• Smart Structures and Systems
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• 제23권1호
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• pp.15-29
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• 2019

This paper addresses the problem of damage detection in suspension bridge hangers, with an emphasis on the modal flexibility method. It aims at evaluating the capability and the accuracy of the modal flexibility method to detect and locate single and multiple damages in suspension bridge hangers, with different level of severity and various locations. The study is conducted numerically and experimentally on a laboratory suspension bridge mock-up. First, the covariance-driven stochastic subspace identification is used to extract the modal parameters of the bridge from experimental data, using only output measurements data from ambient vibration. Then, the method is demonstrated for several damage scenarios and compared against other classical methods, such as: Coordinate Modal Assurance Criterion (COMAC), Enhanced Coordinate Modal Assurance Criterion (ECOMAC), Mode Shape Curvature (MSC) and Modal Strain Energy (MSE). The paper demonstrates the relative merits and shortcomings of these methods which play a significant role in the damage detection ofsuspension bridges.

• Smart Structures and Systems
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• 제17권3호
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• pp.445-470
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• 2016

In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.688-693
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• 2002

Identification method is formulated to evaluate the dynamic characteristics of air bearings under NFR(Near Field Recording) sliders. Impulse responses and frequency response functions of NFR sliders are obtained on numerical non-linear models including rigid motion of slider and fluid motion of air bearing under the slider. Modal parameters and system parameters are identified by modal analysis method and instrumental variable method. The parameters of sliders are utilized to evaluate the dynamic characteristics of air bearings. Also, this study shows the difference between the dynamic characteristics of NFR and HDD slides, and squeeze effect of air bearings.

• Smart Structures and Systems
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• 제5권4호
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• pp.427-442
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• 2009

In this paper, the acceptability of system identification results for health monitoring of instrumented bridges is addressed. This is conducted by comparing the confidence intervals of identified modal parameters for a bridge in California, namely Truckee I80/Truckee river bridge, with the change of these parameters caused by several damage scenarios. A challenge to the accuracy of the identified modal parameters involves consequences regarding the damage detection and health monitoring, as some of the identified modal information is essentially not useable for acquiring a reliable damage diagnosis of the bridge system. Use of strong motion data has limitations that should not be ignored. The results and conclusions underline these limitations while presenting the opportunities offered by system identification using strong motion data for better understanding and monitoring the health of bridge systems.

• 한국지진공학회논문집
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• 제21권5호
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• pp.237-244
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• 2017

This study proposes a numerical model to explain the closely placed double modes in the vibration of a layered stone pagoda system. The friction surface between the stones is modelled as the Timoshenko finite element while each stone layer is modelled as a rigid body. It is assumed that the irregular asperity on the friction surface enables the stone to be excited. This results in the closely placed modes that are composed of natural modes and self-excited modes. To examine the validity of the proposed model, a set of modal testing and analysis for a layered stone pagoda mock-up model has been conducted and a set of closely placed double modes are extracted. Applying the extended sensitivity-based system identification technique, the various system parameters are identified so that the modal parameters of the proposed numerical model are the same with those of the experimental mock-up. For a horizontal impulse excitation, the simulated acceleration responses are compared with measurements.

• Structural Engineering and Mechanics
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• 제71권4호
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• pp.391-405
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• 2019

Compared to the ambient vibration test mainly identifying the structural modal parameters, such as frequency, damping and mode shapes, the impact testing, which benefits from measuring both impacting forces and structural responses, has the merit to identify not only the structural modal parameters but also more detailed structural parameters, in particular flexibility. However, in traditional impact tests, an impacting hammer or artificial excitation device is employed, which restricts the efficiency of tests on various bridge structures. To resolve this problem, we propose a new method whereby a moving vehicle is taken as a continuous exciter and develop a corresponding flexibility identification theory, in which the continuous wheel forces induced by the moving vehicle is considered as structural input and the acceleration response of the bridge as the output, thus a structural flexibility matrix can be identified and then structural deflections of the bridge under arbitrary static loads can be predicted. The proposed method is more convenient, time-saving and cost-effective compared with traditional impact tests. However, because the proposed test produces a spatially continuous force while classical impact forces are spatially discrete, a new flexibility identification theory is required, and a novel structural identification method involving with equivalent load distribution, the enhanced Frequency Response Function (eFRFs) construction and modal scaling factor identification is proposed to make use of the continuous excitation force to identify the basic modal parameters as well as the structural flexibility. Laboratory and numerical examples are given, which validate the effectiveness of the proposed method. Furthermore, parametric analysis including road roughness, vehicle speed, vehicle weight, vehicle's stiffness and damping are conducted and the results obtained demonstrate that the developed method has strong robustness except that the relative error increases with the increase of measurement noise.

