• Structural Engineering and Mechanics
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• 제35권2호
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• pp.257-260
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• 2010

• Smart Structures and Systems
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• 제12권6호
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• pp.679-694
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• 2013

In this paper the application of the Interpolation Damage Detection Method to the numerical model of a suspension bridge instrumented with a network of Micro-Electro-Mechanical System sensors is presented. The method, which, in its present formulation, belongs to Level II damage identification method, can identify the presence and the location of damage from responses recorded on the structure before and after a seismic damaging event. The application of the method does not require knowledge of the modal properties of the structure nor a numerical model of it. Emphasis is placed herein on the influence of recorded signals noise on the reliability of the results given by the Interpolation Damage Detection Method. The response of a suspension bridge to seismic excitation is computed from a numerical model and artificially corrupted with random noise characteristic of two families of Micro-Electro-Mechanical System accelerometers. The reliability of the results is checked for different damage scenarios.

• 한국구조물진단유지관리공학회 논문집
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• 제3권3호
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• pp.167-176
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• 1999

This paper is concerned with the damage detection of existing 2 and 3-dimensional truss structures based on free vibration equation and extended Kalman filter. The local damage is characterized in terms of the stiffness degradation of damaged members. As the observed data, the natural frequencies and mode shapes of damaged truss structure model are adopted. Both location and stiffness of damaged parts of members in truss structures can be estimated by the proposed inverse solution procedure. The applicability and effectiveness of proposed inverse solution procedure are demonstrated through the numerical examples.

• Smart Structures and Systems
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• 제5권6호
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• pp.681-697
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• 2009

Limited, noisy data in vibration testing is a hindrance to the development of structural damage detection. This paper presents a method for optimizing sensor placement and performing damage detection using finite element model updating. Sensitivity analysis of the modal flexibility matrix determines the optimal sensor locations for collecting information on structural damage. The optimal sensor locations require the instrumentation of only a limited number of degrees of freedom. Using noisy modal data from only these limited sensor locations, a method based on model updating and changes in the flexibility matrix successfully determines the location and severity of the imposed damage in numerical simulations. In addition, a steel cantilever beam experiment performed in the laboratory that considered the effects of model error and noise tested the validity of the method. The results show that the proposed approach effectively and robustly detects structural damage using limited, optimal sensor information.

• Smart Structures and Systems
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• 제31권1호
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• pp.29-43
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• 2023

This study investigates the possibility of damage detection of a real bridge by means of a modal parameter-based finite element (FE) model update. Field moving vehicle experiments were conducted on an actual steel plate girder bridge. In the damage experiment, cracks were applied to the bridge to simulate damage states. A fast Bayesian FFT method was employed to identify and quantify uncertainties of the modal parameters then these modal parameters were used in the Bayesian model update. Material properties and boundary conditions are taken as uncertainties and updated in the model update process. Observations showed that although some differences existed in the results obtained from different model classes, the discrepancy between modal parameters of the FE model and those experimentally obtained was reduced after the model update process, and the updated parameters in the numerical model were indeed affected by the damage. The importance of boundary conditions in the model updating process is also observed. The capability of the MCMC model update method for application to the actual bridge structure is assessed, and the limitation of FE model update in damage detection of bridges using only modal parameters is observed.

• Advances in aircraft and spacecraft science
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• 제4권6호
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• pp.613-637
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• 2017

The development systems for the Structural Health Monitoring has attracted considerable interest from several engineering fields during the last decades and more specifically in the aerospace one. In fact, the introduction of those systems could allow the transition of the maintenance strategy from a scheduled basis to a condition-based approach providing cost benefits for the companies. The research presented in this paper consists of a definition and next comparison of four methods applied to numerical measurements for the extraction of damage features. The first method is based on the determination of the Structural Intensity field at the on-resonance condition in order to acquire information about the dissipation of vibrational energy throughout the structure. The Damage Quantification Indicator and the Average Integrated Global Amplitude Criterion methods need the evaluation of the Frequency Response Function for a healthy plate and a damaged one. The main difference between these two parameters is their mathematical definition and therefore the accuracy of the scalar values provided as output. The fourth and last method is based on the Mode-shape Curvature, a FRF-based technique which requires the application of particular finite-difference schemes for the derivation of the curvature of the plate. All the methods have been assessed for several damage conditions (the shape, the extension and the intensity of the damage) on two test plates: an isotropic (steel) plate and a 4-plies composite plate.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.754-759
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• 2007

This study exploits the data discriminating capability of silhouette statistics, which combines wavelet-based vertical energy threshold technique for the purpose of extracting damage-sensitive features and clustering signals of the same class. This threshold technique allows to first obtain a suitable subset of the extracted or modified features of our data, i.e., good predictor sets should contain features that are strongly correlated to the characteristics of the data without considering the classification method used, although each of these features should be as uncorrelated with each other as possible. The silhouette statistics have been used to assess the quality of clustering by measuring how well an object is assigned to its corresponding cluster. We use this concept for the discriminant power function used in this paper. The simulation results of damage detection in a truss structure show that the approach proposed in this study can be successfully applied for locating both open- and breathing-type damage even in the presence of a considerable amount of process and measurement noise.

• Structural Monitoring and Maintenance
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• 제8권4호
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.225-231
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• 2006

The purpose of this study is to develop a promising hybrid structural health monitoring system for structural joints. For this propose, the combined use of vibration-based techniques and electro-mechanical impedance technique is employed. For the verification of the proposed health monitoring scheme, a series of damage scenarios are designed to simulate various situations at which the connection joints can experience during their service life. The obtained experimental results, modal parameters and electro-magnetic impedance signatures, are carefully analyzed to recognize the connecting states and the target damage locations. From the analysis. it is shown that the proposed hybrid health monitoring system is successful for acquiring global and local damage information on the structural joints.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.197-202
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• 2008

In this paper, a hybrid vibration-impedance approaches is newly proposed to detect the occurrence of damage, the location of damage, and extent of damage in steel plate-girder bridges. The hybrid scheme mainly consists of three sequential phases: 1) to alarm the occurrence of damage, 2) to classify the alarmed damage, and 3) to estimate the classified damage in detail. Damage types of interest include flexural stiffness-loss in girder and bolts-loose in supports. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the alarmed damage is classified into subsystems by recognizing patterns of impedance features. In the final phase, the location and the extent of damage are estimated by using modal strain energy-based damage index method and root mean square deviation method. The feasibility of the proposed system is evaluated on a laboratory-scaled steel plate-girder bridge model for which hybrid vibration-impedance signatures were measured for several damage scenarios.