Research on the relationship between process parameters and mechanical properties of composites based on neural network

Fei Shi; XiaoMing Cheng

doi:10.1117/12.2673544

22 May 2023 Research on the relationship between process parameters and mechanical properties of composites based on neural network

Fei Shi, XiaoMing Cheng

Author Affiliations +

Proceedings Volume 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022); 126401H (2023) https://doi.org/10.1117/12.2673544
Event: International Conference on Internet of Things and Machine Learning (IoTML 2022), 2022, Harbin, China

Abstract

At present, it is difficult to distinguish the relationship between the mechanical properties and process parameters of composites by direct calculation or finite element method. But, through the neural network method, there is no need to involve the solid-liquid coupling problem. In this paper, via the study of neural network, the model of relationship between the process parameters and the mechanical properties of the composites is established. The calculated results of the model are in good agreement with the experimental values after training the classifiers by the samples, and its show that the model is correct. At the same time, a set of data is used to test the model, and the results are consistent. This study also shows that the interlaminar shear strength and bending strength of the composites increase with the decrease of resin injection temperature，shortening of resin injection time and the increase of resin injection pressure.

Citation Download Citation

Fei Shi and XiaoMing Cheng "Research on the relationship between process parameters and mechanical properties of composites based on neural network", Proc. SPIE 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022), 126401H (22 May 2023); https://doi.org/10.1117/12.2673544

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