• Smart Structures and Systems
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• 제3권3호
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• pp.281-298
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• 2007

The load carrying capacity of a bridge needs to be properly assessed to operate the bridge safely and maintain it efficiently. For the evaluation of load carrying capacity considering the current state of a bridge, static and quasi-static loading tests with weight-controlled heavy trucks have been conventionally utilized. In these tests, the deflection (or strain) of the structural members loaded by the controlled vehicles are measured and analyzed. Using the measured data, deflection (or strain) correction factor and impact correction factor are calculated. These correction factors are used in the enhancement of the load carrying capacity of a bridge, reflecting the real state of a bridge. However, full or partial control of the traffic during the tests and difficulties during the installment of displacement transducers or strain gauges may cause not only inconvenience to the traffic but also the increase of the logistics cost and time. To overcome these difficulties, an alternative method is proposed using an excited response part of full measured ambient acceleration data by ordinary traffic on a bridge without traffic control. Based on the modal properties extracted from the ambient vibration data, the initial finite element (FE) model of a bridge can be updated to represent the current real state of a bridge. Using the updated FE model, the deflection of a bridge akin to the real value can be easily obtained without measuring the real deflection. Impact factors are obtained from pseudo-deflection, which is obtained by double-integration of the acceleration data with removal of the linear components on the acceleration data. For validation, a series of tests were carried out on a steel plategirder bridge of an expressway in Korea in four different seasons, and the evaluated load carrying capacities of the bridge by the proposed method are compared with the result obtained by the conventional load test method.

• Smart Structures and Systems
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• 제15권2호
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• pp.355-373
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• 2015

An optimal sensor placement (OSP) method based on structural subsection technique (SST) and model reduction technique was proposed for modal identification of truss structures, which was conducted using genetic algorithm (GA). The constraints of GA variables were determined by SST in advance. Subsequently, according to model reduction technique, the optimal group of master degrees of freedom and the optimal objective function value were obtained using GA in a case of the given number of sensors. Correspondingly, the optimal number of sensors was determined according to optimal objective function values in cases of the different number of sensors. The proposed method was applied on a scaled jacket offshore platform to get its optimal number of sensors and the corresponding optimal sensor layout. Then modal kinetic energy and modal assurance criterion were adopted to evaluate vibration energy and mode independence property. The experiment was also conducted to verify the effectiveness of the selected optimal sensor layout. The results showed that experimental modes agreed reasonably well with numerical results. Moreover the influence of the proposed method using different optimal algorithms and model reduction technique on optimal results was also compared. The results showed that the influence was very little.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 춘계학술대회
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• pp.735-737
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• 2015

본 논문은 SaaS(Software as a Service) 기반의 건설공정전송 및 안전관리 시스템을 건설작업에 활용하여 공정관리와 안전관리에 적용함으로써 초고속 무선인터넷을 통해 이루어지는 다양한 유형의 건설 공정에 대한 일정 및 결과와 안전관리에 대한 체계적인 수단을 확보할 수 있고 공정 내에서 이루어지는 모든 관리 체계를 신속하고 정확하게 관리할 수 있다.작업자는 스마트폰을 활용하여 감독관으로 작업을 지시받고 작업의 현황과 결과를 보고한다. 또한 비상상황 시 감독관에게 보고를 즉시 할수 있으며 일정시간 이상 스마트 폰 진동 발생이 없는 경우 작업자에게 위험 상황을 체크하게 된다. 감독관의 경우 수립된 공정별 업무를 지시하고 결과를 확인하며 현장 작업자 위험 상황의 조치명령을 내리고 미흡한 부분을 제시함으로써 만족되는 결과를 얻게 된다. 또한 소프트웨어(서버)의 경우 작업에 관련된 모든 자료를 저장하고 회원관리 및 보안을 담당하였다.

• Smart Structures and Systems
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• 제21권5호
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• pp.695-703
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• 2018

Based on monitoring data collected from the Nanjing Dashengguan Bridge over the last five years, this paper systematically investigates the effects of temperature field and train loadings on the structural responses of this long-span high-speed railway bridge, and establishes the early warning thresholds for various structural responses. Then, some lessons drawn from the structural health monitoring system of this bridge are summarized. The main context includes: (1) Polynomial regression models are established for monitoring temperature effects on modal frequencies of the main girder and hangers, longitudinal displacements of the bearings, and static strains of the truss members; (2) The correlation between structural vibration accelerations and train speeds is investigated, focusing on the resonance characteristics of the bridge at the specific train speeds; (3) With regard to various static and dynamic responses of the bridge, early warning thresholds are established by using mean control chart analysis and probabilistic analysis; (4) Two lessons are drawn from the experiences in the bridge operation, which involves the lacks of the health monitoring for telescopic devices on the beam-end and bolt fractures in key members of the main truss.

