Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.

The study is aimed at the frosting problem of the air source heat pump in the low temperature and high humidity environment, which reduces the service life of the system. First, the frosting characteristics at the evaporator side of the air source heat pump system are analyzed. Then, a new defrost t...

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Autores principales:	Bo Yu, Yuye Luo, Wenxiao Chu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1f8cadb07989466fa4caf09620c16c45
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spelling	oai:doaj.org-article:1f8cadb07989466fa4caf09620c16c452021-12-02T20:08:34ZAnalysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.1932-620310.1371/journal.pone.0256836https://doaj.org/article/1f8cadb07989466fa4caf09620c16c452021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0256836https://doaj.org/toc/1932-6203The study is aimed at the frosting problem of the air source heat pump in the low temperature and high humidity environment, which reduces the service life of the system. First, the frosting characteristics at the evaporator side of the air source heat pump system are analyzed. Then, a new defrost technology is proposed, and dimensional theory and neural network are combined to predict the transfer performance of the new system. Finally, an adaptive network control algorithm is proposed to predict the frosting amount. This algorithm optimizes the traditional neural network algorithm control process, and it is more flexible, objective, and reliable in the selection of the hidden layer, the acquisition of the optimal function, and the selection of the corresponding learning rate. Through model performance, regression analysis, and heat transfer characteristics simulation, the effectiveness of this method is further confirmed. It is found that, the new air source heat pump defrost system can provide auxiliary heat, effectively regulating the temperature and humidity. The mean square error is 0.019827, and the heat pump can operate efficiently under frosting conditions. The defrost system is easy to operate, and facilitates manufactures designing for different regions under different conditions. This research provides reference for energy conservation, emission reduction, and sustainable economic development.Bo YuYuye LuoWenxiao ChuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0256836 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bo Yu Yuye Luo Wenxiao Chu Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.
description	The study is aimed at the frosting problem of the air source heat pump in the low temperature and high humidity environment, which reduces the service life of the system. First, the frosting characteristics at the evaporator side of the air source heat pump system are analyzed. Then, a new defrost technology is proposed, and dimensional theory and neural network are combined to predict the transfer performance of the new system. Finally, an adaptive network control algorithm is proposed to predict the frosting amount. This algorithm optimizes the traditional neural network algorithm control process, and it is more flexible, objective, and reliable in the selection of the hidden layer, the acquisition of the optimal function, and the selection of the corresponding learning rate. Through model performance, regression analysis, and heat transfer characteristics simulation, the effectiveness of this method is further confirmed. It is found that, the new air source heat pump defrost system can provide auxiliary heat, effectively regulating the temperature and humidity. The mean square error is 0.019827, and the heat pump can operate efficiently under frosting conditions. The defrost system is easy to operate, and facilitates manufactures designing for different regions under different conditions. This research provides reference for energy conservation, emission reduction, and sustainable economic development.
format	article
author	Bo Yu Yuye Luo Wenxiao Chu
author_facet	Bo Yu Yuye Luo Wenxiao Chu
author_sort	Bo Yu
title	Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.
title_short	Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.
title_full	Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.
title_fullStr	Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.
title_full_unstemmed	Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.
title_sort	analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using bp neural network learning algorithm.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/1f8cadb07989466fa4caf09620c16c45
work_keys_str_mv	AT boyu analysisonfrostingofheatexchangerandnumericalsimulationofheattransfercharacteristicsusingbpneuralnetworklearningalgorithm AT yuyeluo analysisonfrostingofheatexchangerandnumericalsimulationofheattransfercharacteristicsusingbpneuralnetworklearningalgorithm AT wenxiaochu analysisonfrostingofheatexchangerandnumericalsimulationofheattransfercharacteristicsusingbpneuralnetworklearningalgorithm
_version_	1718375167318556672

Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.

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