• Structural Engineering and Mechanics
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• 제50권2호
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• pp.137-149
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• 2014

In this study, modal parameters such as natural frequencies, mode shapes and damping ratios of RC frames with low strength are determined for different construction stages using ambient vibration test. For this purpose full scaled, one bay and one story RC frames are produced and tested for plane, brick in-filled and brick in-filled with plaster conditions. Measurement time, frequency span and effective mode number are determined by considering similar studies and literature. To obtain experimental dynamic characteristics, Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification techniques are used together. It is shown that the ambient vibration measurements are enough to identify the most significant modes of RC frames. The results indicate that modal parameters change significantly depending on the construction stages. In addition, Infill walls increase stiffness and change the mode shapes of the RC frame. There is a good agreement between mode shapes obtained from brick in-filled and in-filled with plaster conditions. However, some differences are seen in plane frame, like expected. Dynamic characteristics should be verified using finite element analysis. Finally, inconsistency between experimental and analytical dynamic characteristics should be minimize by finite element model updating using some uncertain parameters such as material properties, boundary condition and section properties to reflect the current behavior of the RC frames.

• 한국소음진동공학회논문집
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• 제16권2호
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• pp.115-123
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• 2006

A feasibility of using the topology optimization method for structural damage identification is investigated for the first time. The frequency response functions (FRFs) are assumed to be constructed by the finite element models of damaged and undamaged structures. In addition to commonly used resonances, antiresonances are employed as the damage identifying modal parameters. For the topology optimization formulation, the modal parameters of the undamaged structure are made to approach those of the damaged structure by means of the constraint equations, while the objective function is an explicit penalty function requiring clear black-and-white images. The developed formulation is especially suitable for damage identification problems dealing with many modal parameters. Although relatively simple numerical problems were considered in this investigation, the possibility of using the topology optimization method for structural damage identification is suggested through this research.

• 한국정밀공학회지
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• 제27권2호
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• pp.109-116
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• 2010

It is important to make a mechanical structure precisely and reasonably in predicting the dynamic characteristics, controlling the vibration, and designing the structure dynamics. In finite element analysis model updating is appropriate as the design parameter is used to analyze the dynamic system. The errors can be contained from the physical parameters and the element modeling. From the dynamic test, more precise dynamic characteristics can be obtained. In this paper, model updating algorithm is developed using frequency difference between experiment and calculation. Modal frequencies are obtained by experiment and finite element analysis for beams with various cross section and shapes which have added masses and holes in the middle. For plates with and without groove, experiment and analyses are carried out by applying free boundary conditions as well. Mass and stiffness matrices are updated by comparing test and analytical modal frequencies. The result shows that the updated frequencies become closer to the test frequencies in case that both matrices are updated. An improved analytical model is obtained by changing model parameters such that the discrepancy between test and finite element frequencies is minimized. For beam and plate models updating of mass and stiffness matrices can improve the dynamical behavior of the model by acting on the physical parameters such as masses and stiffness.

• Structural Engineering and Mechanics
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• 제70권4호
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• pp.457-466
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• 2019

This study develops a damage detection method based on neural networks. The performance of the method is numerically and experimentally verified using a three-story shear building model. The framework is mainly composed of two hierarchical stages to identify damage location and extent using artificial neural network (ANN). The normalized damage signature index, that is a normalized ratio of the changes in the natural frequency and mode shape caused by the damage, is used to identify the damage location. The modal parameters extracted from the numerically developed structure for multiple damage scenarios are used to train the ANN. The positive alarm from the first stage of damage detection activates the second stage of ANN to assess the damage extent. The difference in mode shape vectors between the intact and damaged structures is used to determine the extent of the related damage. The entire procedure is verified using laboratory experiments. The damage is artificially modeled by replacing the column element with a narrow section, and a stochastic subspace identification method is used to identify the modal parameters. The results verify that the proposed method can accurately detect the damage location and extent.