1. Localization of impact on CFRP structure based on fiber Bragg gratings and CNN-LSTM-Attention.
- Author
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Yu, Junsong, Liu, Jun, Peng, Zipeng, Gan, Linghui, and Wan, Shengpeng
- Subjects
- *
FIBER Bragg gratings , *CARBON fibers , *DETECTORS , *COMPARATIVE studies , *POLYMERS - Abstract
• Low-velocity impacts can cause microscopic and invisible damage to Carbon Fiber Reinforced Polymer (CFRP) structures, potentially compromising their integrity and leading to catastrophic failures. In this paper, an impact localization system for CFRP structures was developed by using Fiber Bragg Grating (FBG) sensors. The time difference of arrival (TDOA) between signals from different FBG sensors are collected to characterize the impact location, and an impact localization method of CFRP structure based on CNN-LSTM-Attention is proposed. The following conclusions can be made from this study: • A monitoring system of impact on CFRP structures was developed by using fiber Bragg grating (FBG) sensors, and impact signals detected by FBG sensors are demodulated by edge-filtering at high speed. • The Time Difference of Arrival (TDOA) between signals from different FBG sensors are collected to characterize the impact location, the occurrence time of the first trough in the low-frequency narrowband signal component is extracted as the arrival time of impact signal, which is found to be sensitive to the location of impact and thus can be used as features for impact localization. • An impact localization method of CFRP structure based on CNN-LSTM-Attention is proposed. The time differences in the arrival of impact signal detected by different FBG sensors are used as features, and attention mechanism is introduced into the CNN-LSTM model of impact localization to emphasizes the arrival time difference of impact signal detected by nearby FBG sensors. • The impact localization method was developed and validated on a CFRP plate by using FBG sensors. Comparative analysis of localization performance between different models confirms the effectiveness and satisfactory performance of the proposed method. Low-velocity impacts can cause microscopic and invisible damage to carbon fiber reinforced polymer (CFRP) structures, potentially compromising their integrity and leading to catastrophic failures. Therefore, obtaining precise information about the impact location is crucial for monitoring the health of CFRP structures. In this paper, an impact localization system for CFRP structures was developed by using fiber Bragg grating (FBG) sensors, and impact signals detected by FBG sensors are demodulated by edge-filtering at high speed. An impact localization method of CFRP structure based on CNN-LSTM-Attention is proposed. The time difference of arrival (TDOA) between signals from different FBG sensors are collected to characterize the impact location, and attention mechanism is introduced into the CNN-LSTM model to augment the significance of TDOA of impact signal detected by proximal FBG sensors. The model is trained using the training set, its parameters are optimized using the validation set and the localization performance of different models are compared by the test set. The proposed impact localization method based on CNN-LSTM-Attention model was verified on a CFRP plate with an experiment area of 400 mm*400 mm. Experimental results prove the effectiveness and satisfactory performance of the proposed method. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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