• Smart Structures and Systems
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• v.15 no.5
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• pp.1253-1270
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• 2015

In this paper Magnetic Charged System Search (MCSS) and Particle Swarm Optimization (PSO) are applied to the problem of damage detection using frequencies and mode shapes of the structures. The objective is to identify the location and extent of multi-damage in structures. Both natural frequencies and mode shapes are used to form the required objective function. To moderate the effect of noise on measured data, a penalty approach is applied. A variety of numerical examples including two beams and two trusses are considered. A comparison between the PSO and MCSS is conducted to show the efficiency of the MCSS in finding the global optimum. The results show that the present methodology can reliably identify damage scenarios using noisy measurements and incomplete data.

• Structural Monitoring and Maintenance
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• v.5 no.4
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• pp.507-519
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• 2018

In this paper, damage assessment in wind-turbine towers using vibration-based artificial neural networks (ANNs) is numerically investigated. At first, a vibration-based ANNs algorithm is designed for damage detection in a wind turbine tower. The ANNs architecture consists of an input, an output, and hidden layers. Modal parameters of the wind turbine tower such as mode shapes and frequencies are utilized as the input and the output layer composes of element stiffness indices. Next, the finite element model of a real wind-turbine tower is established as the test structure. The natural frequencies and mode shapes of the test structure are computed under various damage cases of single and multiple damages to generate training patterns. Finally, the ANNs are trained using the generated training patterns and employed to detect damaged elements and severities in the test structure.

• Earthquakes and Structures
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• v.13 no.6
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• pp.539-549
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• 2017

Existing reinforced concrete frame buildings designed for vertical loads could only suffer severe damage during earthquakes. In recent years, many research activities were undertaken to develop a reliable and practical analysis procedure to identify the safety level of existing structures. The Incremental Dynamic Analysis (IDA) is considered to be one of the most accurate methods to estimate the seismic demand and capacity of structures. However, the executions of many nonlinear response history analyses (NL_RHA) are required to describe the entire range of structural response. The research discussed in this paper deals with the proposal of an efficient Incremental Modal Pushover Analysis (IMPA) to obtain capacity curves by replacing the nonlinear response history analysis of the IDA procedure with Modal Pushover Analysis (MPA). Firstly, In this work, the MPA is examined and extended to three-dimensional asymmetric structures and then it is incorporated into the proposed procedure (IMPA) to estimate the structure's seismic response and capacity for given seismic actions. This new procedure, which accounts for higher mode effects, does not require the execution of complex NL-RHA, but only a series of nonlinear static analysis. Finally, the extended MPA and IMPA were applied to an existing irregular framed building.

• Smart Structures and Systems
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• v.3 no.1
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• pp.23-49
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• 2007

Wavelet transforms are the emerging signal-processing tools for damage identification and time-frequency localization. A small perturbation in a static or dynamic displacement profile could be captured using multi-resolution technique of wavelet analysis. The paper presents the wavelet analysis of damaged linear structural elements using DB4 or BIOR6.8 family of wavelets. Starting with a localized reduction of EI at the mid-span of a simply supported beam, damage modeling is done for a typical steel and reinforced concrete beam element. Rotation and curvature mode shapes are found to be the improved indicators of damage and when these are coupled with wavelet analysis, a clear picture of damage singularity emerges. In the steel beam, the damage is modeled as a rotational spring and for an RC section, moment curvature relationship is used to compute the effective EI. Wavelet analysis is performed for these damage models for displacement, rotation and curvature mode shapes as well as static deformation profiles. It is shown that all the damage indicators like displacement, slope and curvature are magnified under higher modes. A localization scheme with arbitrary location of curvature nodes within a pseudo span is developed for steady state dynamic loads, such that curvature response and damages are maximized and the scheme is numerically tested and proved.

• Structural Engineering and Mechanics
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• v.75 no.5
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• pp.585-594
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• 2020

Detecting the damage of indeterminate trusses is of major importance in the literature. This paper proposes a quick approach in this regard, utilizing a precise mathematical approach based on Finite Element Method. Different to a general two-step method defined in the literature essentially based on optimization approach, this method consists of three steps including Damage-Suspected Element Identification step, Imminent Damaged Element Identification step, and finally, Damage Severity Detection step and does not need any optimizing algorithm. The first step focuses on the identification of damage-suspected elements using an index based on modal residual force vector. In the second step, imminent damage elements are identified among the damage-suspected elements detected in the previous step using a specific technique. Ultimately, in the third step, a novel relation is derived to calculate the damage severity of each imminent damaged element. To show the efficiency and quick function of the proposed method, three examples including a 25-bar planar truss, a 31-bar planar truss, and a 52-bar space truss are studied; results of which indicate that the method is innovatively capable of suitably detecting, for indeterminate trusses, not only damaged elements but also their individual damage severity by carrying out solely one analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.218-226
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• 2020

