Image recognition method for frost sensing applications
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.6/12115 |
Resumo: | Frost formation in the heat exchangers of refrigeration systems is a well-documented phenomenon. This frost accumulation creates a thermally insulating barrier that can restrict, or even block, the airflow between fins, resulting in decreased efficiency and degradation of the food products. Several methods of frost detection and defrosting have been developed, although there is not an efficient mainstream method to measure and control frost formation. In previous works, the results of a small low-cost resistive sensor for frost detection were shown to be promising. This paper extends that research using computer vision to compare the results of this sensor with the frost formed on the heat exchanger, allowing for a better study of the sensor. This method allowed to trace and plot a frost formation curve of the sensor detected values. |
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Image recognition method for frost sensing applicationsComputer VisionDefrostingFrost FormationFrost sensingRefrigerationFrost formation in the heat exchangers of refrigeration systems is a well-documented phenomenon. This frost accumulation creates a thermally insulating barrier that can restrict, or even block, the airflow between fins, resulting in decreased efficiency and degradation of the food products. Several methods of frost detection and defrosting have been developed, although there is not an efficient mainstream method to measure and control frost formation. In previous works, the results of a small low-cost resistive sensor for frost detection were shown to be promising. This paper extends that research using computer vision to compare the results of this sensor with the frost formed on the heat exchanger, allowing for a better study of the sensor. This method allowed to trace and plot a frost formation curve of the sensor detected values.This work has been supported by the project Centro-01-0145-FEDER000017 -EMaDeS -Energy, Materials and Sustainable Development, co-funded by the Portugal 2020 Program (PT 2020), within the Regional Operational Program of the Center (CENTRO 2020) and the EU through the European Regional Development Fund (ERDF). The authors thank the opportunity and financial support to carry on this project to Fundac¸ao para a Ci ˜ encia e ˆ Tecnologia (FCT) and R&D Unit “Centre for Mechanical and Aerospace Science and Technologies” (C-MAST), under project UIDB/00151/2020. This study is within the activities of project “PrunusPos - Optimization of processes for the storage, cold ´ conservation, active and/or intelligent packaging and food quality traceability in post-harvested fruit products”, project n. ◦ PDR2020-101-031695, Partnership n◦ 87, initiative n.◦ 175, promoted by PDR 2020 and co-funded by EAFRD within Portugal 2020.uBibliorumAguiar, MartimGaspar, Pedro DinisSilva, Pedro Dinho da2022-03-25T16:36:36Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.6/12115eng10.1016/j.egyr.2022.01.049info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-15T09:54:58Zoai:ubibliorum.ubi.pt:10400.6/12115Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:51:47.414270Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Image recognition method for frost sensing applications |
title |
Image recognition method for frost sensing applications |
spellingShingle |
Image recognition method for frost sensing applications Aguiar, Martim Computer Vision Defrosting Frost Formation Frost sensing Refrigeration |
title_short |
Image recognition method for frost sensing applications |
title_full |
Image recognition method for frost sensing applications |
title_fullStr |
Image recognition method for frost sensing applications |
title_full_unstemmed |
Image recognition method for frost sensing applications |
title_sort |
Image recognition method for frost sensing applications |
author |
Aguiar, Martim |
author_facet |
Aguiar, Martim Gaspar, Pedro Dinis Silva, Pedro Dinho da |
author_role |
author |
author2 |
Gaspar, Pedro Dinis Silva, Pedro Dinho da |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
uBibliorum |
dc.contributor.author.fl_str_mv |
Aguiar, Martim Gaspar, Pedro Dinis Silva, Pedro Dinho da |
dc.subject.por.fl_str_mv |
Computer Vision Defrosting Frost Formation Frost sensing Refrigeration |
topic |
Computer Vision Defrosting Frost Formation Frost sensing Refrigeration |
description |
Frost formation in the heat exchangers of refrigeration systems is a well-documented phenomenon. This frost accumulation creates a thermally insulating barrier that can restrict, or even block, the airflow between fins, resulting in decreased efficiency and degradation of the food products. Several methods of frost detection and defrosting have been developed, although there is not an efficient mainstream method to measure and control frost formation. In previous works, the results of a small low-cost resistive sensor for frost detection were shown to be promising. This paper extends that research using computer vision to compare the results of this sensor with the frost formed on the heat exchanger, allowing for a better study of the sensor. This method allowed to trace and plot a frost formation curve of the sensor detected values. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-03-25T16:36:36Z 2022 2022-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.6/12115 |
url |
http://hdl.handle.net/10400.6/12115 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.egyr.2022.01.049 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799136406578135040 |