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Monitoring the cohesive damage of the adhesive layer in CFRP double-lapped bonding joint based on non-uniform strain profile reconstruction using dynamic particle swarm optimization algorithm
•A novel method achieves the cohesive damage monitoring of adhesive layer.•Non-uniform strain profile reconstruction is the foundations of the method.•Using DPSO algorithm in reconstructing non-uniform strain profile is realized. To well understand the failure mode and monitor the internal damage of...
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Published in: | Measurement : journal of the International Measurement Confederation 2018-07, Vol.123, p.235-245 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •A novel method achieves the cohesive damage monitoring of adhesive layer.•Non-uniform strain profile reconstruction is the foundations of the method.•Using DPSO algorithm in reconstructing non-uniform strain profile is realized.
To well understand the failure mode and monitor the internal damage of the carbon fiber reinforced plastic (CFRP) bonding joint provides guarantee for the safety and reliability of the aerospace. This article obtained the mapping relationship model between the strain profiles change of the adherend and the damage evolution of adhesive layer in the CFRP double-lapped bonding joint by ABAQUS based on the cohesive zone model. Then the Fiber Bragg Grating (FBG) was embedded in CFRP adherend to calculate the reflection spectrum of FBG for reconstructing the adherend strain profile of FBG sensing area with the dynamic particle swarm optimization algorithm. The reconstructed results showed that the maximum error between the simulated strain profile and the reconstructed one under different loads was not exceeding 1.701, revealing good consistency and making it possible to monitor the cohesive damage of adhesive layer based on the non-uniform strain profile reconstruction. |
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ISSN: | 0263-2241 1873-412X |
DOI: | 10.1016/j.measurement.2018.03.063 |