An experimental study was conducted on baseline model updating and damage estimation techniques for the health monitoring of offshore wind turbine tripod substructures. First, a procedure for substructure health monitoring was proposed. An initial baseline model for a scaled model of a tripod substructure was established. A baseline model was updated based on the natural frequencies and the mode shapes measured in the healthy state. A training pattern was then generated using the updated baseline model, and the damage was estimated by inputting the modal parameters measured in the damaged state into the trained neural network. The baseline model could be updated reasonably using the effective fixity model. The damage tests were performed, and the damage locations could be estimated reasonably. In addition, the estimated damage severity also increased as the actual damage severity increased. On the other hand, when the damage severity was relatively small, the corresponding damage location was detected, but it was more difficult to identify than the other cases. Further studies on small damage estimation and stiffness reduction quantification will be needed before the presented method can be used effectively for the health monitoring of tripod substructures.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.9-16
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• 2010

In the health monitoring of civil engineering structures, the optimal sensor placement has a major influence on the quality of the results. This paper considers the problem of locating sensors with the aim of maximizing the data information so that structural parameters or damage of structures can be assessed. An proposed technique using a genetic algorithm is introduced to find the optimal placement of sensors. The sensitivity on modal vectors by structural parameters and the orthogonality of modal vectors have been taken as the fitness function of the genetic algorithm. A simple tower structure is used for example analyses to investigate the feasibility and applicability of the proposed approach. The example analyses show the way how the modal sensitivity and the modal orthogonality in the fitness function have influence on the optimal sensor placement. It is shown that the present method using the proposed fitness function can provide the reliable results.

• Structural Engineering and Mechanics
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• v.44 no.1
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• pp.51-60
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• 2012

Concrete sleepers are essential components of the conventional railway. As support elements, sleepers are always subjective to a variety of time-dependent loads attributable to the train operations, either wheel or rail abnormalities. It has been observed that the sleepers may deteriorate due to these loads, inducing the formation of hairline cracks. There are two areas along the sleepers that are more prone to crack: the central and the rail seat sections. Several non-destructive methods have been developed to identify failures in structures. Health monitoring techniques are based on vibration responses measurements, which help engineers to identify the vibration-based damage or remotely monitor the sleeper health. In the present paper, the dynamic effects of the cracks in the vibration signatures of the railway pre-stressed concrete sleepers are investigated. The experimental modal analysis has been used to evaluate the modal bending changes in the vibration characteristics of the sleepers, differentiating between the central and the rail seat locations of the cracks. Modal parameters changes of the 'healthy' and cracked sleepers have been highlighted in terms of natural frequencies and modal damping. The paper concludes with a discussion of the most suitable failure indicator and it defines the vibration signatures of intact, central cracked and rail seat cracked sleepers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.12 s.243
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• pp.1586-1596
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• 2005

In this paper, a structural damage identification method (SDIM) is developed to identify the line crack-like directional damages generated within a cylindrical shell. First, the equations of motion for a damaged cylindrical shell are derived. Based on a theory of continuum damage mechanics, a small material volume containing a directional damage is represented by the effective orthotropic elastic stiffness, which is dependent of the size and the orientation of the damage with respect to the global coordinates. The present SDIM is then derived from the frequency response function (FRF) directly solved from the equations of motion of a damaged shell. In contrast with most existing SDIMs which require the modal parameters measured in both intact and damaged states, the present SDIM may require only the FRF-data measured at damaged state. By virtue of utilizing FRF-data, one may choose as many sets of excitation frequency and FRF measurement point as needed to acquire a sufficient number of equations for damage identification analysis. The numerically simulated damage identification tests are conducted to study the feasibility of the present SDIM.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.243-260
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• 2018

Detection of damages in fibre reinforced plastic (FRP) composite structures is important from the safety and serviceability point of view. Usually, damage is realized as a local reduction of stiffness and if dynamic responses of the structure are sensitive enough to such changes in stiffness, then a well posed inverse problem can provide an efficient solution to the damage detection problem. Usually, such inverse problems are solved within the framework of pattern recognition. Support Vector Machine (SVM) Algorithm is one such methodology, which minimizes the weighted differences between the experimentally observed dynamic responses and those computed using the finite element model- by optimizing appropriately chosen parameters, such as stiffness. A damage detection strategy is hereby proposed using SVM which perform stepwise by first locating and then determining the severity of the damage. The SVM algorithm uses simulations of only a limited number of damage scenarios and trains the algorithm in such a way so as to detect damages at unknown locations by recognizing the pattern of changes in dynamic responses. A rectangular fiber reinforced plastic composite plate has been investigated both numerically and experimentally to observe the efficiency of the SVM algorithm for damage detection. Experimentally determined modal responses, such as natural frequencies and mode shapes are used as observable parameters. The results are encouraging since a high percentage of damage cases have been successfully determined using the proposed algorithm.