Inverse analysis of strain distributions sensed by distributed fiber optic sensors subject to strain transfer

•Strain distributions sensed by distributed fiber optic sensors are subject to strain transfer effect.•An inverse analysis is presented to convert measured strains into real strain distributions.•The method is applicable when the type and location of loading and strain field are unknown.•Multiple me...

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Veröffentlicht in:Mechanical systems and signal processing Jg. 166; S. 108474
Hauptverfasser: Mahjoubi, Soroush, Tan, Xiao, Bao, Yi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin Elsevier Ltd 01.03.2022
Elsevier BV
Schlagworte:
Distributed fiber optic sensor
Fiber optics
Genetic algorithms
Heuristic methods
Inverse analysis
Inverse method
Metaheuristics
Optimization
Optimization algorithms
Particle swarm optimization
Prestressed concrete
Protective coatings
Sensors
Strain analysis
Strain transfer
Structural health monitoring
Inverse analysis
Distributed fiber optic sensor
Strain transfer
Structural health monitoring
Metaheuristics
Optimization
ISSN:0888-3270, 1096-1216
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Zusammenfassung:•Strain distributions sensed by distributed fiber optic sensors are subject to strain transfer effect.•An inverse analysis is presented to convert measured strains into real strain distributions.•The method is applicable when the type and location of loading and strain field are unknown.•Multiple metaheuristic optimization algorithms are used and compared for the inverse analysis.•The method has been implemented to a prestressed concrete beam under four-point bending test. Strains measured by distributed fiber optic sensors with protective coatings can be different from the real strains in host matrix due to strain transfer effect. This study presents a novel inverse method to determine the real strain distributions in host matrix using strain distributions measured from distributed fiber optic sensors. Two different scenarios of strain distributions in host matrix are investigated, which have known and unknown types of strain fields, respectively. Three representative metaheuristic algorithms are respectively utilized in the inverse analysis, which are colliding bodies optimization algorithm, particle swarm optimization algorithm, and genetic algorithm. The performance of the proposed method was evaluated by analytical case studies and experimental testing of a prestressed concrete beam subjected to four-point bending. The results demonstrated high accuracy and efficiency of the proposed method. This study is expected to greatly advance distributed fiber optic sensing capabilities in measuring strain distributions for structural health monitoring.
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ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2021.108474