Volume 47 Issue 6
Jun.  2021
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LIN Yuan, GUAN Zhidong. Predicting the formation uniformity of composite autoclave by BP neural network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(6): 1271-1276. doi: 10.13700/j.bh.1001-5965.2020.0158(in Chinese)
Citation: LIN Yuan, GUAN Zhidong. Predicting the formation uniformity of composite autoclave by BP neural network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(6): 1271-1276. doi: 10.13700/j.bh.1001-5965.2020.0158(in Chinese)

Predicting the formation uniformity of composite autoclave by BP neural network

doi: 10.13700/j.bh.1001-5965.2020.0158
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  • Corresponding author: GUAN Zhidong, E-mail: zdguan@buaa.edu.cn
  • Received Date: 23 Apr 2020
  • Accepted Date: 30 May 2020
  • Publish Date: 20 Jun 2021
  • The difference in degree of cure in the forming process of composite autoclave is one of the main characterization parameters of degree of cure uniformity of composite. Based on thethree-layer BP neural network, this paper established a rapid estimation model of maximum difference of curing degree at any time in the forming process with heating rate, holding time and holding temperature as input parameters. Maximum difference in degree of cure was obtained by simulating the forming process of composite autoclave as test sample data to train the BP neural network, and the accuracy of the model was verified after the training. The results show that the accuracy and efficiency of this BP neural network model are high, which provides a fast and effective new method for estimating the difference of the maximum curing degree of composite autoclave.

     

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