• Smart Structures and Systems
• /
• v.31 no.3
• /
• pp.247-257
• /
• 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.

• Structural Engineering and Mechanics
• /
• v.64 no.3
• /
• pp.279-285
• /
• 2017

Modal expansion technique (MET) is a method to estimate the vibration fields of flexible structures by using eigenmodes of the structure and the signals of sensors. It is the useful method to estimate the vibration fields but has the truncation error since it only uses the limit number of the eigenmodes in the frequency of interest. Even though block-wise MET performed frequency block by block with different valid eigenmodes was developed, it still has the truncation error due to the absence of other eigenmodes. Thus, this paper suggested an improved block-wise modal expansion technique. The technique recovers the truncation errors in one frequency block by utilizing other eigenmodes existed in the other frequency blocks. It was applied for estimating the vibration fields of a cylindrical shell. The estimated results were compared to the vibration fields of the forced vibration analysis by using two indices: the root mean square error and parallelism between two vectors. These indices showed that the estimated vibration fields of the improved block-wise MET more accurately than those of the established METs. Especially, this method was outstanding for frequencies near the natural frequency of the highest eigenmode of each block. In other words, the suggested technique can estimate vibration fields more accurately by recovering the truncation errors of the established METs.

• Smart Structures and Systems
• /
• v.31 no.1
• /
• pp.45-56
• /
• 2023

Vibration-based structural health monitoring is used to ensure the safety of structures by installing sensors in structures. The peak picking method, one of the applications of vibration-based structural health monitoring, is a method that analyze the dynamic characteristics of a structure using the peaks of the frequency response function. However, the results may vary depending on the person predicting the peak point; further, the method does not predict the exact peak point in the presence of noise. To overcome the limitations of the existing peak picking methods, this study proposes a new method to automate the modal analysis process by utilizing long short-term memory, a type of recurrent neural network. The method proposed in this study uses the time series data of the frequency response function directly as the input of the LSTM network. In addition, the proposed method improved the accuracy by using the phase as well as amplitude information of the frequency response function. Simulation experiments and lab-scale model experiments are performed to verify the performance of the LSTM network developed in this study. The result reported a modal assurance criterion of 0.8107, and it is expected that the dynamic characteristics of a civil structure can be predicted with high accuracy using data without experts.

• Journal of KSNVE
• /
• v.10 no.2
• /
• pp.319-324
• /
• 2000

This paper shows hot to model the submerged elastic structures and adequate analysis tools for modal behavior when using finite element and boundary element method. Four different cases are reviewed depending on the location of the water and air. First case is that structures are filled with air and water is located outside. Second case is opposite to case one. These cases are solved by direct approach using collocation procedure. Third case is that water is located both sides of structures. Last case is that air is located both sides. These cases are solved by indirect approach using variational procedure. As analysis tools harmonic frequency sweep analysis and eigenvalue iteration method are selected to obtain the natural frequencies of vibrating submerged structures depending on the cases. Results are compared with closed form solutions of submerged spherical shell.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.708-713
• /
• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.05a
• /
• pp.361-365
• /
• 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
• /
• v.70 no.6
• /
• pp.649-659
• /
• 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
• /
• v.58 no.2
• /
• pp.277-300
• /
• 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.

• Journal of Korean Society of Steel Construction
• /
• v.24 no.4
• /
• pp.399-410
• /
• 2012

In this study, vibration tests are performed on cantilevered and clamped-clamped laminated composite rectangular plates using experimental modal analysis technique. The damages are simulated by applying progressive line cracks to the laminated composite plates for damage evaluations due to crack growth. The changes of frequency response functions(FRFs), MAC values, and modal parameters (frequency, mode shape and damping ratio) of the damaged composite plates, which are obtained by the modal testing of impact hammer, are investigated. Each experimental modal parameter of the progressively damaged composite plates is compared with natural frequencies and mode shapes obtained by finite element analysis. It is seen that the damage can be evaluated from the changes in the geometric properties and structural behaviors of the laminated composite plates resulting from the model updating process of the finite element model as a benchmark.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.36 no.3
• /
• pp.155-163
• /
• 2023

Real-time monitoring technology is critical for ensuring the safety and reliability of nuclear power plant structures. However, the current seismic monitoring system has limited system identification capabilities such as modal parameter estimation. To obtain global behavior data and dynamic characteristics, multiple sensors must be optimally placed. Although several studies on optimal sensor placement have been conducted, they have primarily focused on civil and mechanical structures. Nuclear power plant structures require robust signals, even at low signal-to-noise ratios, and the robustness of each mode must be assessed separately. This is because the mode contributions of nuclear power plant containment buildings are concentrated in low-order modes. Therefore, this study proposes an optimal sensor placement methodology that can evaluate robustness against noise and the effects of each mode. Indicators, such as auto modal assurance criterion (MAC), cross MAC, and mode shape distribution by node were analyzed, and the suitability of the methodology was verified through numerical analysis.