• Tribology and Lubricants
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• 제31권2호
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• pp.62-68
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• 2015

A magnetorheological (MR) fluid is a smart material whose rheological behavior can be controlled by varying the parameters of the applied magnetic field. Because the damping force and shear force of an MR fluid can be controlled using a magnetic field, it is widely employed in many industrial applications, such as in vehicle vibration control, powertrains, high-precision grinding processes, valves, and seals. However, the characteristics of friction caused by iron particles inside the MR fluid need to be understood and improved so that it can be used in practical applications. Surface process technologies such as polytetrafluoroethylene (PTFE) coatings and diamond-like carbon (DLC) coatings are widely used to improve the surface friction properties. This study examines the friction characteristics of an MR fluid with different surface process technologies such as PTFE coatings and DLC coatings, by using a reciprocating friction tester. The coefficients of friction are in the following descending order: MR fluid without any coating, MR fluid with a DLC coating, and MR fluid with a PTFE coating. Scanning electron microscopy is used to observe the worn surfaces before and after the experiment. In addition, energy dispersive X-ray spectroscopy is used to analyze the chemical composition of the worn surface. Through a comparison of the results, the friction characteristics of the MR fluid based on the different coating technologies are analyzed.

• Smart Structures and Systems
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• 제30권1호
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• pp.75-88
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• 2022

Engineering structures in operation essentially belong to time-varying or nonlinear structures and the resultant response signals are usually non-stationary. For such time-varying structures, it is of great importance to extract time-dependent dynamic parameters from non-stationary response signals, which benefits structural health monitoring, safety assessment and vibration control. However, various traditional signal processing methods are unable to extract the embedded meaningful information. As a newly developed technique, variational mode decomposition (VMD) shows its superiority on signal decomposition, however, it still suffers two main problems. The foremost problem is that the number of modal components is required to be defined in advance. Another problem needs to be addressed is that VMD cannot effectively separate non-stationary signals composed of closely spaced or overlapped modes. As such, a new method named generalized adaptive variational modal decomposition (GAVMD) is proposed. In this new method, the number of component signals is adaptively estimated by an index of mean frequency, while the generalized demodulation algorithm is introduced to yield a generalized VMD that can decompose mode overlapped signals successfully. After that, synchrosqueezing wavelet transform (SWT) is applied to extract instantaneous frequencies (IFs) of the decomposed mono-component signals. To verify the validity and accuracy of the proposed method, three numerical examples and a steel cable with time-varying tension force are investigated. The results demonstrate that the proposed GAVMD method can decompose the multi-component signal with overlapped modes well and its combination with SWT enables a successful IF extraction of each individual component.

• 스마트미디어저널
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• 제11권5호
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• pp.75-81
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• 2022

농업의 탄소 중립 및 기후변화 대응을 위해 그동안 내연기관 중심으로 발전해 왔던 농업기계도 온실가스의 배출이 없는 전동 기반의 기술로 전환이 필요하다. 이 연구에서는 농업용 전동 UTV의 진동과 충격을 저감시키고, 차량의 주행안정성과 조종성능을 향상하기 위하여 전동 UTV 서스펜션 설계를 위한 시뮬레이션을 수행하였다. 시뮬레이션은 차체의 공차 하중과 화물을 적재한 하중 상태로 나누어 수행되었다. UTV의 서스펜션 스프링의 가동 범위는 조건 B가 공차상태에서 가동범위 30% 이내의 수준을 나타내고, 적재 중량을 만재한 상태의 UTV 서스펜션 변위는 264mm→121mm로 작아지고, 댐핑속도는 260mm/s→300mm/s로 가동범위 60% 이내의 수준에 있음을 알 수 있었다. 다목적 농작업용을 위한 전동 UTV의 서스펜션은 주행과 지형 적응뿐 아니라 경운과 같은 견인작업에서 농작업 능력을 유지하기 위해 매우 중요한 요인이다. 이 연구의 결과는 전동 UTV를 다양한 농작업에 이용할 수 있도록 적절한 댐핑 범위를 갖는 스프링 파라메터를 결정하는데 유용하게 활용될 수 있을 것이다.

• Smart Structures and Systems
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• 제20권1호
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• pp.61-74
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• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.