下一代视觉检测系统:从三维模型到 ReCo 文件的流水线

IF 5.9 2区 工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent Manufacturing Pub Date : 2024-08-01 DOI:10.1007/s10845-024-02456-6
Francesco Lupi, Nelson Freitas, Miguel Arvana, Andre Dionisio Rocha, Antonio Maffei, José Barata, Michele Lanzetta
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引用次数: 0

摘要

本文在《Lupi, F., Maffei, A., & Lanzetta, M. (2024)》一书中概述的模块化框架基础上,提出并实施了一种新的管道,用于对灵活、可重构、基于 CAD 的自主视觉检测系统(VIS)进行自我重新配置。基于 CAD 的自主视觉检测系统。Procedia Computer Science, 232, 2127-2136. https://doi.org/10.1016/J.PROCS.2024.02.033)。根据基于模型的设计(MBD)原则,该管道可自动提取和处理设计人员在设计阶段手动纳入计算机辅助设计(CAD)三维模型的检测特征,这反过来又促进了并行工程和设计(Dfx)等良性方法,最终最大限度地缩短了产品上市时间。丰富的 CAD 包含附加到几何实体上的检测注释(文本或尺寸),作为管道的输入,可以按照产品数据交换标准(STEP)应用协议(AP)242 以中性文件格式导出,与所使用的建模软件无关。该管道的输出是一个重新配置(ReCo)文件,可通过软件(可编程)对 VIS 的灵活硬件(如机器人检测单元)和软件组件进行重新配置。这项工作的主要成果包括(i) 演示了端到端(即 CAD 到 ReCo 文件)流水线的可行性,该流水线通过应用编程接口 (API) 集成了建议的软件模块,以及 (ii) 正式定义了 ReCo 文件。演示实施的实验结果增强了本文的清晰度。缺陷检测的准确率达到了 96% 的真阳性率和 6% 的假阳性率,从而在两种产品变体的六种不同检测特征的 72 项质量检测中,每项检测对六个样品进行了测试,总体准确率为 94%,精确率为 88%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Next-generation Vision Inspection Systems: a pipeline from 3D model to ReCo file

This paper proposes and implements a novel pipeline for the self-reconfiguration of a flexible, reconfigurable, CAD-based, and autonomous Vision Inspection System (VIS), expanding upon the modular framework theoretically outlined in (Lupi, F., Maffei, A., & Lanzetta, M. (2024). CAD-based Autonomous Vision Inspection Systems. Procedia Computer Science, 232, 2127–2136. https://doi.org/10.1016/J.PROCS.2024.02.033.). The pipeline automates the extraction and processing of inspection features manually incorporated by the designer into the Computer Aided Design (CAD) 3D model during the design stage, in accordance with Model Based Design (MBD) principles, which, in turn, facilitate virtuous approaches such as concurrent engineering and design for (Dfx), ultimately minimizing the time to market. The enriched CAD, containing inspection annotations (textual or dimensional) attached to geometrical entities, serving as the pipeline’s input, can be exported in a neutral file format, adhering to the Standard for Product Data Exchange (STEP) Application Protocol (AP)242, regardless of the modeling software used. The pipeline’s output is a Reconfiguration (ReCo) file, enabling the flexible hardware (e.g., robotic inspection cell) and software components of the VIS to be reconfigured via software (programmable). The main achievements of this work include: (i) demonstrating the feasibility of an end-to-end (i.e., CAD-to-ReCo file) pipeline that integrates the proposed software modules via Application Programming Interfaces (API)s, and (ii) formally defining the ReCo file. Experimental results from a demonstrative implementation enhance the clarity of the paper. The accuracy in defect detection achieved a 96% true positive rate and a 6% false positive rate, resulting in an overall accuracy of 94% and a precision of 88% across 72 quality inspection checks for six different inspection features of two product variants, each tested on six samples.

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来源期刊
Journal of Intelligent Manufacturing
Journal of Intelligent Manufacturing 工程技术-工程:制造
CiteScore
19.30
自引率
9.60%
发文量
171
审稿时长
5.2 months
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.
期刊最新文献
Industrial vision inspection using digital twins: bridging CAD models and realistic scenarios Reliability-improved machine learning model using knowledge-embedded learning approach for smart manufacturing Smart scheduling for next generation manufacturing systems: a systematic literature review An overview of traditional and advanced methods to detect part defects in additive manufacturing processes A systematic multi-layer cognitive model for intelligent machine tool
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