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| Advances in Engineering Software |
An improved hybrid optimization algorithm for vibration based-damage etection
abstract
In this paper, an improvement in the hybrid stochastic/deterministic Pincus-Nelder-Mead optimization algo-rithm (P-NMA) which enables to solve the target optimization problem of vibration-based damage detectionis proposed.
The proposed modification consists in reducing the sampling domain of the Pincus formula by assigning a maximum number of damaged elements, i.e., by allowing only a few elements of the sampling vector to be different from.
Consequently, a new parameter which determines the maximum number of damaged elements (npmax) is introduced and must be choose by the designer. Such a modification attempts to speed up the convergence of the original version of the P-NMA and thus, reducing its computational cost.
A series of numerical examples, all selected from literature, was performed. To test the accuracy and efficiency of the proposed improved optimization algorithm (IP-NMA), its results were compared to those obtained by the P-NMA and the metaheuristic harmony search algorithm (HS). A statistical analysis was also performed in order to test the robustness of the three algorithms.
The proposed improved optimization algorithm showed better performance (more accurate and required lower computational cost than the original version of the P-NMA and the metaheuristic HS), emphasizing its capacity in damage diagnosis and assessment.
Introduction
It is recognized that efficient methods to detect and quantify structural damage generate a wide interest in the civil, mechanical and aerospace fields. Thus, the application of robust procedures in programs to restore the reliability of engineering structures to ini- tial design levels is highly desired.
One method that may fulfill those requirements is dynamic non-destructive testing, which consists of monitoring the modal properties (e.g., natural frequencies, vibration modes and damping) during the lifetime of a structure. Several strate- gies have been reported in the vibration-based damage detection field.
For instance, local damage detection using dynamic SOFO experi- mental data and damage assessment from SOFO dynamic measure- ments were used by Casciati et al, from responses recorded on the structure before and after a seismic event, damage detection through Micro-Electro-Mechanical System (MEMS) and Operational Deformed Shapes (ODS) were used by Domaneschi et al., dam- age detection under ambient vibration by Miguel et al., to name just a few. Even considering the recent developments of vibration- based damage detection techniques and the results of numerous studies with different degrees of success, this problem cannot be con- sidered fully addressed and remains a challenging task.
Special atten-tion and additional work should be dedicated to develop robust and accurate techniques that are able to minimize numerical errors, thus smoothing false positive damage diagnoses.
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