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Impact Damage Identification of Aluminum Alloy Reinforced Plate Based on GWO-ELM Algorithm

Wei Li1,2, Benjian Zou1, Yuxiang Luo2, Ning Yang2, Faye Zhang1,*, Mingshun Jiang1, Lei Jia1

1 School of Control Science and Engineering, Shandong University, Jinan, 250061, China
2 Communication Technology Division, Shandong Institute of Space Electronic Technology, Yantai, 264000, China

* Corresponding Author: Faye Zhang. Email: email

Structural Durability & Health Monitoring 2023, 17(6), 485-500. https://doi.org/10.32604/sdhm.2023.025989

Abstract

As a critical structure of aerospace equipment, aluminum alloy stiffened plate will influence the stability of spacecraft in orbit and the normal operation of the system. In this study, a GWO-ELM algorithm-based impact damage identification method is proposed for aluminum alloy stiffened panels to monitor and evaluate the damage condition of such stiffened panels of spacecraft. Firstly, together with numerical simulation, the experimental simulation to obtain the damage acoustic emission signals of aluminum alloy reinforced panels is performed, to establish the damage data. Subsequently, the amplitude-frequency characteristics of impact damage signals are extracted and put into an extreme learning machine (ELM) model to identify the impact location and damage degree, and the Gray Wolf Optimization (GWO) algorithm is employed to update the weight parameters of the model. Finally, experiments are conducted on the irregular aluminum alloy stiffened plate with the size of 2200 mm × 500 mm × 10 mm, the identification accuracy of impact position and damage degree is 98.90% and 99.55% in 68 test areas, respectively. Comparative experiments with ELM and backpropagation neural networks (BPNN) demonstrate that the impact damage identification of aluminum alloy stiffened plate based on GWO-ELM algorithm can serve as an effective way to monitor spacecraft structural damage.

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APA Style
Li, W., Zou, B., Luo, Y., Yang, N., Zhang, F. et al. (2023). Impact damage identification of aluminum alloy reinforced plate based on GWO-ELM algorithm. Structural Durability & Health Monitoring, 17(6), 485-500. https://doi.org/10.32604/sdhm.2023.025989
Vancouver Style
Li W, Zou B, Luo Y, Yang N, Zhang F, Jiang M, et al. Impact damage identification of aluminum alloy reinforced plate based on GWO-ELM algorithm. Structural Durability Health Monit . 2023;17(6):485-500 https://doi.org/10.32604/sdhm.2023.025989
IEEE Style
W. Li et al., "Impact Damage Identification of Aluminum Alloy Reinforced Plate Based on GWO-ELM Algorithm," Structural Durability Health Monit. , vol. 17, no. 6, pp. 485-500. 2023. https://doi.org/10.32604/sdhm.2023.025989



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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