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Author:

Wang, S. (Wang, S..) | Wei, W. (Wei, W..) | Xie, J. (Xie, J..) | Wang, W. (Wang, W..) | Sun, Y. (Sun, Y..) | Li, Z. (Li, Z..) | Lin, Y. (Lin, Y..) | Huang, C. (Huang, C..) | Deng, S. (Deng, S..)

Indexed by:

EI Scopus SCIE

Abstract:

In practice, owing to the unreasonable defrosting initiating method of air source heat pumps (ASHPs), mal–defrost occurs frequently, further leading to the increase of building heating energy consumption. In recent years, with the development of image recognition technology in many fields, it has been expected to be used in defrosting initiating control methods of ASHPs. Although former investigations demonstrate that it is feasible and promising, there is still lack of a control strategy to make it become reality. To promote the application of image recognition in defrosting initiating method of ASHPs, a control strategy for the defrosting initiating method based on image gray recognition was proposed in the present work and used in an image gray recognition equipment (IGRE). Then, nine groups of experiments were conducted based on this new IGRE method. Results indicate that the proposed control strategy for the IGRE method is feasible and practical. By employing this new IGRE method, the defrosting accuracy rate and the average COP of the ASHPs are respectively 42.86% and 36.60% higher, compared with those using the conventional T–T method. In complex and variable environments, the defrosting accuracy rate of this new IGRE method reaches 93.33% in a 10–day test. © 2023 Elsevier Ltd

Keyword:

Building heating energy consumption Defrosting initiating control Image recognition Air source heat pumps Defrosting accuracy rate

Author Community:

  • [ 1 ] [Wang S.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Wei W.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Xie J.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 4 ] [Wang W.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 5 ] [Wang W.]School of Safety Engineering, Beijing Institute of Petrochemical Technology, Beijing, 102627, China
  • [ 6 ] [Sun Y.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 7 ] [Li Z.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 8 ] [Lin Y.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 9 ] [Huang C.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 10 ] [Deng S.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 11 ] [Deng S.]Department of Mechanical and Industrial Engineering, Qatar University, P.O. Box 2713, Doha, Qatar

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Source :

Applied Thermal Engineering

ISSN: 1359-4311

Year: 2024

Volume: 236

6 . 4 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:3

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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