Data-Model Fusion-Driven Method for Fault Quantitative Diagnosis of Heat Exchanger

Xiaogang Qin, Shiwei Yan, Haibo Xu, Yi Gao, Yanbing Yu and Jinjiang Wang ()
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Xiaogang Qin: CNOOC China Limited Beijing Research Center, Beijing 100028, China
Shiwei Yan: School of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China
Haibo Xu: CNOOC China Limited Beijing Research Center, Beijing 100028, China
Yi Gao: School of Safety and Ocean Engineering, China University of Petroleum, Beijing 102249, China
Yanbing Yu: Exploration and Development Department of CNOOC Limited, Beijing 100010, China
Jinjiang Wang: Key Laboratory of Oil and Gas Production Equipment Quality Inspection and Health Diagnosis, State Administration for Market Regulation, Beijing 100088, China

Energies, 2024, vol. 17, issue 23, 1-17

Abstract: Heat exchangers play essential roles in the oil and gas production process for convective heat transfer and heat conduction. The health management of heat exchangers stays in the direct monitoring of performance parameters. Aiming at the difficulty of precise fault identification and quantification for heat exchangers in multiple unknown failure modes, a data-model fusion-driven fault quantitative diagnosis method is proposed. Firstly, based on the monitoring data such as temperature, pressure and flow rate, the secondary parameters characterizing the heat exchanger running state are constructed combined with structural physical parameters. Then, by analyzing the correlation among parameter variation, failure modes and deterioration degree, a qualitative inference model of heat exchanger is formed for fault identification, where weights of parameters are introduced based on their sensitivity for different failure modes. After the fault mode is identified, to achieve quantitative analysis of the failure degree, an index-integrated mechanism equation is constructed using monitoring data and secondary parameters, where the index is dynamically modified by online data. Finally, a heat exchanger experiment is carried out to demonstrate the robustness and accuracy of the proposed method.

Keywords: heat exchanger; fault identification; fault quantitation index; data-model hybrid (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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