@MISC{Raich_redundant,

author = {Anne Raich and Tamás Liszkai},

title = {Redundant},

year = {}

}

Abstract. A robust structural damage detection method that can handle noisy frequency response function information is discussed. The inherent unstructured nature of damage detection problems is exploited by applying an implicit redundant representation (IRR) genetic algorithm. The unbraced frame structure results obtained show that the IRR GA is less sensitive to noise than a SGA. 1 Unstructured Problem Domain of FRF-Based Damage Detection The goal of structural damage identification methods (SDIM) is to accurately assess the condition of structures. Most SDIMs assume that vibration signatures are sensitive indicators of structural integrity. In this research, FRF data was used to identify the location and severity of damage. An optimization problem was defined using an error function between the measured data and the discrete analytical model. Although the total number of structural elements typically is large, the number actually damaged is smaller. This unique situation defines an unstructured problem, in which the number of damages is unknown. The optimization problem is solved using genetic algorithms (GA) by altering member properties. A damage vector is obtained that identifies the location and severity of damage(s) in the structure. This formulation requires minimal measurement information. A comprehensive review of model parameter updating methods is provided in [1]. Two GA representations were investigated (Fig. 1). A fixed number of variables were encoded using a SGA representation to represent a complete solution by defining a damage indicator for each element. The IRR representation [2] considered the unstructured nature of damage detection by allowing the number of damaged elements to change during optimization, which is beneficial when the number and location of damages are unknown. A complete solution is encoded using only the damages for a small subset of the elements, instead of all elements.

genetic algorithm complete solution optimization problem frf-based damage detection discrete analytical model irr ga irr representation unbraced frame structure result comprehensive review implicit redundant representation unstructured problem error function structural damage identification method member property damage vector sga representation structural integrity inherent unstructured nature problem domain damage detection structural element frf data model parameter vibration signature fixed number damage detection problem damage indicator total number unstructured nature damaged element robust structural damage detection method small subset noisy frequency response function information sensitive indicator ga representation unique situation minimal measurement information

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