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A fast-convergent approach for damage assessment using CMA-ES optimization algorithm and modal parameters

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Abstract

This paper investigates the application and the performance of covariance matrix adaptation-evolution strategy (CMA-ES) in structural damage detection and quantification. Many of the proposed optimization algorithms cannot detect damages accurately when the dimensions of the optimization problems increase. In essence, they stick in local optimum points and need huge amount of time and effort to find the exact solution of the problem. For this study, a novel objective function was proposed for the optimization problem based on natural frequencies and mode shapes. The efficiency of the CMA-ES algorithm has been examined by comparing to results of particle swarm optimization, genetic algorithm, and multi-population genetic algorithm (MPGA). Furthermore, robustness of the method has been evaluated in the presence of noise. The algorithms have been applied to a truss structure and a frame structure with different damage scenarios. The results of the paper demonstrated that the CMA-ES method is able to identify damages with satisfactory precision. Also, it was seen that the CMA-ES optimization algorithm is faster, more accurate, and more reliable than other algorithms.

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Authors and Affiliations

  1. School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Behzad Ghahremani & Maryam Bitaraf

  2. School of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran

    Hossein Rahami

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  1. Behzad Ghahremani
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  2. Maryam Bitaraf
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Correspondence to Maryam Bitaraf.

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Ghahremani, B., Bitaraf, M. & Rahami, H. A fast-convergent approach for damage assessment using CMA-ES optimization algorithm and modal parameters. J Civil Struct Health Monit 10, 497–511 (2020). https://doi.org/10.1007/s13349-020-00397-1

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