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.

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

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

ER -