• Structural Engineering and Mechanics
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• 제62권3호
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• pp.303-310
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• 2017

The model updating problems, which are to find the optimal approximation to the discrete quadratic model obtained by the finite element method, are critically important to the vibration analysis. In this paper, the structured model updating problem is considered, where the coefficient matrices are required to be symmetric and positive semidefinite, represent the interconnectivity of elements in the physical configuration and minimize the dynamics equations, and furthermore, due to the physical feasibility, the physical parameters should be positive. To the best of our knowledge, the model updating problem involving all these constraints has not been proposed in the existed literature. In this paper, based on the semidefinite programming technique, we design a general-purpose numerical algorithm for solving the structured model updating problems with incomplete measured data and present some numerical results to demonstrate the effectiveness of our method.

• Structural Engineering and Mechanics
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• 제88권5호
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• pp.493-500
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• 2023

The multiparameter eigenvalue method can be used to solve the damped finite element model updating problems. This method transforms the original problems into multiparameter eigenvalue problems. Comparing with the numerical methods based on various optimization methods, a big advantage of this method is that it can provide all possible choices of physical parameters. However, when solving the transformed singular multiparameter eigenvalue problem, the proposed method based on the generalised inverse of a singular matrix has some computational challenges and may fail. In this paper, more details on the transformation from the dynamic model updating problem to the multiparameter eigenvalue problem are presented and the structure of the transformed problem is also exposed. Based on this structure, the rigorous mathematical deduction gives the upper bound of the number of possible choices of the physical parameters, which confirms the singularity of the transformed multiparameter eigenvalue problem. More importantly, we present a row and column compression method to overcome the defect of the proposed numerical method based on the generalised inverse of a singular matrix. Also, two numerical experiments are presented to validate the feasibility and effectiveness of our method.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.876-881
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• 2004

Finite element model updating is an inverse problem to identify and correct uncertain modeling parameters that leads to better predictions of the dynamic behavior of a target structure. Unlike other inverse problems, the restrictions on selecting parameters all: very high since the updated model should maintains its physical meaning. That is, only the regions with modeling errors should be parameterized. And the variations of the parameters should be kept small while the updated results give acceptable correlations with experimental data. To avoid an ill-conditioned numerical problem, the number of parameters should be kept as small as possible. Thus it is very difficult to select an adequate set of updating parameters which meet all these requirements. In this paper, the importance of updating parameter selection is illustrated through a case study, and an automated procedure to guide the parameter selection is suggested based on simple observations. The effectiveness of the suggested procedure is tested with two example problems, ones is a simulated case study and the other is a real engineering structure.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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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.

• 소음진동
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• 제9권1호
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• pp.163-173
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• 1999

Precise and reasonable modelling is necessary and indispensable to the analysis of dynamic characteristics of mechanical structures. Also. the effective prediction of the change of modal properties due to the variation of design parameters is required especially for the application of finite element method to the structural dynamics problems. To meet those necessity and requirement, three model updating algorithms are proposed for finite element methods. Those algorithms are based on sensitivity analysis of the modal data obtained from experimental modal analysis(EMA) and analytical modal analysis(AMA). The adapted sensitivity analysis methods of the algorithms are 1)eigensensitivity(EGNS) method. 2)frequency response function sensitivity(FRFS) method. 3)sensitivity based element-by-element method (SBEEM), Singular value decomposition(SVD) is used for performing eigenanalysis and parameter estimation in the updating process. Those algorithms are applied to finite element of a plate and the updating capability of each algorithm is compared in terms of accuracy. reliability and stability of the updating process. It is shown that the model updating method using frequency response function is superior to the other methods in view of various updating capabilities.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.433-436
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• 2008

A demand on the spatial data management has been rapidly increased with the introduction and diffusion process of ITS, Telematics, and Wireless Sensor Network, and many different people use the digital map that offers various thematic spatial data. Spatial data for digital map can manage to tile-based and feature-based data. The existing tile-based digital map management systems have difficult problems of data construction, history management, and updating based on a spatial object. In order to solve these problems, this paper proposed the data model for the feature-based digital map management system that is designed for feature-based seamless map, history management, real-time updating of spatial data, and analyzed the validity and utility of the proposed model.

• 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.

• Smart Structures and Systems
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• 제21권4호
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• pp.435-448
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• 2018

This paper reports the development of a theoretically rigorous method for permanent way engineers to assess the condition of railway ballast under a concrete sleeper with the potential to be extended to a smart system for long-term health monitoring of railway ballast. Owing to the uncertainties induced by the problems of modeling error and measurement noise, the Bayesian approach was followed in the development. After the selection of the most plausible model class for describing the damage status of the rail-sleeper-ballast system, Bayesian model updating is adopted to calculate the posterior PDF of the ballast stiffness at various regions under the sleeper. An obvious drop in ballast stiffness at a region under the sleeper is an evidence of ballast damage. In model updating, the model that can minimize the discrepancy between the measured and model-predicted modal parameters can be considered as the most probable model for calculating the posterior PDF under the Bayesian framework. To address the problems of non-uniqueness and local minima in the model updating process, a two-stage hybrid optimization method was developed. The modified evolutionary algorithm was developed in the first stage to identify the important regions in the parameter space and resulting in a set of initial trials for deterministic optimization to locate all most probable models in the second stage. The proposed methodology was numerically and experimentally verified. Using the identified model, a series of comprehensive numerical case studies was carried out to investigate the effects of data quantity and quality on the results of ballast damage detection. Difficulties to be overcome before the proposed method can be extended to a long-term ballast monitoring system are discussed in the conclusion.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.882-886
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• 2004

In this section, the proposed parameter selection procedure is applied to two example problems, one is the plate example given in section 2.2 and the other is a cover structure of hard disk drive (HDD).