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

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.