• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.446-451
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• 2007

An Improved finite element model updating method to address the numerical difficulty associated with ill-conditioning and rank-deficiency. These difficulties frequently occur in model updating problems, when the identification of a larger number of physical parameters is attempted than that warranted by the information content of the experimental data. Based on the standard Bounded Variables Least-squares (BVLS) method, which incorporates the usual upper/lower-bound constraints, the proposed method is equipped with new constraints based on the correlation coefficients between the sensitivity vectors of updating parameters. The effectiveness of the proposed method is investigated through the numerical simulation of a simple framed structure by comparing the results of the proposed method with those obtained via pure BVLS and the regularization method. The comparison indicated that the proposed method and the regularization method yield approximate solutions with similar accuracy.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.1150-1155
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• 2001

The updating of the FE model to match it with the experimental results needs the modal information. There are two causes where this methodology is ill-equip to deal with; under-determined and ill-conditioning problem. In this research, the feedback exciter which uses the summation of the white noise and the signals from the measurement sensors multiplied with feedback gains is proposed. The new energy path generated by the feedback exciter changes the modal characteristics of the system and this additional modal information can solve the under-determined problem in the model updating. 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 sensitivity matrix can be modified. This methodology does not require any additional equipments, makes the acquirement of the additional modal information easy and is robust to the measurement noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1633-1640
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• 2000

The finite element analysis (FEA) is widely used in modem structural dynamics because the performance of structure can be predicted in early stage. However, due to the difficult in determination of various uncertain parameters, it is not be easy to obtain a reliable finite element model. To overcome these difficulties, updating program of FE model is developed by consisting of pretest, correlation and updating. In correlation, it calculates modal assurance criteria, cross orthogonality, mixed orthogonality and coordinate modal assurance criteria. For the model updating, the continuum sensitivity analysis and design optimization tool (DOT) are used. The SENSUP program is developed for model updating to obtain physical parameter sensitivity. The developed program is applied to practical examples such as the base plate of HDD, BLDC spindle motor, and upper housing of induction motor. And the sensor placement for the square plate is compared using several methods.

• Smart Structures and Systems
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• v.20 no.5
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• pp.619-636
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• 2017

Magnetorheological (MR) damper is a type of controllable device widely used in vibration mitigation. This device is highly nonlinear, and exhibits strongly hysteretic behavior that is dependent on both the motion imposed on the device and the strength of the surrounding electromagnetic field. An accurate model for understanding and predicting the nonlinear damping force of the MR damper is crucial for its control applications. The MR damper models are often identified off-line by conducting regression analysis using data collected under constant voltage. In this study, a MR damper model is integrated with a model for the power supply unit (PSU) to consider the dynamic behavior of the PSU, and then a real-time nonlinear model updating technique is proposed to accurately identify this integrated MR damper model with the efficiency that cannot be offered by off-line methods. The unscented Kalman filter is implemented as the updating algorithm on a cyber-physical model updating platform. Using this platform, the experimental study is conducted to identify MR damper models in real-time, under in-service conditions with time-varying current levels. For comparison purposes, both off-line and real-time updating methods are applied in the experimental study. The results demonstrate that all the updated models can provide good identification accuracy, but the error comparison shows the real-time updated models yield smaller relative errors than the off-line updated model. In addition, the real-time state estimates obtained during the model updating can be used as feedback for potential nonlinear control design for MR dampers.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.104-108
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• 2003

Finite element (FE) model updating is a procedure to minimize the differences between analytical and experimental results, which can be usually posed as an optimization problem. This paper aims to introduce a hybrid optimization algorithm (GA-SA), which consists of a Genetic algorithm (GA) stage and an Adaptive Simulated Annealing (ASA) stage, to FE model updating for a shrunk shaft. A good agreement of the first four natural frequencies has been achieved obtained from GASA based updated model (FEgasa) and experiment. In order to prove the validity of GA-SA, comparisons of natural frequencies obtained from the initial FE model (FEinit), GA based updated model (FEga) and ASA based updated model (FEasa) are carried out. Simultaneously, the FRF comparisons obtained from different FE models and experiment are also shown. It is concluded that the GA, ASA, GA-SA are powerful optimization techniques which can be successfully applied to FE model updating, the natural frequencies and FRF obtained from all the updated models show much better agreement with experiment than that obtained from FEinit model. However, FEgasa is proved to be the most reasonable FE model, and also FEasa model is better than FEga model.

• Structural Engineering and Mechanics
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• v.87 no.1
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• pp.1-18
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• 2023

The paper presents a Bayesian Finite element (FE) model updating methodology by utilizing modal data. The dynamic condensation technique is adopted in this work to reduce the full system model to a smaller model version such that the degrees of freedom (DOFs) in the reduced model correspond to the observed DOFs, which facilitates the model updating procedure without any mode-matching. The present work considers both the MPV and the covariance matrix of the modal parameters as the modal data. Besides, the modal data identified from multiple setups is considered for the model updating procedure, keeping in view of the realistic scenario of inability of limited number of sensors to measure the response of all the interested DOFs of a large structure. A relationship is established between the modal data and structural parameters based on the eigensystem equation through the introduction of additional uncertain parameters in the form of modal frequencies and partial mode shapes. A novel sampling strategy known as the Metropolis-within-Gibbs (MWG) sampler is proposed to sample from the posterior Probability Density Function (PDF). The effectiveness of the proposed approach is demonstrated by considering both simulated and experimental examples.

• Smart Structures and Systems
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• v.32 no.1
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• pp.61-81
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• 2023

This study presents an ensemble learning based Bayesian model updating approach for structural damage diagnosis. In the developed framework, the structure is initially decomposed into a set of substructures. The autoregressive moving average (ARMAX) model is established first for structural damage localization based structural motion equation. The wavelet packet decomposition is utilized to extract the damage-sensitive node energy in different frequency bands for constructing structural surrogate models. Four methods, including Kriging predictor (KRG), radial basis function neural network (RBFNN), support vector regression (SVR), and multivariate adaptive regression splines (MARS), are selected as candidate structural surrogate models. These models are then resampled by bootstrapping and combined to obtain an ensemble model by probabilistic ensemble. Meanwhile, the maximum entropy principal is adopted to search for new design points for sample space updating, yielding a more robust ensemble model. Through the iterations, a framework of surrogate ensemble learning based model updating with high model construction efficiency and accuracy is proposed. The specificities of the method are discussed and investigated in a case study.

• Journal of Power System Engineering
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• v.4 no.2
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• pp.71-76
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• 2000

It is well known that finite element analysis often has the inaccuracy when they are in conflict with test results. Model updating is concerned with the correction of analytical model by processing records of response from test results. This paper introduce a model updating technique using the frequency response function data. The measurement data is able to be used directly in the FRF sensitivity method because it is not necessary to identify. When a damping model is updated, it is necessary for the sensitivity matrix to be divided Into the complex part and real part. As an applying model, a cantilever and a rotor system are used. Specially the machined clearance($C_p$) of the journal bearing is updated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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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).

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.7
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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).