{"title":"Fast error detection method for additive manufacturing process monitoring using structured light three dimensional imaging technique","authors":"","doi":"10.1016/j.optlaseng.2024.108609","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents a novel method to speed up error detection in an additive manufacturing (AM) process by minimizing the necessary three-dimensional (3D) reconstruction and comparison. We develop a structured light 3D imaging technique that has native pixel-by-pixel mapping between the captured two-dimensional (2D) image and the reconstructed 3D point cloud. This 3D imaging technique allows error detection to be performed in the 2D image domain prior to 3D point cloud generation, which drastically reduces complexity and computational time. Compared to an existing AM error detection method based on 3D reconstruction and point cloud processing, experimental results from a material extrusion (MEX) AM process demonstrate that our proposed method significantly increases the error detection speed.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optics and Lasers in Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0143816624005876","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a novel method to speed up error detection in an additive manufacturing (AM) process by minimizing the necessary three-dimensional (3D) reconstruction and comparison. We develop a structured light 3D imaging technique that has native pixel-by-pixel mapping between the captured two-dimensional (2D) image and the reconstructed 3D point cloud. This 3D imaging technique allows error detection to be performed in the 2D image domain prior to 3D point cloud generation, which drastically reduces complexity and computational time. Compared to an existing AM error detection method based on 3D reconstruction and point cloud processing, experimental results from a material extrusion (MEX) AM process demonstrate that our proposed method significantly increases the error detection speed.
本文提出了一种新方法，通过最大限度地减少必要的三维（3D）重建和比较，加快增材制造（AM）工艺中的误差检测。我们开发了一种结构光三维成像技术，该技术可在捕获的二维（2D）图像和重建的三维点云之间进行原生逐像素映射。这种三维成像技术允许在生成三维点云之前在二维图像域中进行误差检测，从而大大降低了复杂性和计算时间。与基于三维重建和点云处理的现有 AM 错误检测方法相比，材料挤压 (MEX) AM 过程的实验结果表明，我们提出的方法显著提高了错误检测速度。
期刊介绍：
Optics and Lasers in Engineering aims at providing an international forum for the interchange of information on the development of optical techniques and laser technology in engineering. Emphasis is placed on contributions targeted at the practical use of methods and devices, the development and enhancement of solutions and new theoretical concepts for experimental methods.
Optics and Lasers in Engineering reflects the main areas in which optical methods are being used and developed for an engineering environment. Manuscripts should offer clear evidence of novelty and significance. Papers focusing on parameter optimization or computational issues are not suitable. Similarly, papers focussed on an application rather than the optical method fall outside the journal''s scope. The scope of the journal is defined to include the following:
-Optical Metrology-
Optical Methods for 3D visualization and virtual engineering-
Optical Techniques for Microsystems-
Imaging, Microscopy and Adaptive Optics-
Computational Imaging-
Laser methods in manufacturing-
Integrated optical and photonic sensors-
Optics and Photonics in Life Science-
Hyperspectral and spectroscopic methods-
Infrared and Terahertz techniques
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