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  本文選題：復合材料帶纏繞工藝　切入點：層間剪切強度　出處：《固體火箭技術》2017年05期 　論文類型：期刊論文

【摘要】：復合材料帶纏繞成型過程中,成型工藝參數的選取決定了纏繞制品的性能。采用正交實驗法研究各工藝參數對纏繞制品層間剪切強度的影響規(guī)律和敏感度,并將正交試驗數據與神經網絡理論相結合,對帶纏繞成型過程進行建模,得到纏繞成型工藝參數與層間剪切強度之間的非線性映射關系,并通過實驗驗證了模型的可靠性。在此基礎上,利用粒子群優(yōu)化方法在可行工藝參數域內對纏繞成型工藝參數進行優(yōu)化。仿真與實驗結果表明,基于神經網絡模型的工藝參數粒子群優(yōu)化算法能夠快速、準確的得到帶纏繞成型的全局最優(yōu)工藝參數組合。使得纏繞制品層間剪切強度達到最優(yōu)的工藝參數組合為:加熱溫度115℃,纏繞張力357 N,壓輥壓力1006 N和纏繞速度0.28 m/s,在最優(yōu)工藝參數作用下,纏繞制品的層間剪切強度達到102.2 MPa。
[Abstract]:The properties of the winding products are determined by the selection of the forming parameters during the winding process of the composite tape. The influence of the process parameters on the interlaminar shear strength and the sensitivity of the interlaminar shear strength of the winding products are studied by orthogonal experiment. Combining the orthogonal test data with the neural network theory, the nonlinear mapping relationship between the winding process parameters and the interlaminar shear strength is obtained. The reliability of the model is verified by experiments. On this basis, particle swarm optimization (PSO) is used to optimize the process parameters in the feasible process parameters domain. The simulation and experimental results show that, Particle swarm optimization (PSO) algorithm based on neural network model can be used to optimize process parameters quickly. The global optimum process parameter combination with winding molding is obtained accurately. The optimum process parameters for interlaminar shear strength of winding products are as follows: heating temperature 115 鈩，

本文編號：1589285