Fault Diagnosis of Chillers Based on Neural Network and Wavelet Denoising
Chiller fault detection based on neural network is a data-based analysis method. The fault detection efficiency relies on the quality of the training data and the mesasured data.The wavelet transfer method which can remove the measurement nosise is used to improve the detection efficiencies of chil...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Journal of Refrigeration Magazines Agency Co., Ltd.
2016-01-01
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| Series: | Zhileng xuebao |
| Subjects: | |
| Online Access: | http://www.zhilengxuebao.com/thesisDetails#10.3969/j.issn.0253-4339.2016.01.012 |
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| _version_ | 1850232844482248704 |
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| author | Shi Shubiao Chen Huanxin Li Guannan Hu Yunpeng Li Haorong Hu Wenju |
| author_facet | Shi Shubiao Chen Huanxin Li Guannan Hu Yunpeng Li Haorong Hu Wenju |
| author_sort | Shi Shubiao |
| collection | DOAJ |
| description | Chiller fault detection based on neural network is a data-based analysis method. The fault detection efficiency relies on the quality of the training data and the mesasured data.The wavelet transfer method which can remove the measurement nosise is used to improve the detection efficiencies of chiller.The results show that wavelet transfer make the detection efficiencies of fault level improved, especially the first level. The increase of the first level detection rate will be able to timely identify the chiller fault, and take the measures to prevent further deterioration of chiller fault, which is of important significance to reduce energy consumption and improve the reliability of the air-conditioning system and ensure the indoor thermal comfort. The FDD (fault detection and diagnosis）strategy is validated through using ASHRAE Project data, which shows that the detection rate is improved obviously. |
| format | Article |
| id | doaj-art-3aceb99080f243ebbebe29468dbadf1f |
| institution | OA Journals |
| issn | 0253-4339 |
| language | zho |
| publishDate | 2016-01-01 |
| publisher | Journal of Refrigeration Magazines Agency Co., Ltd. |
| record_format | Article |
| series | Zhileng xuebao |
| spelling | doaj-art-3aceb99080f243ebbebe29468dbadf1f2025-08-20T02:03:04ZzhoJournal of Refrigeration Magazines Agency Co., Ltd.Zhileng xuebao0253-43392016-01-013766513589Fault Diagnosis of Chillers Based on Neural Network and Wavelet DenoisingShi ShubiaoChen HuanxinLi GuannanHu YunpengLi HaorongHu WenjuChiller fault detection based on neural network is a data-based analysis method. The fault detection efficiency relies on the quality of the training data and the mesasured data.The wavelet transfer method which can remove the measurement nosise is used to improve the detection efficiencies of chiller.The results show that wavelet transfer make the detection efficiencies of fault level improved, especially the first level. The increase of the first level detection rate will be able to timely identify the chiller fault, and take the measures to prevent further deterioration of chiller fault, which is of important significance to reduce energy consumption and improve the reliability of the air-conditioning system and ensure the indoor thermal comfort. The FDD (fault detection and diagnosis）strategy is validated through using ASHRAE Project data, which shows that the detection rate is improved obviously.http://www.zhilengxuebao.com/thesisDetails#10.3969/j.issn.0253-4339.2016.01.012chillerfault detection and diagnosisBP neural networkwavelet denoisingbayesian regularization |
| spellingShingle | Shi Shubiao Chen Huanxin Li Guannan Hu Yunpeng Li Haorong Hu Wenju Fault Diagnosis of Chillers Based on Neural Network and Wavelet Denoising Zhileng xuebao chiller fault detection and diagnosis BP neural network wavelet denoising bayesian regularization |
| title | Fault Diagnosis of Chillers Based on Neural Network and Wavelet Denoising |
| title_full | Fault Diagnosis of Chillers Based on Neural Network and Wavelet Denoising |
| title_fullStr | Fault Diagnosis of Chillers Based on Neural Network and Wavelet Denoising |
| title_full_unstemmed | Fault Diagnosis of Chillers Based on Neural Network and Wavelet Denoising |
| title_short | Fault Diagnosis of Chillers Based on Neural Network and Wavelet Denoising |
| title_sort | fault diagnosis of chillers based on neural network and wavelet denoising |
| topic | chiller fault detection and diagnosis BP neural network wavelet denoising bayesian regularization |
| url | http://www.zhilengxuebao.com/thesisDetails#10.3969/j.issn.0253-4339.2016.01.012 |
| work_keys_str_mv | AT shishubiao faultdiagnosisofchillersbasedonneuralnetworkandwaveletdenoising AT chenhuanxin faultdiagnosisofchillersbasedonneuralnetworkandwaveletdenoising AT liguannan faultdiagnosisofchillersbasedonneuralnetworkandwaveletdenoising AT huyunpeng faultdiagnosisofchillersbasedonneuralnetworkandwaveletdenoising AT lihaorong faultdiagnosisofchillersbasedonneuralnetworkandwaveletdenoising AT huwenju faultdiagnosisofchillersbasedonneuralnetworkandwaveletdenoising |