• Structural Engineering and Mechanics
• /
• v.77 no.4
• /
• pp.495-508
• /
• 2021

This study devises a novel approach, namely quadruple 1D convolutional neural network, for detecting connection stiffness reduction in steel truss bridge structure using experimental and numerical modal data. The method is developed based on expertise in two domains: firstly, in Structural Health Monitoring, the mode shapes and its high-order derivatives, including second, third, and fourth derivatives, are accurate indicators in assessing damages. Secondly, in the Machine Learning literature, the deep convolutional neural networks are able to extract relevant features from input data, then perform classification tasks with high accuracy and reduced time complexity. The efficacy and effectiveness of the present method are supported through an extensive case study with the railway Nam O bridge. It delivers highly accurate results in assessing damage localization and damage severity for single as well as multiple damage scenarios. In addition, the robustness of this method is tested with the presence of white noise reflecting unavoidable uncertainties in signal processing and modeling in reality. The proposed approach is able to provide stable results with data corrupted by noise up to 10%.

• Journal of the Korean Society of Industry Convergence
• /
• v.10 no.3
• /
• pp.149-155
• /
• 2007

Damage assessment and Damage index for RC members failed in flexure was investigated by using the nonlinear finite element analysis, included with nonlocal constitutive law, which is analyzed for the localization of the failure on the post-peak region. In the nonlcal constitutive law, The local strains obtained at gauss points were averaged over a particular length, i.e. characteristic length and it was used to evaluate the damage of RC column member. As the analysis results, The value of nonlocal strain shows less mesh sensibility. In the damage assessment, It was confirmed that evaluations of damage of RC member were able to use nonlocal compressive strain on a cover concrete and a core concrete of the member. Moreover it was confirmed that damage process for the statically indeterminate structure was able to evaluate the damage context of the component members of the structure.

• Computers and Concrete
• /
• v.20 no.5
• /
• pp.563-572
• /
• 2017

Ordinary reinforced concrete (RC) and prestressed concrete bridges are two popular and typical types of short- and medium-span bridges that accounts for the vast majority of all existing bridges. The cost of maintaining, repairing or replacing degraded existing RC bridges is immense. Detecting the abnormality of RC bridges at an early stage and taking the protective measures in advance are effective ways to improve maintenance practices and reduce the maintenance cost. This study proposes a systematic method from influence line (IL) identification to damage detection with applications to RC bridges. An IL identification method which integrates the cubic B-spline function with Tikhonov regularization is first proposed based on the vehicle information and the corresponding moving vehicle induced bridge response time history. Subsequently, IL change is defined as a damage index for bridge damage detection, and information fusion technique that synthesizes ILs of multiple locations/sensors is used to improve the efficiency and accuracy of damage localization. Finally, the feasibility of the proposed systematic method is verified through experimental tests on a three-span continuous RC beam. The comparison suggests that the identified ILs can well match with the baseline ILs, and it demonstrates that the proposed IL identification method has a high accuracy and a great potential in engineering applications. Results in this case indicate that deflection ILs are superior than strain ILs for damage detection of RC beams, and the performance of damage localization can be significantly improved with the information fusion of multiple ILs.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.6
• /
• pp.2356-2363
• /
• 2015

Localization of lightning strike point (LSP) in the forest is modeled to mitigate the forest fire damage. Though forest fire ignited by lightning rarely happens, its damage on the forest is grievousness. Therefore, predicting accurate location of LSP becomes crucial in order to control the forest fire. In this paper, we proposed a new hybrid localization algorithm by combining the received signal strength (RSS) and the received signal strength ratio (RSSR) to improve the accuracy by mitigating the environmental effect of lightning strike location in the forest. The proposed hybrid algorithm employs antenna theory (AT) model of cloud-to-ground (CG) return stroke lightning channel to forecast the location of the lightning strike. The obtained results show that the proposed hybrid algorithm achieves better location accuracy compared to the existing RSS method for predicting the lightning strike location considering additive white Gaussian noise (AWGN) environment.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2011.04a
• /
• pp.278-281
• /
• 2011

The global coordinates generated from Isomap algorithm provide a simple way to analyze and manipulate high dimensional observations in terms of their intrinsic nonlinear degrees of freedom. Thus, Isomap can find globally meaningful coordinates and nonlinear structure of complex data sets, while neither principal component analysis (PCA) nor multidimensional scaling (MDS) are successful in many cases. It is demonstrated that the adapted Isomap algorithm successfully enhances the quality of pattern classification for damage identification in various numerical examples.

• Structural Engineering and Mechanics
• /
• v.46 no.2
• /
• pp.231-244
• /
• 2013

An efficient method is proposed here to identify multiple damage cases in structural systems using the concepts of flexibility matrix and strain energy of a structure. The flexibility matrix of the structure is accurately estimated from the first few mode shapes and natural frequencies. Then, the change of strain energy of a structural element, due to damage, evaluated by the columnar coefficients of the flexibility matrix is used to construct a damage indicator. This new indicator is named here as flexibility strain energy based index (FSEBI). In order to assess the performance of the proposed method for structural damage detection, two benchmark structures having a number of damage scenarios are considered. Numerical results demonstrate that the method can accurately locate the structural damage induced. It is also revealed that the magnitudes of the FSEBI depend on the damage severity.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.20 no.3
• /
• pp.272-278
• /
• 2010

A method for damage detection in a plate structure is presented based on strain waves that are generated by impact or damage in the structure. Strain responses from continuous sensors, which are long ribbon-like sensors made from piezoceramic fibers or other materials, were used with a neural network technique to estimate the damage location. The continuous sensor uses only a small number of channels of data acquisition and can cover large areas of the structure. A grid type structural neural system composed of the continuous sensors was developed for effective damage localization in a plate structure. The ratios of maximum strains and arrival times of the maximum strains obtained from the continuous sensors were used as input data to a neural network. Simulated damage localizations on a plate were carried out and the identified damage locations agreed reasonably well with the exact damage locations.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.31 no.2
• /
• pp.41-50
• /
• 2003

In this paper, nonlinear parallel structural analyses are introduced by using the parallel multifrontal solver and damage localization for 2D and 3D crack models is presented as the application of nonlinear parallel computation. The parallel algorithms related with nonliear reduce the amount of memory used is carried out because many variables should be utilized for this highly nonlinear damage analysis. Also, Riks' continuation method is parallelized to search the solution when strain softening occurs due to damage evolution. For damage localization problem, several computational models having up to around 1-million degree of freedoms are used. The parallel performance in this nonlinear parallel algorithm is shown through these examples and the local variation of damage at crack tip is compared among the models with different degree of freedoms.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.14 no.1
• /
• pp.165-174
• /
• 2010

In this paper, a two-phase structural health monitoring system using acceleration response signatures are presented to firstly alarm the change in structural condition and to secondly detect the changed location for full-scale concrete girder bridges. Firstly, Mihocheon Bridge which is a two-span continuous concrete girder bridge is selected as the target structure. The dynamic response features of Mihocheon Bridge are extracted by forced vibration test using bowling ball. Secondly, the damage alarming occurrence and the damage localization techniques are selected to design two-phase structural health monitoring system for Mihocheon Bridge. As the damage alarming techniques, auto-regressive model using time-domain signatures, correlation coefficient of frequency response function and frequency response ratio assurance criterion are selected. As the damage localization technique, modal strain energy-based damage index method is selected. Finally, the feasibility of two-phase structural health monitoring systems is evaluated from static loading tests using a dump truck.

• Computers and Concrete
• /
• v.8 no.3
• /
• pp.243-278
• /
• 2011

The paper presents simulations of the Brazilian test using two numerical models. Both models are regularized in order to obtain results independent of discretization. The first one, called gradient damage, is refined by additional averaging equation which contains gradient terms and an internal length scale as localization limiter. In the second one, called viscoplastic consistency model, the yield function depends on the viscoplastic strain rate. In this model regularization properties are governed by the assumed strain rate. The two models are implemented in the FEAP finite element package and compared in this paper. Parameter studies of the split test are performed in order to point out the features of each model.