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Journal of System Simulation

Abstract

Abstract: In response to the high cost and long cycle of using experimental methods for monitoring, diagnosing, and predicting lubricating oil system, a simulation model for oil system is constructed and optimized, and the application of the model in health management of oil system is proposed. Based on the physical characteristics of the components in the oil system, subsystem models for ventilation, oil supply, thermodynamics, and oil return are constructed using a certain engine oil system as an example, and the whole oil system model is constructed and solved iteratively. The model is optimized by combining particle swarm optimization and genetic algorithm. The comparative optimization results show that the particle swarm algorithm has good convergence and optimization effect. The average error of the working parameters of the oil system under different typical working conditions is reduced from more than 10% to about 2%, indicating a certain degree of accuracy. Based on the scalability of the model and combined with the requirements of health management in the oil system, the application of the model in oil monitoring, diagnosis, prediction, and other aspects is analyzed to provide support for the health management of the oil system.

First Page

1266

Last Page

1279

CLC

V233.4

Recommended Citation

Huang Shijie, Zhang Zhensheng, Cai Jing, et al. Research on Modeling, Optimization and Application of Aeroengine Oil System[J]. Journal of System Simulation, 2025, 37(5): 1266-1279.

Corresponding Author

Cai Jing

DOI

10.16182/j.issn1004731x.joss.23-1599

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