摘要
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.
| 投稿的翻译标题 | Predicting the formation uniformity of composite autoclave by BP neural network |
|---|---|
| 源语言 | 繁体中文 |
| 页(从-至) | 1271-1276 |
| 页数 | 6 |
| 期刊 | Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics |
| 卷 | 47 |
| 期 | 6 |
| DOI | |
| 出版状态 | 已出版 - 6月 2021 |
关键词
- Autoclave
- Composite
- Curing process
- Estimation
- Neural network
- Residual stress
学术指纹
探究 'BP神经网络预测复合材料热压罐成型均匀性' 的科研主题。它们共同构成独一无二的学术指纹。引用此
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver