A Comparative study of metaheuristic algorithms in the identification of structural damage in composite beams

Mon, 02 Dec 2024 00:00:00 +0700

Structural damage, whether visible or hidden, is an inevitable occurrence in all structures, machines, and tools, arising from factors such as machining processes, wear, and impact. Over the years, significant efforts in structural dynamics have been devoted to evaluating and reconciling numerical models with experimental data to accurately detect and quantify such damage. This study presents a comprehensive approach to identifying and quantifying structural damage in multilayer composite beams by first assessing the global modal and frequency differences between undamaged and damaged structures using the Frequency Response Function (FRF) method. These results are then utilized in various metaheuristic optimization algorithms to precisely detect and quantify the extent of the damage. The focus of this work is to evaluate the effectiveness of three optimization algorithms: the African Vulture Optimization Algorithm (AVOA), the Salp Swarm Algorithm (SSA), and the Whale Optimization Algorithm (WOA). These algorithms are tested on a composite structure to determine their accuracy and computational efficiency in identifying structural damage.

Crack detection in concrete structures using standard deviation of discrete wavelet transform

Morteza Saadatmorad, Samir Khatir, Bochra Khatir — Tue, 03 Dec 2024 00:00:00 +0700

Crack detection in concrete structures is an important issue in the maintenance and repair operations of the structures. Detecting and distinguishing cracks in concrete can help determine the structure's health and prevent the possibility of structural failure. An efficient method for separating cracks in concrete is to use wavelet transform. This paper proposes a new crack detection technique based on a two-dimensional discrete wavelet transform and the standard deviation obtained from its detail signals to select an optimum wavelet function. According to our findings, there is a significant relation between the statistical index standard deviation and the desired detail signal obtained from the two-dimensional discrete wavelet transform for selecting the optimum wavelet function. Specifically, results show that as the standard deviation of the matrix of detail signal increases by a given wavelet function, crack detection resolution increases by that wavelet function.

HCMCOU Journal of Science – Advances in Computational Structures

A Comparative study of metaheuristic algorithms in the identification of structural damage in composite beams

Crack detection in concrete structures using standard deviation of discrete wavelet transform