Vibration-based damage detection methods have become widely used because of their advantages over traditional methods. This paper presents a new approach to identify the crack depth in steel beam ...structures based on vibration analysis using the Finite Element Method (FEM) and Artificial Neural Network (ANN) combined with Butterfly Optimization Algorithm (BOA). ANN is quite successful in such identification issues, but it has some limitations, such as reduction of error after system training is complete, which means the output does not provide optimal results. This paper improves ANN training after introducing BOA as a hybrid model (BOA-ANN). Natural frequencies are used as input parameters and crack depth as output. The data are collected from improved FEM using simulation tools (ABAQUS) based on different crack depths and locations as the first stage. Next, data are collected from experimental analysis of cracked beams based on different crack depths and locations to test the reliability of the presented technique. The proposed approach, compared to other methods, can predict crack depth with improved accuracy.
In recent decades, swarm optimization methods have been employed to address various optimization problems in structural health monitoring (SHM). One of the widely recognized swarm-based algorithms, ...particle swarm optimization (PSO), has gained significant popularity and found extensive applications across diverse fields. However, it presents some limitations, such as the low convergence rate in the iterative process. The butterfly optimization algorithm (BOA) is a recently developed algorithm that has demonstrated its performance in solving a variety of optimization problems. In this research, a novel hybrid swarm optimization algorithm is introduced, integrating PSO and BOA, with the aim of enhancing its effectiveness. To overcome the limitations of the traditional Artificial Neural Network (ANN) technique and enhance its training performance, this new hybrid algorithm is integrated with ANN. The study offers valuable insights into the creation of a predictive model, known as PSO-BOA-ANN, for detecting structural damage. Input parameters for the model include natural frequencies, while the output parameter is the severity of the damage. To test the efficiency of the proposed technique, data were collected from a finite element model using a simulation tool, and from frequency response function (FRF) after experimental modal analysis for single and double cracked aluminum beams considering different crack depths. A comparative analysis was conducted between the results obtained from PSO, BOA, GA, and their respective combinations with ANN. The findings indicate that the novel PSO-BOA-ANN approach outperforms the other approaches in terms of accuracy when it comes to damage prediction.
The durability and simplicity of the programming of meta-heuristic algorithms make them important in the optimization field. This paper presents a novel application for double cracks identification ...in Carbon Fiber Reinforced Polymer (CFRP) cantilever beams based on experimental and numerical analyses using enhanced optimization techniques. A new hybrid algorithm Particle Swarm Optimization and YUKI (PSO-YUKI) is proposed and combined with Radial Basis Functions (RBF) for solving fast inverse problems. The direct problem is based on the results of the dynamic experimental test of CFRP laminate, measuring the dynamics characteristics of a healthy beam, and the variation in the response corresponding to different scenarios of double cracks with different depths. The Finite Element Method (FEM) is used to simulate this vibrational behavior considering double cracks in different locations. The goal is creating an accurate damage identification method that has a high computational performance, based on the idea of building models that combines the vibrational responses issued from the experiments and simulations. The suggested method is tested based on collected data from numerical and experimental modal analyses in the case of undamaged and damaged CFRP laminates to demonstrate its accuracy and efficiency. The provided results show the robustness of PSO-YUKI compared with PSO for double cracks depth identification. The Matlab Code of PSO-YUKI can be found at https://github.com/Samir-Khatir/Hybrid-PSO-YUKI-.git.
Damage detection and localization in civil engineering constructions using dynamic analysis has become an important topic in recent years. This paper presents a methodology based on non-destructive ...detection, localization and quantification of multiple damages in simple and continuous beams, and a more complex structure, namely two-dimensional frame structure. The proposed methodology makes used of Firefly Algorithm and Genetic Algorithm as optimization tools and the Coordinate Modal Assurance Criterion as an objective function. The results show that the proposed combination of Coordinate Modal Assurance Criterion and Firefly Algorithm or Genetic Algorithm can be easily used to identify multiple local structural damages in complex structures. However, the convergence rate becomes slower for the case of multiple damages compared to the case of single damage. The effect of noise on the algorithm is further investigated. It is found that the proposed technique is able to detect the damage location and its severity with high accuracy in the presence of noise, although the convergence rate became slower than in the case when no noise is present. It is also found that the convergence rate of Firefly Algorithm is much faster than that of Genetic Algorithm.
Damage detection and localization in civil engineering constructions using dynamic analysis has become an important topic in recent years. This paper presents a methodology based on non-destructive ...detection, localization and quantification of multiple damages in simple and continuous beams, and a more complex structure, namely two-dimensional frame structure. The proposed methodology makes used of Firefly Algorithm and Genetic Algorithm as optimization tools and the Coordinate Modal Assurance Criterion as an objective function. The results show that the proposed combination of Coordinate Modal Assurance Criterion and Firefly Algorithm or Genetic Algorithm can be easily used to identify multiple local structural damages in complex structures. However, the convergence rate becomes slower for the case of multiple damages compared to the case of single damage. The effect of noise on the algorithm is further investigated. It is found that the proposed technique is able to detect the damage location and its severity with high accuracy in the presence of noise, although the convergence rate became slower than in the case when no noise is present. It is also found that the convergence rate of Firefly Algorithm is much faster than that of Genetic Algorithm.
Damage detection and localization in civil engineering constructions using dynamic analysis has become an important topic in recent years. This paper presents a methodology based on non-destructive ...detection, localization and quantification of multiple damages in simple and continuous beams, and a more complex structure, namely two-dimensional frame structure. The proposed methodology makes used of Firefly Algorithm and Genetic Algorithm as optimization tools and the Coordinate Modal Assurance Criterion as an objective function. The results show that the proposed combination of Coordinate Modal Assurance Criterion and Firefly Algorithm or Genetic Algorithm can be easily used to identify multiple local structural damages in complex structures. However, the convergence rate becomes slower for the case of multiple damages compared to the case of single damage. The effect of noise on the algorithm is further investigated. It is found that the proposed technique is able to detect the damage location and its severity with high accuracy in the presence of noise, although the convergence rate became slower than in the case when no noise is present. It is also found that the convergence rate of Firefly Algorithm is much faster than that of Genetic Algorithm.
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