• 한국수소및신에너지학회논문집
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• 제29권6호
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• pp.642-647
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• 2018

Gas compressors are mostly driven by motors. It is important to measure the power of motors to evaluate their power efficiency, because the mechanical loads of gas compressors are always varied. In order to measure the power given to the driving motors, the torque should be measured. Manufacturers of compressors usually use the torque data to calculate the compressors qualities such as power consumption, efficiencies and failures. In general, measurements for the shaft torque of the compressors have been based upon contact types, strain gauges. In the cases of larger compressors, the contact type of strain gauges have several disadvantages such as large size and high cost. In this study, a relatively inexpensive and simple torque sensing technique that is not restricted to shaft diameter is introduced using visualization technique. Particle image velocimetry (PIV) has been adopted to complete non-contact torques measurements for rotating motors. In order to compare the performance of the newly constructed torque measurement technique, torque measurement by a transducer based on MEMS technology has been performed simultaneously during experiments.

• Smart Structures and Systems
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• 제29권1호
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.353-373
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• 2012

The instrumented Canton Tower is a 610 m high-rise structure, which has been considered as a benchmark problem for structural health monitoring (SHM) research. In this paper, an improved automatic modal identification method is presented based on a natural excitation technique in conjunction with the eigensystem realization algorithm (NExT/ERA). In the proposed modal identification method, damping ratio, consistent mode indicator from observability matrices (CMI_O) and modal amplitude coherence (MAC) are used as criteria to distinguish the physically true modes from spurious modes. Enhanced frequency domain decomposition (EFDD), the data-driven stochastic subspace identification method (SSI-DATA) and the proposed method are respectively applied to extract the modal parameters of the Canton Tower under different environmental conditions. Results of modal parameter identification based on output-only measurements are presented and discussed. User-selected parameters used in those methods are suggested and discussed. Furthermore, the effect of environmental conditions on the dynamic characteristics of Canton tower is investigated.

• 응용통계연구
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• 제7권1호
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• pp.149-158
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• 1994

커널 추정은 커널함수와 bandwidth에 의해서 결정이 된다. 그러나 평활의 정도를 조절하는 적절한 bandwidth를 찾는 것이 더욱 중요한 문제이다. 그러므로 이론적으로 최적의 bandwidth와 비교하여 실제자료에 잘 적용될 수 있는 적절한 bandwidth를 어떻게 찾느냐는 것이 문제가 된다. 본 논문에서는 평균제곱오차(mean square error)의 편의(bias)와 분산(variance)의 관계를 통하여 커널을 이용한 회귀선의 추정에 있어서 간단하고 효과적인 local bandwidth를 찾을 수 있는 알고리즘을 제안하였다.

• Earthquakes and Structures
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• 제6권2호
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• pp.201-216
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• 2014

Many building codes use the empirical equation to determine fundamental period of vibration where in effect of length, width and the stiffness of the building is not explicitly accounted for. Also the equation, estimates the fundamental period of vibration with large safety margin beyond certain height of the building. An attempt is made to arrive at the simple empirical equations for fundamental period of vibration with adequate safety margin, using soft computing technique of Genetic Programming (GP). In the present study, GP models are developed in four categories, varying the number of input parameters in each category. Input parameters are chosen to represent mass, stiffness and geometry of the buildings directly or indirectly. Total numbers of 206 buildings are analyzed out of which, data set of 142 buildings is used to develop these models. It is observed that GP models developed under B and C category yield the same equation for fundamental period of vibration along X direction as well as along Y direction whereas the equation of fundamental period of vibration along X direction and along Y direction is of the same form for category D. The equations obtained as an output of GP models clearly indicate the influence of mass, geometry and stiffness of the building over fundamental period of vibration. These equations are then compared with the equation recommended by other researcher.

