• Structural Engineering and Mechanics
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• 제53권2호
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• pp.249-260
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• 2015

Damage detection based on a reference set of measured data usually has the problem of different environmental temperature in the two sets of measurements, and the effect of temperature difference is usually ignored in the subsequent model updating. This paper attempts to identify the structural damage including the temperature difference with artificial measurement noise. Both local damages and the temperature difference are identified in a gradient-based model updating method based on dynamic response sensitivity. The sensitivities of dynamic response with respect to the system parameters and temperature difference are calculated by direct integration method. The measured dynamic responses of the structure from two different states are used directly to identify the structural local damages and the temperature difference. A single degree-of-freedom mass-spring system and a planar truss structure are studied to illustrate the effectiveness of the proposed method.

• Earthquakes and Structures
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• 제8권4호
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• pp.935-956
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• 2015

Structural Health Monitoring (SHM) of steel towers has become a hot research topic. From the literature, it is impractical and impossible to develop a "general" method that can detect all kinds of damages for all types of structures. A practical method should make use of the characteristics of the type of structures and the kind of damages. This paper reports a feasibility study on the use of measured modal parameters for the detection of damaged braces of tower structures following the Bayesian probabilistic approach. A substructure-based structural model-updating scheme, which groups different parts of the target structure systematically and is specially designed for tower structures, is developed to identify the stiffness distributions of the target structure under the undamaged and possibly damaged conditions. By comparing the identified stiffness distributions, the damage locations and the corresponding damage extents can be detected. By following the Bayesian theory, the probability model of the uncertain parameters is derived. The most probable model of the steel tower can be obtained by maximizing the probability density function (PDF) of the model parameters. Experimental case studies were employed to verify the proposed method. The contributions of this paper are not only on the proposal of the substructure-based Bayesian model updating method but also on the verification of the proposed methodology through measured data from a scale model of transmission tower under laboratory conditions.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.647-652
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• 2008

This paper focused on the application of finite element model updating technique to evaluate the structural properties of the reinforced concrete specimen using the data collected from shaking table tests. The specimen was subjected to six El Centro(NS, 1942) ground motion histories with different Peak Ground Acceleration(PGA) ranging from 0.06g to 0.50g. For model updating, flexural stiffness values of structural members(walls and slabs) were chosen as the updating parameters so that the converged results have direct physical interpretations. Initial values for finite element model were determined from the member dimensions and material properties. Frequency response functions(i.e. transfer functions), natural frequencies and mode shapes were obtained using the acceleration measurement at each floor and given ground acceleration history. The weighting factors were used to account for the relative confidence in different types of inputs for updating(i.e. transfer function and natural frequencies). The constraints based on upper/lower bound of parameters and sensitivity-based constraints were implemented to the updating procedure in this study using standard bounded variable least-squares(BVLS) method. The veracity of the updated finite element model was investigated by comparing the predicted and measured responses. The results indicated that the updated model replicates the dynamic behavior of the specimens reasonably well. At each stage of shaking, severity of damage that results from cracking of the reinforced concrete member was quantified from the updated parameters(i.e. flexural stiffness values).

• 한국소음진동공학회논문집
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• 제18권7호
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• pp.725-731
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• 2008

This paper focused on the application of finite element model updating technique to evaluate the structural properties of the reinforced concrete specimen using the data collected from shaking table tests. The specimen was subjected to six El Centre (NS, 1942) ground motion histories with different peak ground acceleration (PGA) ranging from 0.06 g to 0.50 g. For model updating, flexural stiffness values of structural members (walls and slabs) were chosen as the updating parameters so that the converged results have direct physical interpretations. Initial values for finite element model were determined from the member dimensions and material properties. Frequency response functions (i.e. transfer functions), natural frequencies and mode shapes were obtained using the acceleration measurement at each floor and given ground acceleration history. The weighting factors were used to account for the relative confidence in different types of Inputs for updating (j.e. transfer function and natural frequencies) The constraints based on upper/lower bound of parameters and sensitivity-based constraints were implemented to the updating procedure in this study using standard bounded variable least-squares(BVLS) method. The veracity of the updated finite element model was investigated by comparing the predicted and measured responses. The results indicated that the updated model replicates the dynamic behavior of the specimens reasonably well. At each stage of shaking, severity of damage that results from cracking of the reinforced concrete member was quantified from the updated parameters (i.e. flexural stiffness values).

• Structural Monitoring and Maintenance
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• 제2권4호
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• pp.399-418
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• 2015

Automated damage detection through Structural Health Monitoring (SHM) techniques has become an active area of research in the bridge engineering community but widespread implementation on in-service infrastructure still presents some challenges. In the meantime, visual inspection remains as the most common method for condition assessment even though collected information is highly subjective and certain types of damage can be overlooked by the inspector. In this article, a Frequency Response Functions-based model updating algorithm is evaluated using experimentally collected data from the University of Central Florida (UCF)-Benchmark Structure. A protocol for measurement selection and a regularization technique are presented in this work in order to provide the most well-conditioned model updating scenario for the target structure. The proposed technique is composed of two main stages. First, the initial finite element model (FEM) is calibrated through model updating so that it captures the dynamic signature of the UCF Benchmark Structure in its healthy condition. Second, based upon collected data from the damaged condition, the updating process is repeated on the baseline (healthy) FEM. The difference between the updated parameters from subsequent stages revealed both location and extent of damage in a "blind" scenario, without any previous information about type and location of damage.

• Structural Engineering and Mechanics
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• 제70권3호
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• pp.339-350
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• 2019

This research focuses on finite element model updating and damage assessment of structures at element level based on global nondestructive test results. For this purpose, an optimization system is generated to minimize the structural dynamic parameters discrepancies between numerical and experimental models. Objective functions are selected based on the square of Euclidean norm error of vibration frequencies and modal assurance criterion of mode shapes. In order to update the finite element model and detect local damages within the structural members, modern optimization techniques is implemented according to the evolutionary algorithms to meet the global optimized solution. Using a simulated numerical example, application of genetic algorithm (GA), particle swarm (PSO) and artificial bee colony (ABC) algorithms are investigated in FE model updating and damage detection problems to consider their accuracy and convergence characteristics. Then, a hybrid multi stage optimization method is presented merging advantages of PSO and ABC methods in finding damage location and extent. The efficiency of the methods have been examined using two simulated numerical examples, a laboratory dynamic test and a high-rise building field ambient vibration test results. The implemented evolutionary updating methods show successful results in accuracy and speed considering the incomplete and noisy experimental measured data.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.802-807
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• 2002

The updating of FE model to match it with the experimental results needs the modal information. There are two cases where this methodology is ill-equip to deal with； under-determined and ill-conditioning problem. The feedback exciter that uses the summation of the white noise and the signals from the measurement sensors multiplied with feedback gains can deal with these problems as the new modal data from the closed loop system generate more constraints the updating parameters should obey. The new modal data from the closed loop system should be different to enhance the condition of the modal sensitivity matrix. In this research, a guide for the selection of the sensor locations and the decision of the corresponding output feedback gains is proposed. This method is based on the sensitivity of the modal data with respect to the feedback gains. Through the proper selection of the exciter and sensor locations and the feedback gain, the eigenvalue sensitivity of the updating parameters which cause the ill-conditioning of the modal sensitivity matrix can be modified and consequently the error contamination in updating parameters are reduced.

• Computers and Concrete
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• 제21권4호
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• pp.441-449
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• 2018

FE models for complex or large-scaled structures that need detailed modeling of structural components are usually constructed using commercial analysis softwares. Updating of such FE model by conventional sensitivity-based methods is difficult since repeated computation for perturbed parameters and manual calculations are needed to obtain sensitivity matrix in each iteration. In this study, an FE model updating procedure avoiding such difficulties by using response surface (RS) method and a Pareto-based multiobjective optimization (MOO) was formulated and applied to FE models constructed with a commercial analysis package. The test building is a low-rise reinforced concrete building that has been seismically retrofitted. Dynamic properties of the building were extracted from vibration tests performed before and after the seismic retrofits, respectively. The elastic modulus of concrete and masonry, and spring constants for the expansion joint were updated. Two RS functions representing the errors in the natural frequencies and mode shape, respectively, were obtained and used as the objective functions for MOO. Among the Pareto solutions, the best compromise solution was determined using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) procedure. A similar task was performed for retrofitted building by taking the updating parameters as the stiffness of modified or added members. Obtained parameters of the existing building were reasonably comparable with the current code provisions. However, the stiffness of added concrete shear walls and steel section jacketed members were considerably lower than expectation. Such low values are seemingly because the bond between new and existing concrete was not as good as the monolithically casted members, even though they were connected by the anchoring bars.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.708-713
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• 2007

Finite element model updating has been performed using an optimization technique in the paper. The objective function consists of natural frequencies, modal assurance criterion values, and bandwidths of modes, which are obtained from finite element analysis and experiment. Young's modulus and damping coefficient of the material are selected as design variables whose values are modified to make the objective function as small as possible. To consider the loading effect of an accelerometer, its mass and moment of inertia are added to design variables. This model updating method has been applied to a cantilever beam, and experimental data are measured by modal test.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.708-713
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• 2000

Finite element analysis is frequently used to get dynamic characteristics of complex structures. Since the results often show differences from experimentally measured ones, updating of finite element models is performed to make the FE results agree with measured ones. Among several model updating methods, one is to use frequency response function data. This paper investigates characteristics of the model updating method using simulated and experimental data for a cantilever beam. Damping effect is included in FE models, and FRFs for rotational displacements are calculated from FRFs for translational displacements using interpolation.