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The purpose of this paper is to provide an effective and simple technique to structural damage identification, particularly to identify a crack in a structure. Artificial neural networks approach is an alternative to identify the extent and location of the damage over the classical methods. Radial basis function (RBF) networks are good at function mapping and generalization ability among the various neural network approaches. RBF neural networks are chosen for the present study of crack identification.

Analyzing the vibration response of a structure is an effective way to monitor its health and even to detect the damage. A novel two‐stage improved radial basis function (IRBF) neural network methodology with conventional RBF in the first stage and a reduced search space moving technique in the second stage is proposed to identify the crack in a cantilever beam structure in the frequency domain. Latin hypercube sampling (LHS) technique is used in both stages to sample the frequency modal patterns to train the proposed network. Study is also conducted with and without addition of 5% white noise to the input patterns to simulate the experimental errors.

The results show a significant improvement in identifying the location and magnitude of a crack by the proposed IRBF method, in comparison with conventional RBF method and other classical methods. In case of crack location in a beam, the average identification error over 12 test cases was 0.69 per cent by IRBF network compared to 4.88 per cent by conventional RBF. Similar improvements are reported when compared to hybrid CPN BPN networks. It also requires much less computational effort as compared to other hybrid neural network approaches and classical methods.

The proposed novel IRBF crack identification technique is unique in originality and not reported elsewhere. It can identify the crack location and crack depth with very good accuracy, less computational effort and ease of implementation.

The early detection of cracks, corrosion and structural failure in aging structures is one of the major challenges in the civil, mechanical and aircraft industries. Common inspection techniques are time consuming and hence can have strong economic implications due to downtime. The paper aims to discuss these issues.

As a result, during the past decade a number of methodologies have been proposed for detecting crack in structure based on variations in the structure's dynamic characteristics. This work showcases the efficacy of particle swarm optimization (PSO) and genetic algorithm (GA) in damage assessment of structures.

Efficiency of these tools has been tested on structures like beam, plane and space truss. The results show the effectiveness of PSO in crack identification and the possibility of implementing it in a real-time structural health monitoring system for aircraft and civil structures.

The methodology presented establishes the PSO as robust and competent tool over GA for crack identification using changes in natural frequencies.

This study aimed to solve the engineering problem of free vibration disturbance and local mesh refinement induced by microcrack damage in circularly curved beams. The accurate identification of the crack damage depth, number and location depends on high-precision frequency and vibration mode solutions; therefore, it is critical to obtain these reliable solutions. The high-precision finite element method for the free vibration of cracked beams needs to be developed to grasp and control error information in the conventional solutions and the non-uniform mesh generation near the cracks. Moreover, the influence of multi-crack damage on the natural frequency and vibration mode of a circularly curved beam needs to be detected.

A scheme for cross-sectional damage defects in a circularly curved beam was established to simulate the depth, location and the number of multiple cracks by implementing cross-section reduction induced by microcrack damage. In addition, the h-version finite element mesh adaptive analysis method of the Timoshenko beam was developed. The superconvergent solution of the vibration mode of the cracked curved beam was obtained using the superconvergent patch recovery displacement method to determine the finite element solution. The superconvergent solution of the frequency was obtained by computing the Rayleigh quotient. The superconvergent solution of the eigenfunction was used to estimate the error of the finite element solution in the energy norm. The mesh was then subdivided to generate an improved mesh based on the error. Accordingly, the final optimised meshes and high-precision solution of natural frequency and mode shape satisfying the preset error tolerance can be obtained. Lastly, the disturbance behaviour of multi-crack damage on the vibration mode of a circularly curved beam was also studied.

Numerical results of the free vibration and damage disturbance of cracked curved beams with cracks were obtained. The influences of crack damage depth, crack damage number and crack damage distribution on the natural frequency and mode of vibration of a circularly curved beam were quantitatively analysed. Numerical examples indicate that the vibration mode and frequency of the beam would be disturbed in the region close to the crack damage, and a greater crack depth translates to a larger frequency change. For multi-crack beams, the number and distribution of cracks also affect the vibration mode and natural frequency. The adaptive method can use a relatively dense mesh near the crack to adapt to the change in the vibration mode near the crack, thus verifying the efficacy, accuracy and reliability of the method.