• 한국지능시스템학회논문지
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• 제11권7호
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• pp.603-610
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• 2001

Industrial processes are normally operated by skilled humans who have the cumulative and logical information about the system. Fuzzy control has been investigated for many application. Intelligent control approaches based on fuzzy logic have a chance to include human thinking. This paper represents modeling approach based upon operators knowledge without mathematical model of the system and optimize the controller. The experimented system is constructed for sending a ball to the goal position using wind of two DC motors in the predefined path. A vision camera to mimic human eyes detects the ball position. The system used in this experiment could be hardly modeled by mathematical methods and ould not be easily controlled by conventional manners. The controller is designed based on the input-output data and experimental knowledge obtained by trials, and optimized under the predefined performance criterion. And this paper shows the data adaptation for changeable operating condition. When the system is driven in the abnormal condition with unconsidered noise, the new optimal operating parameters could be defined by adjusting membership functions. Thus, this technique could be applied in industrial fields.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.177-180
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• 1999

Nowadays, one of the major technical issues in manufacturing is to create an environment to promote collaboration among diverse engineering activities. Collaborative engineering is an innovative approach integrating widely distributed engineering activities through promoting information sharing and actual collaboration. It requires close interactions among developers, suppliers and customers, and consideration of entire product life cycle from concept to disposal. A carefully-designed operating system is crucial for successful collaboration of many different activities in a Networked Virtual Manufacturing System(NVMS). High extensibility, flexibility and efficiency ale the key characteristics requested of an operating system to handle the complexity of the NVMSs. In this paper, we propose a model of the operating system for collaborative engineering using concurrent quasi-procedural method(QPM). QPM is a goal-driven data management technique for distributed and parallel computing environments. It is to be applied to the evaluation of activities to be executed, validities of input data, execution path of activities for a needed output, and expected to greatly improve the productivity of operations by preventing redundant evaluations. Collaboration among many different engineering activities in NVMSs is to be performed by the network of agents that encapsulate the capabilities of both users and their tools.

• Computers and Concrete
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• 제13권6호
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• pp.765-780
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• 2014

Many building codes use the empirical equation to determine fundamental period of vibration where in effect of length, width and the stiffness of the building is not explicitly accounted for. In the present study, ANN models are developed in three categories, varying the number of input parameters in each category. Input parameters are chosen to represent mass, stiffness and geometry of the buildings indirectly. Total numbers of 206 buildings are analyzed out of which, data set of 142 buildings is used to develop these models. It is demonstrated through developed ANN models that geometry of the building and the sizes of the columns are significant parameters in the dynamic analysis of building frames. The testing dataset of these three models is used to obtain the empirical relationship between the height of the building and fundamental period of vibration and compared with the similar equations proposed by other researchers. Experiments are conducted on Mild Steel frames using uniaxial shake table. It is seen that the values obtained through the ANN models are close to the experimental values. The validity of ANN technique is verified by experimental values.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 춘계학술대회
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• pp.265-268
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• 2010

현재의 IP 위주의 역추적은 Proxy와 우회기법의 발달로 인하여 Real IP 역추적에 어려움이 있다. 또한 IP역추적 후에도 실제 Source IP인지 확인이 어렵다. 따라서 본 논문에서는 지능형 SQL Query에 대한 field, column, table 등의 요소값과 매칭되는 key값을 분석하고 여기에서 사용되는 Data값의 hit point를 분석하여 최초 사용자에 대한 Application Layer를 분석함으로써 IP 역추적에 대한 포렌식 증거로 삼는다. 본 연구는 포렌식과 DB보안 등 전자거래 발전에 기여할 것이다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.225-227
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• 2003

Traditional photogrammetry and satellite image rectification technique have been developed based on control-points for many decades. These techniques are driven from linked points in image space and the corresponding points in the object space in rigorous colinearity or coplanarity conditions. Recently, digital imagery facilitates the opportunity to use features as well as points for images rectification. These implementations were mainly based on rigorous models that incorporated geometric constraints into the bundle adjustment and could not be applied to the new high-resolution satellite imagery (HRSI) due to the absence of sensor calibration and satellite orbit information. This research is an attempt to establish a new Line Based Transformation Model (LBTM), which is based on linear features only or linear features with a number of ground control points instead of the traditional models that only use Ground Control Points (GCPs) for satellite imagery rectification. The new model does not require any further information about the sensor model or satellite ephemeris data. Synthetic as well as real data have been demonestrated to check the validity and fidelity of the new approach and the results showed that the LBTM can be used efficiently for rectifying HRSI.