• 한국자동차공학회논문집
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• 제10권2호
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• pp.220-227
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• 2002

This paper describes an integrated approach process to carry out pre-test, model correlation and updating analysis on the sub-frame of a vehicle. In this study, it was found that the modal test could be more efficient when the exciting point was selected on the area with high driving point residue. Such area could be located with the aid of finite element modal analysis. The model correlation was appraised in conjunction with the modal parameters between modal test and finite elements analysis. Also, the finite element model updating was obtained the good resultant using the iteration method based on sensitivity analysis results that carried out the variation of natural frequencies and MAC for the material properties. Finally, optimization of vehicle subframe was carried out the analysis of core location and physical properties by tow steps.

• 한국강구조학회 논문집
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• 제24권4호
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• pp.399-410
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• 2012

본 연구에서는 실험적 모드해석 기법을 이용하여 캔틸레버 및 양단고정 직사각형 적층복합판의 동적 테스트가 수행되었다. 균열 성장으로 인한 손상평가를 위하여 적층복합판에 인위적인 단계별 손상(균열)을 가하였으며, 충격해머 모드실험에 의해 얻어진 주파수응답함수(FRF), MAC(Modal Assurance Criterion) 값 및 모드매개변수(진동수, 모드형상, 감쇠비)의 변화를 분석하였다. 각 단계별 손상에 대한 적층복합판의 실험적 모드매개변수를 검증하기 위하여 유한요소해석으로부터 구한 고유진동수와 모드형상을 비교하였다. 손상은 벤치마크로서의 유한요소모델을 보정하는 과정으로부터 얻게 되는 적층복합판의 기하학적 특성 및 구조적 거동의 변화를 통하여 평가될 수 있음을 보여주었다.

• 한국전산구조공학회논문집
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• 제36권3호
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• pp.155-163
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• 2023

원전 구조물의 실시간 모니터링 기술이 요구되고 있지만, 현재 운영 중인 지진 감시계통으로는 동특성 추출 등 시스템 식별이 제한된다. 전역적인 거동 데이터 및 동특성 추출을 위해서는 다수의 센서를 최적 배치하여야 한다. 최적 센서배치 연구는 많이 진행되어 왔지만 주로 토목, 기계 구조물이 대상이었으며 원전 구조물 대상으로 수행된 연구는 없었다. 원전 구조물은 미미한 신호대잡음비에도 강건한 신호를 획득하여야 하며, 모드 기여도가 저차 모드에 집중되어 있어 모드별 잡음 영향을 고려해야 하는 등 구조물 특성을 고려해야 한다. 이에 본 연구에서는 잡음에 대한 강건도와 모드별 영향을 평가할 수 있는 최적 센서배치 방법론을 제시하였다. 활용한 지표로서 auto MAC(Modal Assurance Criterion), cross MAC, 노드별 모드형상 분포를 분석하였으며, 잡음에 대한 강건도 평가의 적합성을 수치해석으로 검증하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.361-365
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• 2007

우라늄을 내장한 연료봉은 핵분열이 일어나는 우라늄 펠렛(pellet)을 1차적으로 차폐하는 중요한 구조물이다. 연료봉은 원자로 내에서 유체유발진동에 의해 손상될 수 있으며, 본 연구에서는 유동유발진동 특성을 예측하기 위해 핵연료봉의 동특성 규명을 위한 모드해석을 수행하였다. 핵연료봉의 진동특성을 규명하기 위해 제작한 시험장치를 이용하여 피복관(clad tube)의 진동특성실험과 유한 요소 해석을 수행하였다. 모드시험(Modal Testing)은 현재 상용 핵연료봉(튜브)을 대상으로 수행되었으며, 유한 요소 해석 모델을 개발하여 해석 결과와 시험 결과를 비교 분석하였다.

• Structural Engineering and Mechanics
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• 제70권6호
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• pp.649-659
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• 2019

Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.

• Structural Engineering and Mechanics
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• 제58권1호
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• pp.163-179
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• 2016

The Cuckoo search (CS) algorithm is a simple and efficient global optimization algorithm and it has been applied to figure out large range of real-world optimization problem. In this paper, a new formula is introduced to the discovering probability process to improve the convergence rate and the Tournament Selection Strategy is adopted to enhance global search ability of the certain algorithm. Then an approach for structural damage identification based on modified Cuckoo search (MCS) is presented. Meanwhile, we take frequency residual error and the modal assurance criterion (MAC) as indexes of damage detection in view of the crack damage, and the MCS algorithm is utilized to identifying the structural damage. A simply supported beam and a 31-bar truss are studied as numerical example to illustrate the correctness and efficiency of the propose method. Besides, a laboratory work is also conducted to further verification. Studies show that, the proposed method can judge the damage location and degree of structures more accurately than its counterpart even under measurement noise, which demonstrates the MCS algorithm has a higher damage diagnosis precision.

• Smart Structures and Systems
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• 제31권3호
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• 한국소음진동공학회논문집
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• 제18권9호
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• pp.972-981
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• 2008

The blower which is installed in a FCEV(fuel cell electric vehicle) may cause noise due to misalignment and unbalance of mechanical components that rotate at high speed. One of the key points in efforts to minimize the noise radiation from a blower is the knowledge of the main radiating component and the relation between the surface vibration of a blower and the sound pressure. In this research, the blower model is developed based on FEM(finite element method). FE(finite element) model is reliable by correlation of frequencies and MAC(modal assurance criterion) values between EMA(experimental modal analysis) and FEA(finite element analysis). This model is applied to predict the vibration of a blower by using inverse force identification method and predict the radiating noise by using BEM(boundary element method). Comparing the frequencies of resonance and those mode shapes between EMA and FEA, a structural modification of the FE model is evaluated for reducing the parameters of the blower noise.

• Structural Engineering and Mechanics
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• 제58권2호
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• pp.277-300
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• 2016

Cold-formed steel (CFS) sections are becoming an increasingly popular solution for constructing floors in residential, healthcare and education buildings. Their reduced weight, however, makes them prone to excessive vibrations, increasing the need for accurate prediction of CFS floor modal properties. By combining experimental modal analysis of a full-scale CFS framed building and its floors and their numerical finite element (FE) modelling this paper demonstrates that the existing methods (based on the best engineering judgement) for predicting CFS floor modal properties are unreliable. They can yield over 40% difference between the predicted and measured natural frequencies for important modes of vibration. This is because the methods were adopted from other floor types (e.g., timber or standard steel-concrete composite floors) and do not take into account specific features of CFS floors. Using the adjusted and then updated FE model, featuring semi-rigid connections led to markedly improved results. The first four measured and calculated CFS floor natural frequencies matched exactly and all relevant modal assurance criterion (MAC) values were above 90%. The introduction of flexible supports and more realistic modelling of the floor boundary conditions, as well as non-structural $fa{\c{c}}ade$ walls, proved to be crucial in the development of the new more successful modelling strategy. The process used to develop 10 identified and experimentally verified FE modelling parameters is based on published information and parameter adjustment resulting from FE model updating. This can be utilised for future design of similar lightweight steel floors in prefabricated buildings when checking their vibration serviceability, likely to be their governing design criterion.

• Smart Structures and Systems
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• 제13권3호
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• pp.389-406
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• 2014

Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.