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Fault Diagnosis Method of Centrifugal Pump Based on Siamese Networks under Small Sample Conditions
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Ke LI1, 2, Lai-bin ZHANG1, 2, Li-xiang DUAN1, 2, *, Hai-peng LIU3, Xin-yue ZHANG1, 2
Science Technology and Engineering | 2025, 25(11) : 4543 - 4550
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Science Technology and Engineering | 2025, 25(11): 4543-4550
• Papers·Mechanical and Instrumental Industry •
Fault Diagnosis Method of Centrifugal Pump Based on Siamese Networks under Small Sample Conditions
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Ke LI1, 2, Lai-bin ZHANG1, 2, Li-xiang DUAN1, 2, *, Hai-peng LIU3, Xin-yue ZHANG1, 2
Affiliations
  • 1 College of Safety and Ocean Engineering, China University of Petroleum(Beijing), Beijing 102249, China
  • 2 Key Laboratory of Oil and Gas Production Safety and Emergency Technology, Ministry of Emergency Management, Beijing 102249, China
  • 3 China National Petroleum International Pipeline Co., Ltd., Beijing 102206, China
Published: 2025-04-18 doi: 10.12404/j.issn.1671-1815.2403506
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Conventional diagnostic methods that require a large amount of data support in practical engineering are difficult to effectively perform centrifugal pump fault diagnosis under small sample conditions. Therefore, the residual network (ResNet) in deep learning was combined with dilated convolution and extended into a siamese network to construct a dilated residual siamese network (DRSN). The dilated residual network was used as the feature extraction module of the siamese network, which enhanced the feature extraction ability of the model. Positive and negative sample pairs were constructed to extract more information from each sample, and make more effective use of limited data.The two sub-networks share parameters, the number of free parameters and lowering the risk of overfitting was reduced when the sample was insufficient. The proposed network model alleviated the problem of insufficient training samples, improved the efficiency of data utilization, and realized the fault classification of centrifugal pump under the condition of small samples. The research results show that even in the most sample-scarce situation, the accuracy of the model on the centrifugal pump test dataset can still reach 82.20%, which is at least 8.8 percentage points higher than other models.

centrifugal pump  /  fault diagnosis  /  small sample  /  residual network  /  siamese network
Ke LI, Lai-bin ZHANG, Li-xiang DUAN, Hai-peng LIU, Xin-yue ZHANG. Fault Diagnosis Method of Centrifugal Pump Based on Siamese Networks under Small Sample Conditions[J]. Science Technology and Engineering, 2025 , 25 (11) : 4543 -4550 . DOI: 10.12404/j.issn.1671-1815.2403506
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Year 2025 volume 25 Issue 11
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Article Info
doi: 10.12404/j.issn.1671-1815.2403506
  • Receive Date：2024-05-12
  • Online Date：2025-07-09
  • Published：2025-04-18
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History
  • Received：2024-05-12
  • Revised：2024-08-10
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Affiliations
    1 College of Safety and Ocean Engineering, China University of Petroleum(Beijing), Beijing 102249, China
    2 Key Laboratory of Oil and Gas Production Safety and Emergency Technology, Ministry of Emergency Management, Beijing 102249, China
    3 China National Petroleum International Pipeline Co., Ltd., Beijing 102206, China
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