基于NNBoost的卫星用复合材料层合板结构不确定性固有频率分析方法研究

doi:10.3901/JME.2023.24.242

机械工程学报 ›› 2023, Vol. 59 ›› Issue (24): 242-250.doi: 10.3901/JME.2023.24.242

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基于NNBoost的卫星用复合材料层合板结构不确定性固有频率分析方法研究

赵琳¹, 刘源¹, 曹喜滨¹, 侯耀东¹, 张俊杰²

1. 哈尔滨工业大学卫星技术研究所哈尔滨 150001;
2. 哈尔滨工业大学精密工程研究所哈尔滨 150001

收稿日期:2023-03-02 修回日期:2023-08-09 出版日期:2023-12-20 发布日期:2024-03-05
通讯作者: 刘源(通信作者)，男，1981年出生，教授，博士研究生导师。主要研究方向为航天器先进结构跨尺度分析与设计；航天器不确定性量化、动力分析与设计优化；航天器高性结构与机构创新设计与产品制备。E-mail：liuyuan_hit@hit.edu.cn
作者简介:赵琳，女，1999年出生。主要研究方向为航天器不确定性量化、动力分析与设计优化。E-mail：22s118195@stu.hit.edu.cn
基金资助:
国家自然科学基金资助项目(52372351，51875119)

Research on NNBoost-based Uncertain Natural Frequency of Composite Laminates for Satellite Structures

ZHAO Lin¹, LIU Yuan¹, CAO Xibin¹, HOU Yaodong¹, ZHANG Junjie²

1. Research Center of Satellite Technology, Harbin Institute of Technology, Harbin 150001;
2. Center for Precision Engineering, Harbin Institute of Technology, Harbin 150001

Received:2023-03-02 Revised:2023-08-09 Online:2023-12-20 Published:2024-03-05

摘要/Abstract

摘要： 为实现卫星用复合材料层合板固有频率的精确分析，综合考虑结构的加工误差、材料随机偏差等不确定性因素，研究并提出一种采用神经网络增强(Neural network boosting, NNBoost)模型对正交各向异性复合材料层合板固有频率进行不确定性分析的方法。将NNBoost模型作为固有频率求解与预测的代理模型，其目标函数设定为损失函数与正则项之和，求解过程中采用一种基于泰勒展开式的梯度下降方法更新权重和阈值以加速收敛。采用该方法，分析考虑输入参数随机性时正交各向异性复合材料层合板固有频率的统计特性。仿真试验结果表明，与直接蒙特卡洛模拟(Monte Carlo simulation, MCS) 相比，采用NNBoost方法在保证预测精度的同时显著提高了求解效率；与传统反向传播(Back propagation, BP) 神经网络方法相比，采用NNBoost方法预测结果的均方误差小于BP神经网络预测结果的均方误差且误差收敛更加平稳。

关键词: 卫星结构, 复合材料层合板, 神经网络增强模型, 不确定性固有频率

Abstract: In order to realize accurate analysis of the natural frequency of composite laminates for satellite structures, a method for analyzing the uncertainty of the natural frequency orthotropic composite laminates by using neural network boosting(NNBoost) model is proposed by considering the factors of uncertainty such as machining errors and material random deviations. In this paper, the NNBoost model is used as a surrogate model for solving and predicting the natural frequency. The objective function is set as sum of the loss function and the regularization term. In the solving process, a gradient descent method based on Taylor expansion is used to update the weights and thresholds to accelerate the convergence. Using this method, statistical characteristics of the natural frequencies of an orthotropic composite laminate are analyzed with the randomness of input parameters considered. The simulation results show that compared with the direct Monte Carlo simulation(MCS), the proposed method significantly improves the solution efficiency while ensuring the prediction accuracy. Compared with the traditional back propagation(BP) neural network method, the mean square error of the prediction results with this method is smaller than that of the BP neural network and the error convergence is more stable.

Key words: satellite structures, composite laminates, neural network boost model, uncertain natural frequency

中图分类号:

赵琳, 刘源, 曹喜滨, 侯耀东, 张俊杰. 基于NNBoost的卫星用复合材料层合板结构不确定性固有频率分析方法研究[J]. 机械工程学报, 2023, 59(24): 242-250.

ZHAO Lin, LIU Yuan, CAO Xibin, HOU Yaodong, ZHANG Junjie. Research on NNBoost-based Uncertain Natural Frequency of Composite Laminates for Satellite Structures[J]. Journal of Mechanical Engineering, 2023, 59(24): 242-250.

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基于NNBoost的卫星用复合材料层合板结构不确定性固有频率分析方法研究

Research on NNBoost-based Uncertain Natural Frequency of Composite Laminates for Satellite Structures

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