Research on fault detection method for heat pump air conditioning system under cold weather

doi:10.1016/j.cjche.2017.06.009

Chinese Journal of Chemical Engineering ›› 2017, Vol. 25 ›› Issue (12): 1812-1819.DOI: 10.1016/j.cjche.2017.06.009

• 第25届中国过程控制会议专栏 • 上一篇下一篇

Research on fault detection method for heat pump air conditioning system under cold weather

Liangliang Sun^1,2, Jianghua Wu¹, Haiqi Jia¹, Xuebin Liu¹

1. Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China;
2. Electrical Engineering, University of Connecticut, Storrs 06269, USA

收稿日期:2016-11-14 修回日期:2017-04-07 出版日期:2017-12-28 发布日期:2018-01-18
通讯作者: Liangliang Sun,E-mail address:sunliangliang@sjzu.edu.cn.
基金资助:
Supported by the National Natural Science Foundation Committee of China (61503259), China Postdoctoral Science Foundation Funded Project (2017M611261), Chinese Scholarship Council (201608210107) and Hanyu Plan of Shenyang Jianzhu University (XKHY2-64).

Research on fault detection method for heat pump air conditioning system under cold weather

Liangliang Sun^1,2, Jianghua Wu¹, Haiqi Jia¹, Xuebin Liu¹

1. Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China;
2. Electrical Engineering, University of Connecticut, Storrs 06269, USA

Received:2016-11-14 Revised:2017-04-07 Online:2017-12-28 Published:2018-01-18
Contact: Liangliang Sun,E-mail address:sunliangliang@sjzu.edu.cn.
Supported by:
Supported by the National Natural Science Foundation Committee of China (61503259), China Postdoctoral Science Foundation Funded Project (2017M611261), Chinese Scholarship Council (201608210107) and Hanyu Plan of Shenyang Jianzhu University (XKHY2-64).

摘要/Abstract

摘要： Building energy consumption accounts for nearly 40% of global energy consumption, HVAC (Heating, Ventilating, and Air Conditioning) systems are the major building energy consumers, and as one type of HVAC systems, the heat pump air conditioning system, which is more energy-efficient compared to the traditional air conditioning system, is being more widely used to save energy. However, in northern China, extreme climatic conditions increase the cooling and heating load of the heat pump air conditioning system and accelerate the aging of the equipment, and the sensor may detect drifted parameters owing to climate change. This non-linear drifted parameter increases the false alarm rate of the fault detection and the need for unnecessary troubleshooting. In order to overcome the impact of the device aging and the drifted parameter, a Kalman filter and SPC (statistical process control) fault detection method are introduced in this paper. In thismethod, themodel parameter and its standard variance can be estimated by Kalman filter based on the gray model and the real-time data of the air conditioning system. Further, by using SPC to construct the dynamic control limits, false alarm rate is reduced. And this paper mainly focuses on the cold machine failure in the component failure and its soft fault detection. This approach has been tested on a simulation model of the “Sino-German Energy Conservation Demonstration Center” building heat pump air-conditioning system in Shenyang, China, and the results show that the Kalman filter and SPC fault detection method is simple and highly efficient with a low false alarm rate, and it can deal with the difficulties caused by the extreme environment and the non-linear influence of the parameters, and what's more, it provides a good foundation for dynamic fault diagnosis and fault prediction analysis.

关键词: Fault detection, Cold machine, Kalman filter, Statistical process control, Dynamic control

Abstract: Building energy consumption accounts for nearly 40% of global energy consumption, HVAC (Heating, Ventilating, and Air Conditioning) systems are the major building energy consumers, and as one type of HVAC systems, the heat pump air conditioning system, which is more energy-efficient compared to the traditional air conditioning system, is being more widely used to save energy. However, in northern China, extreme climatic conditions increase the cooling and heating load of the heat pump air conditioning system and accelerate the aging of the equipment, and the sensor may detect drifted parameters owing to climate change. This non-linear drifted parameter increases the false alarm rate of the fault detection and the need for unnecessary troubleshooting. In order to overcome the impact of the device aging and the drifted parameter, a Kalman filter and SPC (statistical process control) fault detection method are introduced in this paper. In thismethod, themodel parameter and its standard variance can be estimated by Kalman filter based on the gray model and the real-time data of the air conditioning system. Further, by using SPC to construct the dynamic control limits, false alarm rate is reduced. And this paper mainly focuses on the cold machine failure in the component failure and its soft fault detection. This approach has been tested on a simulation model of the “Sino-German Energy Conservation Demonstration Center” building heat pump air-conditioning system in Shenyang, China, and the results show that the Kalman filter and SPC fault detection method is simple and highly efficient with a low false alarm rate, and it can deal with the difficulties caused by the extreme environment and the non-linear influence of the parameters, and what's more, it provides a good foundation for dynamic fault diagnosis and fault prediction analysis.

Key words: Fault detection, Cold machine, Kalman filter, Statistical process control, Dynamic control

Liangliang Sun, Jianghua Wu, Haiqi Jia, Xuebin Liu. Research on fault detection method for heat pump air conditioning system under cold weather[J]. Chinese Journal of Chemical Engineering, 2017, 25(12): 1812-1819.

Liangliang Sun, Jianghua Wu, Haiqi Jia, Xuebin Liu. Research on fault detection method for heat pump air conditioning system under cold weather[J]. Chin.J.Chem.Eng., 2017, 25(12): 1812-1819.

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Research on fault detection method for heat pump air conditioning system under cold weather

Research on fault detection method for heat pump air conditioning system under cold weather

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