• Smart Structures and Systems
• /
• v.26 no.1
• /
• pp.35-47
• /
• 2020

This paper proposes the use of transmissibility functions combined with a machine learning algorithm, Artificial Neural Networks (ANNs), to assess damage in a truss bridge. A new approach method, which makes use of the input parameters calculated from the transmissibility function, is proposed. The network not only can predict the existence of damage, but also can classify the damage types and identity the location of the damage. Sensors are installed in the truss joints in order to measure the bridge vibration responses under train and ambient excitations. A finite element (FE) model is constructed for the bridge and updated using FE software and experimental data. Both single damage and multiple damage cases are simulated in the bridge model with different scenarios. In each scenario, the vibration responses at the considered nodes are recorded and then used to calculate the transmissibility functions. The transmissibility damage indicators are calculated and stored as ANNs inputs. The outputs of the ANNs are the damage type, location and severity. Two machine learning algorithms are used; one for classifying the type and location of damage, whereas the other for finding the severity of damage. The measurements of the Nam O bridge, a truss railway bridge in Vietnam, is used to illustrate the method. The proposed method not only can distinguish the damage type, but also it can accurately identify damage level.

• Smart Structures and Systems
• /
• v.6 no.2
• /
• pp.147-165
• /
• 2010

Impact damage detection in composite structures has gained a considerable interest in many engineering areas. The capability to detect damage at the early stages reduces any risk of catastrophic failure. This paper compares two advanced signal processing methods for impact location in composite aircraft structures. The first method is based on a modified triangulation procedure and Genetic Algorithms whereas the second technique applies Artificial Neural Networks. A series of impacts is performed experimentally on a composite aircraft wing-box structure instrumented with low-profile, bonded piezoceramic sensors. The strain data are used for learning in the Neural Network approach. The triangulation procedure utilises the same data to establish impact velocities for various angles of strain wave propagation. The study demonstrates that both approaches are capable of good impact location estimates in this complex structure.

• Structural Engineering and Mechanics
• /
• v.63 no.2
• /
• pp.251-257
• /
• 2017

A local damage identification method using measured structural static displacement is proposed in this study. Based on the residual force vector deduced from the static equilibrium equation, residual strain energy (RSE) is introduced, which can localize the damage in the element level. In the case of all the nodal displacements are used, the RSE can localize the true location of damage, while incomplete displacement measurements are used, some suspicious damaged elements can be found. A model updating method based on static displacement response sensitivity analysis is further utilized for accurate identification of damage location and extent. The proposed method is verified by two numerical examples. The results indicate that the proposed method is efficient for damage identification. The advantage of the proposed method is that only limited static displacement measurements are needed in the identification, thus it is easy for engineering application.

• Smart Structures and Systems
• /
• v.6 no.9
• /
• pp.991-1005
• /
• 2010

The key to detecting damage to civil engineering structures is to find an effective damage indicator. The damage indicator should promptly reveal the location of the damage and accurately identify the state of the structure. We propose to use the distance measures of low-order AR models as a novel damage indicator. The AR model has been applied to parameterize dynamical responses, typically the acceleration response. The premise of this approach is that the distance between the models, fitting the dynamical responses from damaged and undamaged structures, may be correlated with the information about the damage, including its location and severity. Distance measures have been widely used in speech recognition. However, they have rarely been applied to civil engineering structures. This research attempts to improve on the distance measures that have been studied so far. The effect of varying the data length, number of parameters, and other factors was carefully studied.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2008.04a
• /
• pp.197-202
• /
• 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.

• Advances in Computational Design
• /
• v.7 no.1
• /
• pp.81-98
• /
• 2022

This study presents the application of two indices for the locating of cracks in Reinforced Concrete (RC) structures, as well as the development of their modified forms to overcome limitations. The first index is based on mode shape curvature and the second index is based on the fourth derivative of the mode shape. In order to confirm the indices' effectiveness, both eigenvalues coupled with nonlinear static analyses were carried out and the eigenvectors for two different damage locations and intensities of load were obtained from the finite element model of RC beams. The values of the damage-locating indices derived using both indices were then compared. Generally, the mode shape curvature-based index suffered from insensitivity when attempting to detect the damage location; this also applied to the mode shape fourth derivative-based index at lower modes. However, at higher modes, the mode shape fourth derivative-based index gave an acceptable indication of the damage location. Both the indices showed inconsistencies and anomalies at the supports. This study proposed modification to both indices to overcome identified flaws. The results proved that modified forms exhibited better sensitivity for identifying the damage location. In addition, anomalies at the supports were eliminated.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.27 no.5
• /
• pp.49-56
• /
• 2023

This study proposed a damage location estimation method for automated image-based port infrastructure inspection. Memory efficiency was improved by calculating the homography matrix using feature detection technology and outlier removal technology, without going through the 3D modeling process and storing only damage information. To develop an algorithm specialized for port infrastructure, the algorithm was optimized through ground-truth coordinate pairs created using images of port infrastructure. The location errors obtained by applying this to the sample and concrete wall were (X: 6.5cm, Y: 1.3cm) and (X: 12.7cm, Y: 6.4cm), respectively. In addition, by applying the algorithm to the concrete wall and displaying it in the form of an exterior damage map, the possibility of field application was demonstrated.

• Smart Structures and Systems
• /
• v.24 no.4
• /
• pp.475-490
• /
• 2019

The detection of structural damage without a priori information on the healthy state is challenging. In order to address the issue, the study presents a baseline-free approach to detect damage in beam structures based on an actual influence line. In particular, a multi-segment function-fitting calculation is developed to extract the actual deflection influence line (DIL) of a damaged beam from bridge responses due to a passing vehicle. An intact basis function based on the measurement position is introduced. The damage index is defined as the difference between the actual DIL and a constructed function related to the intact basis, and the damage location is indicated based on the local peak value of the damage index curve. The damage basis function is formulated by using the detected damage location. Based on the intact and damage basis functions, damage severity is quantified by fitting the actual DIL using the least-square calculation. Both numerical and experimental examples are provided to investigate the feasibility of the proposed method. The results indicate that the present baseline-free approach is effective in detecting the damage of beam structures.

• Earthquakes and Structures
• /
• v.8 no.5
• /
• pp.1113-1126
• /
• 2015

A damage localization algorithm based on Operational Deformed Shapes and known as Interpolation Damage Detection Method, is herein applied to the finite element model of a cable stayed bridge for detecting and localizing damages in the stays and the supporting steel beams under the bridge deck. Frequency Response Functions have been calculated basing on the responses of the bridge model to low intensity seismic excitations and used to recover the Operational Deformed Shapes both in the transversal and in the vertical direction. The analyses have been carried in the undamaged configuration and repeated in several different damaged configurations. Results show that the method is able to detect the damage and its correct location, provided an accurate estimation of the Operational Deformed Shapes is available. Furthermore, the damage detection algorithm results effective also when damages coexist at the same time at several location of the cable-stayed bridge members.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.7 s.112
• /
• pp.720-728
• /
• 2006

A robust damage assessment technique is presented such that the location and severity of damage in structures can be identified using measured modal data. In order to identify the damage efficiently, the concept of design of experiment using orthogonal array is used for screening the main effects of each parameter which corresponds to possible damage location in FE model. Then, Taguchi method, which has been widely used for robust design in industry, is applied to parameter updating in analytical FE model. The numerical simulations of a truss structure show that damages in structure can be located from updated parameters.