Interpretability Study on the Fault Diagnosis Model of the Heat pipe/ Vapor Compression Composite Air Conditioning System
Applying data-driven fault diagnosis models to data center air conditioning systems can significantly improve operational reliability. However, such models often lack diagnostic interpretability, limiting their application. This study develops a composite fault diagnosis model based on typical machi...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | Chinese |
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Journal of Refrigeration Magazines Agency Co., Ltd.
2025-01-01
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| Series: | Zhileng xuebao |
| Subjects: | |
| Online Access: | http://www.zhilengxuebao.com/zh/article/117507343/ |
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| author | ZHANG Yiqi HUANG Shuoquan LI Xiuming DI Yanqiang SONG Mengjie HAN Zongwei |
| author_facet | ZHANG Yiqi HUANG Shuoquan LI Xiuming DI Yanqiang SONG Mengjie HAN Zongwei |
| author_sort | ZHANG Yiqi |
| collection | DOAJ |
| description | Applying data-driven fault diagnosis models to data center air conditioning systems can significantly improve operational reliability. However, such models often lack diagnostic interpretability, limiting their application. This study develops a composite fault diagnosis model based on typical machine learning algorithms, compares the diagnostic performance of different models, and finally conducts interpretability research on the diagnostic models using the SHAP method. The results demonstrate that the CNN-based fault diagnosis model achieves optimal performance in both heat pipe and vapor compression modes, with F-1 scores exceeding 0.999 across all classifications. In heat pipe mode, the diagnosis of CNN model primarily relies on condenser fan frequency, outdoor temperature, and refrigerant pump power consumption as key features, whereas in vapor compression mode, the dominant features are outdoor temperature, compressor frequency, and subcooling degree. |
| format | Article |
| id | doaj-art-2f3287f8cca64d928e1036a6a387155c |
| institution | Matheson Library |
| issn | 0253-4339 |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | Journal of Refrigeration Magazines Agency Co., Ltd. |
| record_format | Article |
| series | Zhileng xuebao |
| spelling | doaj-art-2f3287f8cca64d928e1036a6a387155c2025-07-26T19:00:26ZzhoJournal of Refrigeration Magazines Agency Co., Ltd.Zhileng xuebao0253-43392025-01-01117507343Interpretability Study on the Fault Diagnosis Model of the Heat pipe/ Vapor Compression Composite Air Conditioning SystemZHANG YiqiHUANG ShuoquanLI XiumingDI YanqiangSONG MengjieHAN ZongweiApplying data-driven fault diagnosis models to data center air conditioning systems can significantly improve operational reliability. However, such models often lack diagnostic interpretability, limiting their application. This study develops a composite fault diagnosis model based on typical machine learning algorithms, compares the diagnostic performance of different models, and finally conducts interpretability research on the diagnostic models using the SHAP method. The results demonstrate that the CNN-based fault diagnosis model achieves optimal performance in both heat pipe and vapor compression modes, with F-1 scores exceeding 0.999 across all classifications. In heat pipe mode, the diagnosis of CNN model primarily relies on condenser fan frequency, outdoor temperature, and refrigerant pump power consumption as key features, whereas in vapor compression mode, the dominant features are outdoor temperature, compressor frequency, and subcooling degree.http://www.zhilengxuebao.com/zh/article/117507343/data centercomposite air conditioning systemfault diagnosisinterpretability study |
| spellingShingle | ZHANG Yiqi HUANG Shuoquan LI Xiuming DI Yanqiang SONG Mengjie HAN Zongwei Interpretability Study on the Fault Diagnosis Model of the Heat pipe/ Vapor Compression Composite Air Conditioning System Zhileng xuebao data center composite air conditioning system fault diagnosis interpretability study |
| title | Interpretability Study on the Fault Diagnosis Model of the Heat pipe/ Vapor Compression Composite Air Conditioning System |
| title_full | Interpretability Study on the Fault Diagnosis Model of the Heat pipe/ Vapor Compression Composite Air Conditioning System |
| title_fullStr | Interpretability Study on the Fault Diagnosis Model of the Heat pipe/ Vapor Compression Composite Air Conditioning System |
| title_full_unstemmed | Interpretability Study on the Fault Diagnosis Model of the Heat pipe/ Vapor Compression Composite Air Conditioning System |
| title_short | Interpretability Study on the Fault Diagnosis Model of the Heat pipe/ Vapor Compression Composite Air Conditioning System |
| title_sort | interpretability study on the fault diagnosis model of the heat pipe vapor compression composite air conditioning system |
| topic | data center composite air conditioning system fault diagnosis interpretability study |
| url | http://www.zhilengxuebao.com/zh/article/117507343/ |
| work_keys_str_mv | AT zhangyiqi interpretabilitystudyonthefaultdiagnosismodeloftheheatpipevaporcompressioncompositeairconditioningsystem AT huangshuoquan interpretabilitystudyonthefaultdiagnosismodeloftheheatpipevaporcompressioncompositeairconditioningsystem AT lixiuming interpretabilitystudyonthefaultdiagnosismodeloftheheatpipevaporcompressioncompositeairconditioningsystem AT diyanqiang interpretabilitystudyonthefaultdiagnosismodeloftheheatpipevaporcompressioncompositeairconditioningsystem AT songmengjie interpretabilitystudyonthefaultdiagnosismodeloftheheatpipevaporcompressioncompositeairconditioningsystem AT hanzongwei interpretabilitystudyonthefaultdiagnosismodeloftheheatpipevaporcompressioncompositeairconditioningsystem |