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Multi‑domain multi‑body digital twin model of a five‑cylinder pump and its application
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Xin ZHANG1, Zhiliang LIU1, Chenyang WANG1, Chuan XIE2, Meng RAO3, Mingjian ZUO1, 3
Fluid Machinery | 2026, 54(6) : 112 - 122
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Fluid Machinery | 2026, 54(6): 112-122
Multi‑domain multi‑body digital twin model of a five‑cylinder pump and its application
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Xin ZHANG1, Zhiliang LIU1, Chenyang WANG1, Chuan XIE2, Meng RAO3, Mingjian ZUO1, 3
Affiliations
  • 1School of Mechanical and Electrical Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China
  • 2School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China
  • 3Qingdao Mingserve Technology Ltd.,Qingdao 266041,China
Published: 2026-06-30 doi: 10.3969/j.issn.1005-0329.2026.06.014
Outline
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To address the issues in traditional data‑driven fault diagnosis methods for five‑cylinder pumps,such as difficulty in obtaining fault data,insufficient diagnostic capability during the early stage of equipment operation,and poor model generalization,a multi‑domain digital twin model of the five‑cylinder pump was established.The motor system,control system,mechanical system,and hydraulic system of the five‑cylinder pump were modeled,the mathematical models and parameter transfer relationships of each subsystem were clarified,and the overall model was consequently constructed.Based on fault mechanism analysis,the injection and response quantitative analysis of four typical faults,namely piston leakage,inlet blockage,bearing damage,and motor open circuit,were realized.A multi‑domain simulation model coupled with electromechanical‑hydraulic‑control was built using MATLAB/Simscape to obtain simulation data after fault injection.The consistency of the digital twin model was verified using experimental data from the XZQ2200 drilling pump.To demonstrate the application of the model,a drilling rig circulation system model was constructed using the five‑cylinder pump digital twin model,and a TimesNet‑based fault diagnosis method was proposed.The results show that the root mean square error between the twin data and the measured data is 0.039 2.The fault diagnosis model achieves a fault location classification accuracy of 98.33% and a fault classification accuracy of 89.44% on the twin dataset.The established five‑cylinder pump digital twin model has high fidelity and can effectively support typical fault mechanism analysis and fault diagnosis model construction.This study provides a new technical approach for predictive maintenance of complex equipment.

five‑cylinder pump  /  digital twin  /  fault injection  /  fault diagnosis  /  drilling rig
张鑫, 刘志亮, 王晨阳, 谢川, 饶猛, 左明健. 五缸泵多领域多体数字孪生模型及其应用. 流体机械, 2026 , 54 (6) : 112 -122 . DOI: 10.3969/j.issn.1005-0329.2026.06.014
Xin ZHANG, Zhiliang LIU, Chenyang WANG, Chuan XIE, Meng RAO, Mingjian ZUO. Multi‑domain multi‑body digital twin model of a five‑cylinder pump and its application[J]. Fluid Machinery, 2026 , 54 (6) : 112 -122 . DOI: 10.3969/j.issn.1005-0329.2026.06.014
Year 2026 volume 54 Issue 6
73
25
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Article Info
doi: 10.3969/j.issn.1005-0329.2026.06.014
  • Receive Date:2025-11-27
  • Online Date:2026-10-22
  • Published:2026-06-30
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History
  • Received:2025-11-27
  • Revised:2026-05-28
Affiliations
    1School of Mechanical and Electrical Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China
    2School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China
    3Qingdao Mingserve Technology Ltd.,Qingdao 266041,China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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