Optimal sensor placement for enhancing sensitivity to change in stiffness for structural health monitoring

This paper focuses on optimal sensor placement for structural health monitoring (SHM), in which the goal is to find an optimal configuration of sensors that will best predict structural damage. The problem is formulated as a bound constrained mixed variable programming (MVP) problem, in which the di...

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Vydáno v:Optimization and engineering Ročník 9; číslo 2; s. 119 - 142
Hlavní autoři: Beal, Josh M., Shukla, Amit, Brezhneva, Olga A., Abramson, Mark A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Boston Springer US 01.06.2008
Springer Nature B.V
Témata:
Algorithms
Control
Engineering
Environmental Management
Financial Engineering
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Studies
Systems Theory
Mixed variable programming
Optimal sensor placement
Structural health monitoring
ISSN:1389-4420, 1573-2924
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Shrnutí:This paper focuses on optimal sensor placement for structural health monitoring (SHM), in which the goal is to find an optimal configuration of sensors that will best predict structural damage. The problem is formulated as a bound constrained mixed variable programming (MVP) problem, in which the discrete variables are categorical; i.e., they may only take on values from a pre-defined list. The problem is particularly challenging because the objective function is computationally expensive to evaluate and first-order derivatives may not be available. The problem is solved numerically using the generalized mixed variable pattern search (MVPS) algorithm. Some new theoretical convergence results are proved, and numerical results are presented, which show the potential of our approach.
Bibliografie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:1389-4420
1573-2924
DOI:10.1007/s11081-007-9023-1