EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE
Autor(a) principal: | |
---|---|
Data de Publicação: | 2017 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000500887 |
Resumo: | ABSTRACT: This study aim to develop a system, called FANS-N, for evaluation the exhaust fans in the ventilation system of broiler facilities. The system is divided into: 1) Mechanical Structure - consisting of two stepper motors for positioning a anemometer sensor in the vertical and horizontal coordinates; 2) Electronic Interface - control of the anemometer positioning and record data of wind speed; 3) Control Programming Module – accountable for the cursor movement, measurement and record the wind speed data with the anemometer at predetermined points; and 4) Analysis Programming Module - responsible for the interpretation of wind speed values at each point. The software uses artificial neural networks (Multi-Layer Perceptron) for images analyses of data base. The output of neural network give to the user the following recommendations: "possible changing", "maintenance", "standard limit", and "within standard". The system was able to evaluate the exhaust fans, identify the failures and proposing solutions to farmers of a preventive diagnosis. |
id |
SBEA-1_3563b6a5050b8ad1ca10d2c882b71675 |
---|---|
oai_identifier_str |
oai:scielo:S0100-69162017000500887 |
network_acronym_str |
SBEA-1 |
network_name_str |
Engenharia Agrícola |
repository_id_str |
|
spelling |
EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSEbroilerneural networkventilation systemsair flowABSTRACT: This study aim to develop a system, called FANS-N, for evaluation the exhaust fans in the ventilation system of broiler facilities. The system is divided into: 1) Mechanical Structure - consisting of two stepper motors for positioning a anemometer sensor in the vertical and horizontal coordinates; 2) Electronic Interface - control of the anemometer positioning and record data of wind speed; 3) Control Programming Module – accountable for the cursor movement, measurement and record the wind speed data with the anemometer at predetermined points; and 4) Analysis Programming Module - responsible for the interpretation of wind speed values at each point. The software uses artificial neural networks (Multi-Layer Perceptron) for images analyses of data base. The output of neural network give to the user the following recommendations: "possible changing", "maintenance", "standard limit", and "within standard". The system was able to evaluate the exhaust fans, identify the failures and proposing solutions to farmers of a preventive diagnosis.Associação Brasileira de Engenharia Agrícola2017-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000500887Engenharia Agrícola v.37 n.5 2017reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v37n5p887-899/2017info:eu-repo/semantics/openAccessSilva,WagnerMoura,DaniellaCarvalho-Curi,ThaylaSeber,RogérioMassari,Julianaeng2017-09-18T00:00:00Zoai:scielo:S0100-69162017000500887Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2017-09-18T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE |
title |
EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE |
spellingShingle |
EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE Silva,Wagner broiler neural network ventilation systems air flow |
title_short |
EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE |
title_full |
EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE |
title_fullStr |
EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE |
title_full_unstemmed |
EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE |
title_sort |
EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE |
author |
Silva,Wagner |
author_facet |
Silva,Wagner Moura,Daniella Carvalho-Curi,Thayla Seber,Rogério Massari,Juliana |
author_role |
author |
author2 |
Moura,Daniella Carvalho-Curi,Thayla Seber,Rogério Massari,Juliana |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Silva,Wagner Moura,Daniella Carvalho-Curi,Thayla Seber,Rogério Massari,Juliana |
dc.subject.por.fl_str_mv |
broiler neural network ventilation systems air flow |
topic |
broiler neural network ventilation systems air flow |
description |
ABSTRACT: This study aim to develop a system, called FANS-N, for evaluation the exhaust fans in the ventilation system of broiler facilities. The system is divided into: 1) Mechanical Structure - consisting of two stepper motors for positioning a anemometer sensor in the vertical and horizontal coordinates; 2) Electronic Interface - control of the anemometer positioning and record data of wind speed; 3) Control Programming Module – accountable for the cursor movement, measurement and record the wind speed data with the anemometer at predetermined points; and 4) Analysis Programming Module - responsible for the interpretation of wind speed values at each point. The software uses artificial neural networks (Multi-Layer Perceptron) for images analyses of data base. The output of neural network give to the user the following recommendations: "possible changing", "maintenance", "standard limit", and "within standard". The system was able to evaluate the exhaust fans, identify the failures and proposing solutions to farmers of a preventive diagnosis. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-09-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000500887 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000500887 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-eng.agric.v37n5p887-899/2017 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
dc.source.none.fl_str_mv |
Engenharia Agrícola v.37 n.5 2017 reponame:Engenharia Agrícola instname:Associação Brasileira de Engenharia Agrícola (SBEA) instacron:SBEA |
instname_str |
Associação Brasileira de Engenharia Agrícola (SBEA) |
instacron_str |
SBEA |
institution |
SBEA |
reponame_str |
Engenharia Agrícola |
collection |
Engenharia Agrícola |
repository.name.fl_str_mv |
Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA) |
repository.mail.fl_str_mv |
revistasbea@sbea.org.br||sbea@sbea.org.br |
_version_ |
1752126273548713984 |