The proposed combination of methodologies provides an extremely robust approach for free vibration of beams with cracks. The non-uniform mesh refinement in the adaptive method can adapt to changes in the vibration mode caused by crack damage. Moreover, the proposed method can adaptively divide a relatively fine mesh at the crack, which is applied to investigating free vibration under various curved beam angles and crack damage distribution conditions. The proposed method can be extended to crack damage detection of 2D plate and shell structures and three-dimensional structures with cracks.

The purpose of this paper is to provide an effective and simple technique for structural parameter identification, particularly to identify multiple cracks in a structure using simultaneous measurement of acceleration responses and voltage signals from PZT patches which is a multidisciplinary approach. A hybrid element constituted of one-dimensional beam element and a PZT sensor is used with reduced material properties which is very convenient for beams and is a novel application for inverse problems.

Multi-objective formulation is used whereby structural parameters are identified by minimizing the deviation between the predicted and measured values from the PZT patch and acceleration responses, when subjected to excitation. In the proposed method, a patch is attached to either end of the fixed beam. Using particle swarm optimization algorithm, normalized fitness functions are defined for both voltage and acceleration components with weighted aggregation multi-objective optimization technique. The signals are polluted with 5 percent Gaussian noise to simulate experimental noise. The effects of various weighting factors for the combined objective function are studied. The scheme is also experimentally validated by identification of cracks in a fixed-fixed beam.

The numerical and experimental results shows that significant improvement in accuracy of damage detection is achieved by the combined multidisciplinary method, when compared with only voltage or only acceleration-matching method as well as with other methods.

The proposed multidisciplinary crack identification approach, which is based on one-dimensional PZT patch model as well as conventional acceleration method, is not reported in the literature.

This study aims to develop a numerical identification and characterization of crack propagation through the use of a new optimization metaheuristics called Lichtenberg optimization.

The damage-identification problem is treated as an inverse problem, which combines finite element methods with intelligent computational methods to obtain the best possible response. To optimize the objectives, the Lichtenberg algorithm is applied, which includes concepts of random cluster growth in nature.

The simulations show that it is possible to determine the Lichtenberg spectrum algorithm a part of the structure to be removed and replaced in this case to stop the propagation.

The results show a very good crack identification in plates-like structures using the Lichtenberg algorithm (LA) based only in strain fields. Although many studies have reported on damage-identification-based optimization methods, very few have focused on the crack tip modeling and LA as the main solver.

The problem of damage and crack detection in structural components has acquired an important role in recent years. Since the presence of cracks in a structure may alter its vibrational characteristics, the estimation of such variations can be used to detect cracks and damage, and to monitor the integrity of structures. The use of fast, easy and inexpensive non‐destructive testing is thus a major task. In this paper, sensitivity analysis by measurement of the reduction of eigenfrequencies was utilized to localize a crack in a non‐rotating shaft coupled to an elastic foundation. The shaft was modeled by the finite element method and coupled to an experimentally identified foundation model. The detection of a crack with different depths and orientations was verified experimentally and a good agreement between actual and detected crack positions was achieved. Finally easiness, effectiveness, applicability of the method and its extensions are also shown.

This paper aims to study the influence of different reinforcement methods on crack monitoring characteristics of eddy current array sensors, and the sensors with two different reinforcement methods, SUS304 reinforcement and permalloy reinforcement, are proposed.

First, the finite element model of the sensor is established to analyze the influence of the reinforcement plate’s electromagnetic parameters on the crack identification sensitivity. Then, the crack monitoring accuracy test of sensors with two reinforcement methods is carried out. Finally, the fatigue crack monitoring experiments with bolt tightening torques of 45 and 63 N · m are carried out, respectively.

In this study, it is found that the crack identification sensitivity of the sensor can be improved by increasing the relative permeability of the reinforcement plate. The crack monitoring accuracy of the sensors with two different reinforcement methods is about 1 mm. And the crack identification sensitivity of the sensor reinforced by permalloy reinforcement plate is significantly higher than that of the sensor reinforced by SUS304 reinforcement plate.

