4236/jcc.2023.118008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In steel plants, estimation of the production system characteristic is highly critical to adjust the system parameters for best efficiency. Although the sys-tem parameters may be tuned very well, due to the machine and human factors involved in the production line some deficiencies may occur in product. It is important to detect such problems as early as possible. Surface defects and dimensional deviations are the most important quality problems. In this study, it is aimed to develop an approach to measure the dimensions of metal profiles by obtaining images of them. This will be of use in detecting the deviations in dimensions. A platform was introduced to simulate the real-time environment and images were taken from the metal profile using 4 laser light sources. The shape of the material is generated by combining the images taken from different cameras. Real dimensions were obtained by using image processing and mathematical conversion operations on the images. The re-sults obtained with small deviations from the real values showed that this method can be applied in a real-time production line.\",\"PeriodicalId\":67799,\"journal\":{\"name\":\"电脑和通信(英文)\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"电脑和通信(英文)\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.4236/jcc.2023.118008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"电脑和通信(英文)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.4236/jcc.2023.118008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在钢铁厂中,对生产系统特性的估计对于调整系统参数以获得最佳效率至关重要。虽然系统参数可以调得很好,但由于生产线中涉及的机器和人为因素,产品可能会出现一些缺陷。尽早发现这些问题很重要。表面缺陷和尺寸偏差是最重要的质量问题。在这项研究中,它的目的是开发一种方法来测量金属型材的尺寸,获得他们的图像。这在检测尺寸偏差时是有用的。介绍了一个模拟实时环境的平台,并使用4个激光光源从金属轮廓上获取图像。材料的形状是由不同相机拍摄的图像组合而成的。通过对图像进行图像处理和数学转换运算,得到实数尺寸。结果表明,该方法与实际值偏差较小,可用于实时生产线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Sectional Dimensions Identification of Metal Profile by Image Processing
In steel plants, estimation of the production system characteristic is highly critical to adjust the system parameters for best efficiency. Although the sys-tem parameters may be tuned very well, due to the machine and human factors involved in the production line some deficiencies may occur in product. It is important to detect such problems as early as possible. Surface defects and dimensional deviations are the most important quality problems. In this study, it is aimed to develop an approach to measure the dimensions of metal profiles by obtaining images of them. This will be of use in detecting the deviations in dimensions. A platform was introduced to simulate the real-time environment and images were taken from the metal profile using 4 laser light sources. The shape of the material is generated by combining the images taken from different cameras. Real dimensions were obtained by using image processing and mathematical conversion operations on the images. The re-sults obtained with small deviations from the real values showed that this method can be applied in a real-time production line.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
784
期刊最新文献
Evaluation of the Global Horizontal Irradiation (GHI) on the Ground from the Images of the Second Generation European Meteorological Satellites MSG Improving Resilience Models of Health Systems before COVID-19 Pandemic in Côte d’Ivoire COST 231-Hata Propagation Model Optimization in 1800 MHz Band Based on Magnetic Optimization Algorithm: Application to the City of Limbé Machine Learning-Based Approach for Identification of SIM Box Bypass Fraud in a Telecom Network Based on CDR Analysis: Case of a Fixed and Mobile Operator in Cameroon Supervised Learning Algorithm on Unstructured Documents for the Classification of Job Offers: Case of Cameroun
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1