Multiple damage detection and localization in beam-like and complex structures using co-ordinate modal assurance criterion combined with firefly and genetic algorithms

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

Residual Force Method for damage identification in a laminated composite plate with different boundary conditions

The strongest point about damage identification based on the dynamic measurements, is the ability perform structural health evaluation globally. Researchers in the last few years payed more attention to damage indicators based on modal analysis using either frequencies, mode shapes, or Frequency Response Functions (FRFs). This paper presents a new application of damage identification in a cross-ply (0°/90°/0°) laminated composite plate based on Force Residual Method (FRM) damage indicator. Considering single and multiple damages with different damage levels. As well as investigating the SSSS and CCCC boundary conditions effect on the estimation accuracy. Moreover, a white Gaussian noise is introduced to test the challenge the technique. The results show that the suggested FRM indicator provides accurate results under different boundary conditions. Favouring the SSSS boundary condition than the CCCC for 3% noise

Numerical study for single and multiple damage detection and localization in beam-like structures using BAT algorithm

This paper presents a new damage detection and localization technique based on the changes in vibration parameters using BAT and Particle Swarm Optimization algorithm. The finite element method is used to apply damage at specific element(s) of the considered beams. The damage is represented by a reduction in Young’s modulus and the identification of damage is formulated as an optimization problem using objective function based on Modal Scale Factor and changes in natural frequencies. A procedure for detecting and locating damage of beam-like structures based on BAT algorithm is used. This approach presents a method that can be used to detect the single and multiple-damage positions and the rate of damage in structural elements with high accuracy after the first iteration. The results obtained using BAT algorithm are compared to those obtained using Particle Swarm Optimization Algorithm. By taking noise into account in the damage detection and localization problem, it is shown that our approach based on BAT algorithm can detect the damage locations with high accuracy

Numerical study for single and multiple damage detection and localization in beam-like structures using BAT algorithm

This paper presents a new damage detection and localization technique based on the changes in vibration parameters using BAT and Particle Swarm Optimization algorithm. The finite element method is used to apply damage at specific element(s) of the considered beams. The damage is represented by a reduction in Young's modulus and the identification of damage is formulated as an optimization problem using objective function based on Modal Scale Factor and changes in natural frequencies. A procedure for detecting and locating damage of beam-like structures based on BAT algorithm is used. This approach presents a method that can be used to detect the single and multiple-damage positions and the rate of damage in structural elements with high accuracy after the first iteration. The results obtained using BAT algorithm are compared to those obtained using Particle Swarm Optimization Algorithm. By taking noise into account in the damage detection and localization problem, it is shown that our approach based on BAT algorithm can detect the damage locations with high accuracy

Multiple damage detection in composite beams using particle swarm optimization and genetic algorithm

This paper presents a methodology for damage detection and localization in composite beams using vibration data, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The data was acquired by developing a program that performs dynamic analysis of unidirectional graphite -epoxy composite beams based on the Finite Element Method (FEM). The objective function makes use of natural frequencies and Modal Assurance Criterion. The proposed methodology is validated using numerically simulated data and experimental data. A comparative study between the performances of PSO and GA in detecting multiple and single damage scenarios is carried out. Then, the effect of noise is investigated by taking different noise levels in the modal data It appears that the noise has a negligible effect on the performance of the presented approaches

Republished Paper. Multiple damage detection and localization in beam-like and complex structures using co-ordinate modal assurance criterion combined with firefly and genetic algorithms

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

RC beams damaged by cracking and strengthened with NSM CFRP/GFRP rods

The near surface mounted (NSM) method of inserting fiber reinforced polymer (FRP) elements (rods or lamina) into notches has been shown to be a good way for restoring reinforced concrete (RC) elements. The knowledge about the use of Glass-FRP rod following the NSM to reinforce RC beams is limited. This paper deals with the analysis of static and dynamic behaviour of RC beams with and without strengthening. The response of RC beams was assessed at different concrete’s damage level by non-destructive vibration tests. First, a couple of beams have been analysed: one RC beam subjected to bending and under vibration tests; another one beam, damaged by bending and strengthened with NSM Carbon-FRP rods tested again under vibration. Further, one RC beam damage was analysed under bending and vibration tests without strengthening; successively, the beam model with NSM GFRP rod has been tested following the same loading path. Below experimental results are shown and commented; in particular, changes in frequency values are related to the evolution of damage level affected RC beams with NSM CFRP and GFRP rods

Experimental sensitivity analysis of sensor placement based on virtual springs and damage quantification in CFRP composite

This paper suggests a method for vibration sensor placement in Carbon Fibre Reinforced Polymer (CFRP) composite structures in small structure applications where the measuring instrument weight can affect the vibrational characteristics. Considering the actual weight of the beam and the actual weight of the vibrational sensor and connecting cables. We performed a set of structural vibration experiments in various sensor positions and used the experimental results as a reference through the inverse problems technique. And Finite Element Analysis (FEA) for numerical modelling, in which the sensors are modelled as an additional mass on the beam and the virtual springs are modelled with variable rigidity. We employ the Teaching-Learning-Based Optimization Algorithm (TLBO) to identify the optimal sensor placement location. The results indicate that this application can explain the effect of sensor placement. In a second application, we consider the problem of the cracked beam and the prediction of damage severity and crack depth with the help of a formulation for crack location. Results of this Application show that the proposed approach can serve in solving both problems.

Experimental sensitivity analysis of sensor placement based on virtual springs and damage quantification in CFRP composite

This paper suggests a method for vibration sensor placement in Carbon Fibre Reinforced Polymer (CFRP) composite structures in small structure applications where the measuring instrument weight can affect the vibrational characteristics. Considering the actual weight of the beam and the actual weight of the vibrational sensor and connecting cables. We performed a set of structural vibration experiments in various sensor positions and used the experimental results as a reference through the inverse problems technique. And Finite Element Analysis (FEA) for numerical modelling, in which the sensors are modelled as an additional mass on the beam and the virtual springs are modelled with variable rigidity. We employ the Teaching-Learning-Based Optimization Algorithm (TLBO) to identify the optimal sensor placement location. The results indicate that this application can explain the effect of sensor placement. In a second application, we consider the problem of the cracked beam and the prediction of damage severity and crack depth with the help of a formulation for crack location. Results of this Application show that the proposed approach can serve in solving both problems.