{"title":"在物体表面检测过程中优化自动白光干涉仪的图像采集","authors":"Björn Schwarze, Stefan Edelkamp","doi":"10.1007/s10845-023-02306-x","DOIUrl":null,"url":null,"abstract":"<p>This paper considers the efficient quality assurance of diverse geometric objects through the use of a white-light interferometer, with a primary focus on minimizing the number of required image captures. The motivation behind such an algorithm stems from the extended recording times associated with various free-form sheet metal parts. Given that capturing images with a microscope typically consumes 30–40 s, maintaining high-quality assurance is imperative. A reduction in the number of images not only expedites part throughput but also enhances the economic efficiency. A unique aspect in this context is the requirement for focus points to consistently align with the part’s surface. We formulate this challenge in a mathematical framework, necessitating a comprehensive literature review to identify potential solutions, and introduce an algorithm designed to optimize the image acquisition process for inspecting object surfaces. The proposed algorithm enables efficient coverage of large surfaces on objects of various sizes and shapes using a minimal number of images. The primary objective is to create the most concise list of points that comprehensively encompass the entire object surface. Subsequently, the paper conducts a comparative analysis of various strategies to identify the most effective approach.</p>","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"97 1","pages":""},"PeriodicalIF":5.9000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of image acquisition by automated white-light interferometers during the inspection of object surfaces\",\"authors\":\"Björn Schwarze, Stefan Edelkamp\",\"doi\":\"10.1007/s10845-023-02306-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper considers the efficient quality assurance of diverse geometric objects through the use of a white-light interferometer, with a primary focus on minimizing the number of required image captures. The motivation behind such an algorithm stems from the extended recording times associated with various free-form sheet metal parts. Given that capturing images with a microscope typically consumes 30–40 s, maintaining high-quality assurance is imperative. A reduction in the number of images not only expedites part throughput but also enhances the economic efficiency. A unique aspect in this context is the requirement for focus points to consistently align with the part’s surface. We formulate this challenge in a mathematical framework, necessitating a comprehensive literature review to identify potential solutions, and introduce an algorithm designed to optimize the image acquisition process for inspecting object surfaces. The proposed algorithm enables efficient coverage of large surfaces on objects of various sizes and shapes using a minimal number of images. The primary objective is to create the most concise list of points that comprehensively encompass the entire object surface. Subsequently, the paper conducts a comparative analysis of various strategies to identify the most effective approach.</p>\",\"PeriodicalId\":16193,\"journal\":{\"name\":\"Journal of Intelligent Manufacturing\",\"volume\":\"97 1\",\"pages\":\"\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2024-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Intelligent Manufacturing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s10845-023-02306-x\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent Manufacturing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s10845-023-02306-x","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Optimization of image acquisition by automated white-light interferometers during the inspection of object surfaces
This paper considers the efficient quality assurance of diverse geometric objects through the use of a white-light interferometer, with a primary focus on minimizing the number of required image captures. The motivation behind such an algorithm stems from the extended recording times associated with various free-form sheet metal parts. Given that capturing images with a microscope typically consumes 30–40 s, maintaining high-quality assurance is imperative. A reduction in the number of images not only expedites part throughput but also enhances the economic efficiency. A unique aspect in this context is the requirement for focus points to consistently align with the part’s surface. We formulate this challenge in a mathematical framework, necessitating a comprehensive literature review to identify potential solutions, and introduce an algorithm designed to optimize the image acquisition process for inspecting object surfaces. The proposed algorithm enables efficient coverage of large surfaces on objects of various sizes and shapes using a minimal number of images. The primary objective is to create the most concise list of points that comprehensively encompass the entire object surface. Subsequently, the paper conducts a comparative analysis of various strategies to identify the most effective approach.
期刊介绍:
The Journal of Nonlinear Engineering aims to be a platform for sharing original research results in theoretical, experimental, practical, and applied nonlinear phenomena within engineering. It serves as a forum to exchange ideas and applications of nonlinear problems across various engineering disciplines. Articles are considered for publication if they explore nonlinearities in engineering systems, offering realistic mathematical modeling, utilizing nonlinearity for new designs, stabilizing systems, understanding system behavior through nonlinearity, optimizing systems based on nonlinear interactions, and developing algorithms to harness and leverage nonlinear elements.