Deep learning-based fault diagnosis of variable refrigerant flow air-conditioning system for building energy saving-Reference-Cited by-同舟云学术

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Deep learning-based fault diagnosis of variable refrigerant flow air-conditioning system for building energy saving

Published:2018-09 Issue: Volume:225 Page:732-745
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Guo Yabin,Tan Zehan,Chen Huanxin,Li Guannan,Wang Jiangyu,Huang Ronggeng,Liu Jiangyan,Ahmad Tanveer

Funder

National Natural Science Foundation of China

State Key Laboratory of Air-Conditioning Equipment and System Energy Conservation

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference60 articles.

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2. Thermal comfort and building energy consumption implications – a review;Yang;Appl Energy,2014

3. Comparative study of the cooling energy performance of variable refrigerant flow systems and variable air volume systems in office buildings;Yu;Appl Energy,2016

4. National Energy Board press conference; 2017. .

5. Use of the infrared data for heating curve computation in induction motors: application to fault diagnosis;Picazo-Rodenas;Eng Fail Anal,2013

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