基于近似模型的大型汽轮发电机定子端部绕组动力响应预测研究

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摘要针对电磁力作用下大型汽轮发电机定子端部绕组动力响应建模及计算复杂问题，提出一种基于数据驱动的支持向量回归（SVR）动力响应预测方法。通过少量典型样本构建某600MW汽轮发电机动力响应近似模型，从而代替复杂耗时的有限元模型预测不同结构参数下的动态性能。以端部绕组鼻端位移峰值作为动力响应的关键指标，首先选取绑环刚度、径向支架刚度以及滑销和径向支架之间的固定约束数目为设计变量，通过正交试验设计获取样本，在ABAQUS中分别建立试验样本对应的有限元模型，再对其进行计算获得鼻端位移时程曲线；然后通过遗传算法（GA）对SVR中的参数寻优构建端部绕组动力响应的近似模型，对比结果显示，该近似模型精度优于基于响应面法（RSM）和克里金插值法（Kriging）构建的预测模型；最后基于近似模型探讨了设计参数对鼻端位移峰值的影响规律。该方法可用于后续的优化设计以及装备数字孪生系统中电气和力学性能的实时求解与计算。

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	赵洋1
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	何乐1
	刘晋珲1
	陈翔1
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	马莹1
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关键词 ：端部绕组, 动力响应, 支持向量回归, 遗传算法, 近似模型

Abstract：A dynamic response prediction method based on data driven support vector regression (SVR) is proposed to resolve the complex modeling and calculating problem of the dynamic response of large turbo-generator stator end winding under electromagnetic force. In this method, the approximate dynamic response model of a 600MW turbo-generator is constructed by a small number of typical samples to efficiently predict the dynamic performance under different parameter structures, thus replacing the complex and time-consuming finite element model. The peak displacement at the nose of the end winding is taken as the key index of dynamic response. Firstly, the stiffness of the rings, the stiffness of the radial braces and the number of pins bonded to the radial braces are selected as design variables. The samples are obtained through orthogonal experimental design, and the corresponding finite element models of the test samples are established in ABAQUS. After that, the finite element models are calculated to obtain the time history curve of displacement at the nose of the end winding. Secondly, a genetic algorithm (GA) is used to optimize the parameters in SVR to construct an approximate model of the dynamic response of the end winding. The comparison results show that the accuracy of the dynamic response approximate model based on GA-SVR is better than that based on the response surface method (RSM) and Kriging interpolation method (Kriging). Finally, the influence of the parameters on the peak displacement of the nose of the end winding is discussed based on the approximate model. The method presented in this paper can be used in the subsequent optimization design, and also can be used in the real-time solution and calculation of electrical and mechanical properties in the digital twin systems.

Key words： Stator end winding Dynamic response Support vector regression Genetic algorithm Approximate model

收稿日期: 2022-11-15 出版日期: 2023-11-15

引用本文:

赵洋1,2,3, 何乐1, 刘晋珲1, 陈翔1,2，马莹1,2. 基于近似模型的大型汽轮发电机定子端部绕组动力响应预测研究[J]. 振动与冲击, 2023, 42(21): 81-87.
ZHAO Yang1,2,3, HE Le1, LIU Jinhui1, CHEN Xiang1,2, MA Ying1,2. Dynamic response prediction of large turbo-generator stator end winding based on approximate model. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(21): 81-87.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2023/V42/I21/81

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