The sensor reinforced by reinforcement plate can work normally under the squeezing action of the bolt, and the crack monitoring sensitivity of the sensor can be significantly improved by using the reinforcement plate with high relative permeability.

Health monitoring of concrete is one of the important tasks in the structural health monitoring. The life of any infrastructure relies on the quality of the concrete. The computer vision-based methods are very useful to identify the structural defects. The identification of minor cracks in the noisy concrete image is complex. The purpose of this paper is to denoise the concrete crack images and also segment the cracks.

The novelty of the proposed work lies on the usage of anisotropic diffusion filter in the noisy concrete images. Initially anisotropic diffusion filter is applied to smoothen the concrete images. Adaptive threshold and gray level-based edge stopping constant are used in the diffusion process. The statistical six sigma-based method is utilized to segment the cracks from smoothened concrete images.

The proposed method is compared with five state-of-the-art-methods with the performance metrics of mean square error, peak signal to noise ratio and mean structural similarity. The experimental results highlight the advantages of the proposed method.

The novelty of the proposed work lies on the usage of anisotropic diffusion filter in the noisy concrete images. This research work gives the scope for structural damage evaluation by the automation techniques.

The purpose of this paper is to employ analytical and numerical techniques to generate modal displacement data of damaged beams containing very small crack-like surface flaws or slots and to use the data in the development of damage detection methodology. The detection method involves the use of double differentiation of the modal data for identification of the flaw location and magnitude.

The modal displacements of damaged beams are simulated analytically using the Bernoulli-Euler theory and numerically using the finite element method. The principle used in the analytical approach is based on changes in the transverse displacement due to the localized reduction of the flexural rigidity of the beam. Curvature analysis is employed to identify and locate the structural flaws from the modal data. The curvature mode shapes are calculated using a central difference approximation. The effects of random noise on the detectability of the structural flaws are also computed.

The analytical approach is much more robust in simulating modal displacement data for beams with crack-like surface flaws or slots than the finite element analysis (FEA) approach especially for crack-like surface flaws or slots of very small depths. The structural flaws are detectable in the presence of random noise of up to 5 per cent.

Simulating the effects of small crack-like surface flaws is important because it is essential to develop techniques to detect cracks at an early stage of their development. The FEA approach can only simulate the effects of crack-like surface flaws or slots with depth ratio greater than 10 per cent. On the other hand, the analytical approach using the Bernoulli-Euler theory can simulate the effects of crack-like surface flaws or slots with depth ratio as small as 2 per cent.

Moderately thick circular cylindrical shells are widely used as supporting structures or storage cavities in structural engineering, rock engineering, and aerospace engineering. In practical engineering, shells often work with micro-cracks or defects. The existence of micro-crack damage may result in the disturbance of dynamic behaviours and even induce accidental dynamic disasters. The free vibration frequency and mode are important parameters for the dynamic performance and damage identification analysis. In particular, stiffness weakening of the local damage region leads to significant changes in the vibration mode, which makes it difficult for the mesh generated in the conventional finite element method to capture a high-precision solution of the local oscillation.

In response to the above problems, this study developed an adaptive finite element method and a crack damage characterisation method for moderately thick circular cylindrical shells. By introducing the inverse power iteration method, error estimation, and mesh subdivision refinement technique for the analysis of finite element eigenvalue problems, an adaptive computation scheme was constructed for the free vibration problem of moderately thick circular cylindrical shells with circumferential crack damage.

Based on typical numerical examples, the established adaptive finite element solution for the free vibration of moderately thick circular cylindrical shells demonstrated its suitability for solving the high-precision free vibration frequency and mode of cylindrical shell structures. The any order frequency and mode shape of cracked cylindrical shells under the conditions of different ring wave numbers, crack locations, crack depths, and multiple cracks were successfully solved. The influences of the location, depth, and number of cracks on the disturbance of dynamic behaviours were analysed.

This study can be used as a reference for the adaptive finite element solution of free vibration of moderately thick circular cylindrical shells with cracks and lays the foundation for further development of a high-performance computation method suitable for the dynamic disturbance and damage identification analysis of general cracked structures.