{"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}
引用次数: 0
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.