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Particle Swarm Optimisation in Practice: Multiple Applications in a Digital Microscope System

Louis Ryan, Stefan Kuhn Orcid Logo, Simon Colreavy-Donnely Orcid Logo, Fabio Caraffini Orcid Logo

Applied Sciences, Volume: 12, Issue: 15, Start page: 7827

Swansea University Author: Fabio Caraffini Orcid Logo

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DOI (Published version): 10.3390/app12157827

Abstract

We demonstrate that particle swarm optimisation (PSO) can be used to solve a variety of problems arising during operation of a digital inspection microscope. This is a use case for the feasibility of heuristics in a real-world product. We show solutions to four measurement problems, all based on PSO...

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Published in: Applied Sciences
ISSN: 2076-3417
Published: MDPI AG 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa60897
first_indexed 2022-09-23T11:38:37Z
last_indexed 2023-01-13T19:21:22Z
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spelling 2022-09-23T12:40:37.0437784 v2 60897 2022-08-28 Particle Swarm Optimisation in Practice: Multiple Applications in a Digital Microscope System d0b8d4e63d512d4d67a02a23dd20dfdb 0000-0001-9199-7368 Fabio Caraffini Fabio Caraffini true false 2022-08-28 MACS We demonstrate that particle swarm optimisation (PSO) can be used to solve a variety of problems arising during operation of a digital inspection microscope. This is a use case for the feasibility of heuristics in a real-world product. We show solutions to four measurement problems, all based on PSO. This allows for a compact software implementation solving different problems. We have found that PSO can solve a variety of problems with small software footprints and good results in a real-world embedded system. Notably, in the microscope application, this eliminates the need to return the device to the factory for calibration. Journal Article Applied Sciences 12 15 7827 MDPI AG 2076-3417 digital microscope; inspection system; metrology; particle swarm optimisation; heuristics; image stitching 4 8 2022 2022-08-04 10.3390/app12157827 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University This research received no external funding. 2022-09-23T12:40:37.0437784 2022-08-28T18:49:52.2033245 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Louis Ryan 1 Stefan Kuhn 0000-0002-5990-4157 2 Simon Colreavy-Donnely 0000-0002-1795-6995 3 Fabio Caraffini 0000-0001-9199-7368 4 60897__25201__6cc5294afa4a445fa78d3523ac06f00b.pdf 60897_VoR.pdf 2022-09-23T12:39:10.2542539 Output 9131604 application/pdf Version of Record true © 2022 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license true eng https://creativecommons.org/licenses/by/4.0/
title Particle Swarm Optimisation in Practice: Multiple Applications in a Digital Microscope System
spellingShingle Particle Swarm Optimisation in Practice: Multiple Applications in a Digital Microscope System
Fabio Caraffini
title_short Particle Swarm Optimisation in Practice: Multiple Applications in a Digital Microscope System
title_full Particle Swarm Optimisation in Practice: Multiple Applications in a Digital Microscope System
title_fullStr Particle Swarm Optimisation in Practice: Multiple Applications in a Digital Microscope System
title_full_unstemmed Particle Swarm Optimisation in Practice: Multiple Applications in a Digital Microscope System
title_sort Particle Swarm Optimisation in Practice: Multiple Applications in a Digital Microscope System
author_id_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb
author_id_fullname_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb_***_Fabio Caraffini
author Fabio Caraffini
author2 Louis Ryan
Stefan Kuhn
Simon Colreavy-Donnely
Fabio Caraffini
format Journal article
container_title Applied Sciences
container_volume 12
container_issue 15
container_start_page 7827
publishDate 2022
institution Swansea University
issn 2076-3417
doi_str_mv 10.3390/app12157827
publisher MDPI AG
college_str Faculty of Science and Engineering
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hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
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description We demonstrate that particle swarm optimisation (PSO) can be used to solve a variety of problems arising during operation of a digital inspection microscope. This is a use case for the feasibility of heuristics in a real-world product. We show solutions to four measurement problems, all based on PSO. This allows for a compact software implementation solving different problems. We have found that PSO can solve a variety of problems with small software footprints and good results in a real-world embedded system. Notably, in the microscope application, this eliminates the need to return the device to the factory for calibration.
published_date 2022-08-04T14:17:35Z
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score 11.048042

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