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风电齿轮箱迷宫密封泄漏量分析及结构优化设计

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为了分析某风电齿轮箱内迷宫密封各参数对泄漏量的影响,利用数值模拟和构建代理模型对迷宫密封的泄漏行为开展了研究.首先,根据风电齿轮箱三维实体模型构建了其迷宫密封三维流场模型;然后,基于FLUENT软件,通过单一变量法研究了迷宫密封泄漏量随进出口压力比、润滑液动力黏度、高速轴与低速轴的转速和迷宫密封的密封齿间隙的变化规律;最后,构建了径向基神经网络(RBF)代理模型,在该代理模型的基础上,在影响迷宫密封性能的因素中,选取了密封间隙、密封腔体高度和密封腔体宽度三个结构参数作为设计变量,以迷宫密封的最小泄漏量和出口最大速度为优化目标,使用非劣分层遗传算法(NSGA-Ⅱ)获得了最优解.研究结果表明:迷宫密封泄漏量受两个转轴的转速影响很小;泄漏量与进出口压力比、密封间隙成正比,而与润滑油动力黏度成反比;求得最优解对应的参数所对应泄漏量减小了 47%,出口最大速度降低了 36%,数值模拟与优化理论计算结果一致.该结果可为研究迷宫密封泄漏量的影响特性提供理论依据.
Leakage analysis and structural optimization design of labyrinth seal in wind power gearbox
In order to analyze the influence of labyrinth seal parameters on the leakage of a wind power gearbox,the leakage behavior of labyrinth seal was studied by numerical simulation and proxy model.Firstly,the three-dimensional flow field model of labyrinth seal was constructed according to the three-dimensional solid model of wind turbine gearbox.Then,based on FLUENT software,the changes of labyrinth seal leakage with inlet and outlet pressure ratio,dynamic viscosity of lubricating fluid,speed of high-speed shaft and low-speed shaft and seal tooth clearance of labyrinth seal were studied by single variable method.Finally,a radial basis neural network(RBF)proxy model was constructed.On the basis of this proxy model,three structural parameters,seal gap,seal cavity height and seal cavity width,were selected as design variables among the factors affecting the labyrinth sealing performance,and the minimum leakage and maximum exit velocity of the labyrinth seal were taken as optimization objectives.Non-inferior hierarchical genetic algorithm(NSGA-Ⅱ)was used to obtain the optimal solution.The results show that the leakage of labyrinth seal is little affected by the speed of two rotating shafts.The leakage is proportional to the ratio of inlet and outlet pressure and seal clearance,and inversely proportional to the dynamic viscosity of lubricating oil.When the parameters corresponding to the optimal solution are obtained,the leakage is reduced by 47%and the maximum exit velocity is reduced by36%.The numerical simulation element results are consistent with the optimization theoretical calculation results.The results provide a theoretical basis for studying the influence characteristics of labyrinth seal leakage.

wind turbinegear caselabyrinth sealleakage volumenumerical simulationoptimal designradial basis neural network(RBF)proxy model

高羡明、张洋、张功学、杨汶轩、蔡志祥

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陕西科技大学 机电工程学院,陕西 西安 710021

风电机组 齿轮箱 迷宫密封 泄漏量 数值模拟 优化设计 径向基神经网络(RBF)代理模型

国家自然科学基金青年科学基金资助项目

51905328

2024

机电工程
浙江大学 浙江省机电集团有限公司

机电工程

CSTPCD北大核心
影响因子:0.785
ISSN:1001-4551
年,卷(期):2024.41(4)
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