A Leakage Detection Method for a Vapor-Compression Refrigeration System Based on System Modeling
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A Leakage Detection Method for a Vapor-Compression Refrigeration System Based on System Modeling
Journal of RefrigerationVol. 47, Issue 5, Pages: 32-40(2026)
作者机构:
1.中国航空工业集团公司金城南京机电液压工程研究中心 南京 211106
2. 航空机电系统综合航空科技重点实验室 南京 211106
3. 浙江大学制冷与低温研究所 全省制冷与低温技术重点实验室 杭州 310027
作者简介:
Han Xiaohong, female, professor, Ph. D. supervisor, Institute of Refrigeration and Cryogenics, Zhejiang University, 86-571-87953944, E-mail: hanxh66@zju.edu.cn. Research fields: high heat flux cooling technologies (including heat pipe cooling, microchannel cooling, and immersion liquid cooling), immersion liquid cooling thermal management for power batteries, refrigerant replacement technologies, refrigerant leakage detection, recovery, and reuse.
基金信息:
National Natural Science Foundation of China(52076185)
Gao Zanjun,Jiang Ning,Kong Jiaqi,et al.A Leakage Detection Method for a Vapor-Compression Refrigeration System Based on System Modeling[J].Journal of Refrigeration,2026,47(05):32-40.
Gao Zanjun,Jiang Ning,Kong Jiaqi,et al.A Leakage Detection Method for a Vapor-Compression Refrigeration System Based on System Modeling[J].Journal of Refrigeration,2026,47(05):32-40.DOI: 10.12465/issn.0253-4339.20250822001.
A Leakage Detection Method for a Vapor-Compression Refrigeration System Based on System Modeling
Refrigerant leakage from a refrigeration system not only degrades the system performance and increases the energy consumption, but aggravates environmental hazards and safety risks because of the high global warming potential or flammability of many refrigerants. Therefore, fast and accurate methods are required to detect and rectify refrigerant leaks. This study focuses on a domestic air-conditioning refrigeration system with a cooling capacity of 3.5 kW. Using simulation methods, the dynamic evolution laws of the key node parameters of each component and the system performance parameters under different leakage rates are analyzed quantitatively. Based on the findings, a prediction model of refrigerant inventory is developed for the key components. This model, integrated with the operational data, provides a new leakage detection and diagnosis method based on system modeling. This method aims to evaluate the severity of leakage using a small amount of leakage data. The developed inventory prediction equation of refrigerant charge maintains the prediction uncertainty within ±5% when the leakage rate is below 12%.
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