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Robust and High-Performance Machine Vision System for Automatic Quality Inspection in Assembly Processes

This paper addresses the problem of automatic quality inspection in assembly processes by discussing the design of a computer vision system realized by means of a heterogeneous multiprocessor system-on-chip. Such an approach was applied to a real catalytic converter assembly process, to detect plana...

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Autores principales: Frustaci, Fabio, Spagnolo, Fanny, Perri, Stefania, Cocorullo, Giuseppe, Corsonello, Pasquale
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9032890/
https://www.ncbi.nlm.nih.gov/pubmed/35458824
http://dx.doi.org/10.3390/s22082839
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author Frustaci, Fabio
Spagnolo, Fanny
Perri, Stefania
Cocorullo, Giuseppe
Corsonello, Pasquale
author_facet Frustaci, Fabio
Spagnolo, Fanny
Perri, Stefania
Cocorullo, Giuseppe
Corsonello, Pasquale
author_sort Frustaci, Fabio
collection PubMed
description This paper addresses the problem of automatic quality inspection in assembly processes by discussing the design of a computer vision system realized by means of a heterogeneous multiprocessor system-on-chip. Such an approach was applied to a real catalytic converter assembly process, to detect planar, translational, and rotational shifts of the flanges welded on the central body. The manufacturing line imposed tight time and room constraints. The image processing method and the features extraction algorithm, based on a specific geometrical model, are described and validated. The algorithm was developed to be highly modular, thus suitable to be implemented by adopting a hardware–software co-design strategy. The most timing consuming computational steps were identified and then implemented by dedicated hardware accelerators. The entire system was implemented on a Xilinx Zynq heterogeneous system-on-chip by using a hardware–software (HW–SW) co-design approach. The system is able to detect planar and rotational shifts of welded flanges, with respect to the ideal positions, with a maximum error lower than one millimeter and one sexagesimal degree, respectively. Remarkably, the proposed HW–SW approach achieves a 23× speed-up compared to the pure software solution running on the Zynq embedded processing system. Therefore, it allows an in-line automatic quality inspection to be performed without affecting the production time of the existing manufacturing process.
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spelling pubmed-90328902022-04-23 Robust and High-Performance Machine Vision System for Automatic Quality Inspection in Assembly Processes Frustaci, Fabio Spagnolo, Fanny Perri, Stefania Cocorullo, Giuseppe Corsonello, Pasquale Sensors (Basel) Article This paper addresses the problem of automatic quality inspection in assembly processes by discussing the design of a computer vision system realized by means of a heterogeneous multiprocessor system-on-chip. Such an approach was applied to a real catalytic converter assembly process, to detect planar, translational, and rotational shifts of the flanges welded on the central body. The manufacturing line imposed tight time and room constraints. The image processing method and the features extraction algorithm, based on a specific geometrical model, are described and validated. The algorithm was developed to be highly modular, thus suitable to be implemented by adopting a hardware–software co-design strategy. The most timing consuming computational steps were identified and then implemented by dedicated hardware accelerators. The entire system was implemented on a Xilinx Zynq heterogeneous system-on-chip by using a hardware–software (HW–SW) co-design approach. The system is able to detect planar and rotational shifts of welded flanges, with respect to the ideal positions, with a maximum error lower than one millimeter and one sexagesimal degree, respectively. Remarkably, the proposed HW–SW approach achieves a 23× speed-up compared to the pure software solution running on the Zynq embedded processing system. Therefore, it allows an in-line automatic quality inspection to be performed without affecting the production time of the existing manufacturing process. MDPI 2022-04-07 /pmc/articles/PMC9032890/ /pubmed/35458824 http://dx.doi.org/10.3390/s22082839 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Frustaci, Fabio
Spagnolo, Fanny
Perri, Stefania
Cocorullo, Giuseppe
Corsonello, Pasquale
Robust and High-Performance Machine Vision System for Automatic Quality Inspection in Assembly Processes
title Robust and High-Performance Machine Vision System for Automatic Quality Inspection in Assembly Processes
title_full Robust and High-Performance Machine Vision System for Automatic Quality Inspection in Assembly Processes
title_fullStr Robust and High-Performance Machine Vision System for Automatic Quality Inspection in Assembly Processes
title_full_unstemmed Robust and High-Performance Machine Vision System for Automatic Quality Inspection in Assembly Processes
title_short Robust and High-Performance Machine Vision System for Automatic Quality Inspection in Assembly Processes
title_sort robust and high-performance machine vision system for automatic quality inspection in assembly processes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9032890/
https://www.ncbi.nlm.nih.gov/pubmed/35458824
http://dx.doi.org/10.3390/s22082839
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