Details
Original language | English |
---|---|
Article number | 100014 |
Journal | Optimization and Engineering |
Publication status | E-pub ahead of print - 9 Jan 2025 |
Abstract
Keywords
- math.OC, 70J10, 74R99, 90C26, 90C29, 90C59, Damage location, Pattern search, Mechanical structures, Multi-objective optimization, Parameter identification
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Engineering(all)
- Civil and Structural Engineering
- Engineering(all)
- Aerospace Engineering
- Engineering(all)
- Mechanical Engineering
- Mathematics(all)
- Control and Optimization
- Engineering(all)
- Electrical and Electronic Engineering
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: Optimization and Engineering, 09.01.2025.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Damage location in mechanical structures by multi-objective pattern search
AU - Günther, Christian
AU - Hofmeister, Benedikt
AU - Hübler, Clemens
AU - Jonscher, Clemens
AU - Ragnitz, Jasper
AU - Schubert, Jenny
AU - Steinbach, Marc c.
N1 - Publisher Copyright: © The Author(s) 2025.
PY - 2025/1/9
Y1 - 2025/1/9
N2 - We propose a multi-objective global pattern search algorithm for the task of locating and quantifying damage in flexible mechanical structures. This is achieved by identifying eigenfrequencies and eigenmodes from measurements and matching them against the results of a finite element simulation model, which leads to a nonsmooth nonlinear bi-objective parameter estimation problem. A derivative-free optimization algorithm is required since the problem is nonsmooth and also because complex mechanical simulation models are often solved using commercial black-box software. Moreover, the entire set of non-dominated solutions is of interest to practitioners. Most solution approaches published to date are based on meta-heuristics such as genetic algorithms. The proposed multi-objective pattern-search algorithm provides a mathematically well-founded alternative. It features a novel sorting procedure that reduces the complexity in our context. Test runs on two experimental structures with multiple damage scenarios are used to validate the approach. The results demonstrate that the proposed algorithm yields accurate damage locations and requires moderate computational resources. From the engineer’s perspective it represents a promising tool for structural health monitoring.
AB - We propose a multi-objective global pattern search algorithm for the task of locating and quantifying damage in flexible mechanical structures. This is achieved by identifying eigenfrequencies and eigenmodes from measurements and matching them against the results of a finite element simulation model, which leads to a nonsmooth nonlinear bi-objective parameter estimation problem. A derivative-free optimization algorithm is required since the problem is nonsmooth and also because complex mechanical simulation models are often solved using commercial black-box software. Moreover, the entire set of non-dominated solutions is of interest to practitioners. Most solution approaches published to date are based on meta-heuristics such as genetic algorithms. The proposed multi-objective pattern-search algorithm provides a mathematically well-founded alternative. It features a novel sorting procedure that reduces the complexity in our context. Test runs on two experimental structures with multiple damage scenarios are used to validate the approach. The results demonstrate that the proposed algorithm yields accurate damage locations and requires moderate computational resources. From the engineer’s perspective it represents a promising tool for structural health monitoring.
KW - math.OC
KW - 70J10, 74R99, 90C26, 90C29, 90C59
KW - Damage location
KW - Pattern search
KW - Mechanical structures
KW - Multi-objective optimization
KW - Parameter identification
UR - http://www.scopus.com/inward/record.url?scp=85217164623&partnerID=8YFLogxK
U2 - 10.1007/s11081-024-09940-1
DO - 10.1007/s11081-024-09940-1
M3 - Article
JO - Optimization and Engineering
JF - Optimization and Engineering
SN - 1389-4420
M1 - 100014
ER -