TY - JOUR
T1 - Computer-aided feature recognition of CFRP plates based on real-time strain fields reflected from FBG measured signals
AU - Wang, Hua Ping
AU - Chen, Cong
AU - Ni, Yi Qing
AU - Jayawickrema, Minol
AU - Epaarachchi, Jayantha
N1 - Funding Information:
The work described in this paper was supported by the National Natural Science Foundation of China (51908263, 22YF7GA182 and 11932008); National Foreign Expert Project of China (DL2021175003L and G2021175026L); the Fundamental Research Funds for the Central Universities (No. lzujbky-2022-kb01); Provincial Projects (2020-0624-RCC-0013 and JK2021-18); Hunan Science Fund for Distinguished Young Scholars (2021JJ10061); Key R&D Program of Hunan Province (2020SK2060). Special thanks are due to Prof. Jinping Ou and Prof. Zhi Zhou of Dalian University of Technology, and Prof. Youhe Zhou and Prof. Ning Huang of Lanzhou University. The findings and opinions expressed in this article are only those of the authors and do not necessarily reflect the views of the sponsors.
Funding Information:
The work described in this paper was supported by the National Natural Science Foundation of China ( 51908263 , 22YF7GA182 and 11932008 ); National Foreign Expert Project of China ( DL2021175003L and G2021175026L ); the Fundamental Research Funds for the Central Universities (No. lzujbky-2022-kb01 ); Provincial Projects ( 2020-0624-RCC-0013 and JK2021-18 ); Hunan Science Fund for Distinguished Young Scholars ( 2021JJ10061 ); Key R&D Program of Hunan Province ( 2020SK2060 ). Special thanks are due to Prof. Jinping Ou and Prof. Zhi Zhou of Dalian University of Technology, and Prof. Youhe Zhou and Prof. Ning Huang of Lanzhou University. The findings and opinions expressed in this article are only those of the authors and do not necessarily reflect the views of the sponsors.
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/8/15
Y1 - 2023/8/15
N2 - Condition monitoring of critical and expensive carbon fiber reinforced polymer (CFRP) composite infrastructures is extremely essential task for uninterrupted operation and the durability of structures. Therefore, accurate and robust monitoring techniques and correlated damage identification algorithms need to be developed to characterize the health status of the CFRP structures. However, the effectiveness of existing methods is highly dependent on the structural properties of the CFRP plates. To identify the random damages caused by static or dynamic forces, the concept to establish the real-time strain fields of the structures based on measured signals is proposed. A moving surface spline interpolation algorithm based on Green's function has been developed to map the real-time strain fields of the CFRP plate using strain measured by surface-attached FBG sensors. A few static and impact loadings have been applied to a sample CFRP plate and the strain-field prediction by the proposed algorithm has been evaluated by a finite element model. Time and frequency domain analysis has also been conducted to recognize the dynamic response of the CFRP plates. Results indicate that the proposed algorithm can establish real-time strain field predictions with high precision, which can be used to recognize the static and dynamic responses of CFRP plate. Most importantly, the method is independent on the structural properties of the plate and the sensor layout, which is particularly significant for constructing the smart health monitoring system of CFRP.
AB - Condition monitoring of critical and expensive carbon fiber reinforced polymer (CFRP) composite infrastructures is extremely essential task for uninterrupted operation and the durability of structures. Therefore, accurate and robust monitoring techniques and correlated damage identification algorithms need to be developed to characterize the health status of the CFRP structures. However, the effectiveness of existing methods is highly dependent on the structural properties of the CFRP plates. To identify the random damages caused by static or dynamic forces, the concept to establish the real-time strain fields of the structures based on measured signals is proposed. A moving surface spline interpolation algorithm based on Green's function has been developed to map the real-time strain fields of the CFRP plate using strain measured by surface-attached FBG sensors. A few static and impact loadings have been applied to a sample CFRP plate and the strain-field prediction by the proposed algorithm has been evaluated by a finite element model. Time and frequency domain analysis has also been conducted to recognize the dynamic response of the CFRP plates. Results indicate that the proposed algorithm can establish real-time strain field predictions with high precision, which can be used to recognize the static and dynamic responses of CFRP plate. Most importantly, the method is independent on the structural properties of the plate and the sensor layout, which is particularly significant for constructing the smart health monitoring system of CFRP.
KW - CFRP composites
KW - FBG sensor
KW - Feature recognition
KW - Frequency domain analysis
KW - Strain-field configuration
KW - Surface spline interpolation algorithm
UR - http://www.scopus.com/inward/record.url?scp=85163811701&partnerID=8YFLogxK
U2 - 10.1016/j.compositesb.2023.110866
DO - 10.1016/j.compositesb.2023.110866
M3 - Journal article
AN - SCOPUS:85163811701
SN - 1359-8368
VL - 263
JO - Composites Part B: Engineering
JF - Composites Part B: Engineering
M1 - 110866
ER -