Journal Article10.1177/1475921719825601
Optimization of sensor placement for structural health monitoring: a review:
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TL;DR: This article reviews the work in the area of optimization of sensor placement and highlights the different pitfalls of the optimization algorithms and the countermeasures different researchers have proposed to overcome the known shortcomings.
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Abstract: The deployment cost of the structural health monitoring (SHM) system is the major argument against the more widespread use of the structural health monitoring techniques. Optimization of sensor pla...
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Review of Bridge Structural Health Monitoring Aided by Big Data and Artificial Intelligence: From Condition Assessment to Damage Detection
TL;DR: This work has shown that structural health monitoring techniques have been widely used in long-span bridges but, due to limitations of computational ability and data analysis methods, the knowledge in these techniques is limited.
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Shear horizontal wave transducers for structural health monitoring and nondestructive testing: A review.
Hongchen Miao,Faxin Li +1 more
TL;DR: In this paper, a review of the state-of-the-art SH wave transducers for structural health monitoring (SHM) and nondestructive testing (NDT) is presented.
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A novel load-dependent sensor placement method for model updating based on time-dependent reliability optimization considering multi-source uncertainties
TL;DR: This study proposes a time-dependent, reliability-based method for the optimal load-dependent sensor placement considering multi-source uncertainties using a non-probabilistic theory to characterize the uncertainty in the uncertainty propagation process for model updating.
127
Advancements in fiber-reinforced polymer composite materials damage detection methods: Towards achieving energy-efficient SHM systems
TL;DR: In this article, the authors present recent advances in non-destructive testing and evaluation (NDT&E) and in-situ structural health monitoring (SHM) techniques for damage detection in fiber-reinforced polymer (FRP) composites.
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Multi-objective optimization for improved project management: Current status and future directions
Kai Guo,Limao Zhang +1 more
TL;DR: In this article , a systematic review under both scientometric and qualitative analysis is presented to understand the current state and discuss the future research trends of MOO for project improvement. But, the authors do not provide a detailed analysis of these trends.
107
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Optimal sensor placement for large structures using the nearest neighbour index and a hybrid swarm intelligence algorithm
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Assessment of embedded fiber Bragg gratings for structural health monitoring of composites
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