Multiverse optimizer for structural damage detection: Numerical study and experimental validation

doi:10.1002/tal.1777

Multiverse optimizer for structural damage detection: Numerical study and experimental validation

2020-07-11

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DOI：10.1002/tal.1777

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SummaryNew optimization algorithms have been increasingly developed in the course of the recent years. The accuracy of identified results in optimization‐based damage detection methods depends on the objective function and optimization algorithm. This paper employs multiverse Optimizer (MVO) to solve the optimization‐based damage identification problem. Statistical results obtained by MVO are compared with those of sine cosine algorithm (SCA) and Harris hawks optimization (HHO) in order to perform a comparative study. Two objective functions are used in this optimization problem. The first one is based on the modal assurance criterion (MAC) and the second one on modified total modal assurance criterion (MTMAC). Numerical and experimental examples indicate that the combination of objective function based on MTMAC and MVO algorithm can provide accurate and reliable results in structural damage detection process. MAC is also rejected in competition with MTMAC. While using SCA‐MTMAC, the accuracy of the results is acceptable in some cases. However, HHO‐MTMAC gives weak results in most cases. MVO and SSA are the lowest, and HHO spends significantly more time in terms of computational cost.

Multiverse optimizer for structural damage detection: Numerical study and experimental validation

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