Mathematical modeling of an armature assembly in pilot stage of a hydraulic servo valve based on distributed parameters

Lv, Xinbei; Peng, Jinghui; Li, Songjing

doi:10.1016/j.cja.2020.10.013

Cited by 7 publications

(2 citation statements)

References 23 publications

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“…e JPS valve, which is a core component of electro-hydraulic servo system, is widely concerned and applied in the aerospace system because of its antipollution, high sensitivity, and long service life [1][2][3]. Especially, the JPS valve has better antipollution performance and higher reliability than the nozzle apper valve [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Mathematical Modelling and Hierarchical Encourage Particle Swarm Optimization Genetic Algorithm for Jet Pipe Servo Valve

Chen

Yang

et al. 2022

Computational Intelligence and Neuroscience

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The jet pipe servo (JPS) valve is one key component, whose dynamic performance directly influences the aircraft’s maneuverability. In this paper, a more accurate mathematical model and a novel multiobjective hierarchical encourage particle swarm optimization genetic algorithm (HEPGA) are proposed to improve the dynamic performance of the jet pipe servo valve. By optimizing the main structure parameters of the jet pipe servo valve, the adjustment and overshoot in the dynamic performance are reduced by 24.28% and 51.39%, respectively, compared with the prototype before optimization. To obtain a more accurate mathematical model, the computational fluid dynamics (CFD) is introduced to modify the analytical model considering the turbulent submerged free jet. Different from conventional numerical simulation, the dynamic mesh technique is used to analyze the flow field distribution by considering the force interaction of various parts of the jet pipe servo valve under actual working condition. Then, the HEPGA with better convergence is utilized because of the conflict of adjustment and overshoot. This proposed hybrid algorithm introduces the concept of staff welfare system to divide the population into elite individuals and excellent individuals of particle swarm optimization and general individuals of genetic algorithm. Meanwhile, the convergency performance of the HEPGA is evaluated through the Rosenbrock function by comparing with other particle swarm genetic hybrid methods. Subsequently, the experimental platform is constructed and the dynamic performance tests are conducted on the prototype after optimization. The experimental results verify the accuracy of the established mathematical model and the significant improvement of dynamic performance of the jet pipe servo valve.

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Section: Introductionmentioning

confidence: 99%

“…en the dynamic performance of the armature assembly was investigated by establishing the mathematical model which is veri ed by FEA [5]. e comparison results show that the error between the established model and numerical simulation is 6.6%.…”

Section: Introductionmentioning

confidence: 99%