• The Journal of the Acoustical Society of Korea
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• v.36 no.2
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• pp.89-99
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• 2017

Multi-rotor type UAV (Unmanned Aerial Vehicle)s are expanding their applications not only for military purposes but also for private industries such as aerial photography and unmanned delivery vehicles. For wider use of unmanned aerial vehicles, studies should be carried out to improve aerodynamic efficiency and reduce noise of propellers, which can be achieved based on techniques of predicting aerodynamic performance and noise in a given environment. In this study, aerodynamic and noise prediction techniques were developed for a small unmanned aerial vehicle propeller, and it was verified by comparing it with actual measurement results. Thrust and torque due to the change of r/min and the frequency spectral prediction at a given position secured the reliability of the prediction method, which provides a basis for the shape design of the propeller.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.522-526
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• 2015

Generally, underwater unmanned vehicle have adopted an inertial navigation system (INS), dead reckoning (DR), acoustic navigation and geophysical navigation techniques as the navigation method because GPS does not work in deep underwater environment. Even if the tactical inertial sensor can provide very detail measurement during long operation time, it is not suitable to use the tactical inertial sensor for small size and low cost UUV because the tactical inertial sensor is expensive and large. One alternative to INS is attitude heading reference system (AHRS) with the micro-machined electro mechanical system (MEMS) inertial sensor because of MEMS inertial sensor's small size and low power requirement. A cost effective and small size attitude heading reference system (AHRS) which incorporates measurements from 3-axis micro-machined electro mechanical system (MEMS) gyroscopes, accelerometers, and 3-axis magnetometers has been developed to provide a complete attitude solution for UUV. The AHRS based MEMS overcome many problems that have inhibited the adoption of inertial system for small UUV such as cost, size and power consumption. Several evaluation experiments were carried out for the validation of the developed AHRS's function and these experiments results are presented. Experiments results prove the fact that the developed MEMS AHRS satisfied the required specification.

• Environmental Analysis Health and Toxicology
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• v.19 no.2
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• pp.161-167
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• 2004

Air quality monitoring is a primary activity for industrial and social environment. The government identifies the pollutants that each industry must monitor. Especially, the VOCs (Volatile Organic Compounds), which are very harmful to human body and environment atmosphere, should be controlled under the government policy. However, the VOCs, which have not been confirmed in emission sources are very difficult to monitor. It is needed to develop the monitoring system that allow the continuous and in situ measurement of VOCs mixture in different environmental matrices. Gas chromatography and mass spectrometry are the most prevalent current techniques among those available for the analysis of VOCs. But, they need a large size analytical instrument, which costs a great deal for purchase and operation. In addition, it has some limitations for realtime environmental monitoring such as location problems and slow processing time. Recently, several companies have commercialized a portable VOCs measurement systems, which cannot classify various kinds of VOCs but total quantities. We have developed a VOCs measurement system, which recognizes various kinds and quantities of VOCs, such as benzene, toluene, and xylene (BTX). Also, it can be used as a stand- alone type and/or fixed type in the vehicle with rack for real -time environmental monitoring.

• Journal of Advanced Navigation Technology
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• v.9 no.1
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• pp.10-18
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• 2005

These studies developed system as well as its algorithm which can measure traffic flow and vehicle speed on the highway as well as road by using industrial television(ITV) system. This algorithm used the real time processing of dynamic images. The processing algorithm of dynamic images is developed and proved its validity by frame grabber. Frame grabber can process the information of a small number of sample points only instead of the whole pixel of the images. In the techniques of this algorithm, we made approximate contour of vehicle by allocating sampling points in cross-direction of image, and recognized top of contour of vehicle. Applying these technique, we measured the number of passing vehicles of one lane as well as multilane. Speed of each vehicle is measured by computing the time difference between a pair of sample points on two sample points lines.

• Smart Structures and Systems
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• v.33 no.3
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• pp.189-199
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• 2024

To properly extract the strain components under varying operational conditions is very important in bridge health monitoring. The abnormal sensor readings can be correctly identified and the expected operational performance of the bridge can be better understood if each strain components can be accurately quantified. In this study, strain components under varying load conditions, i.e., temperature variation and live-load variation are evaluated based on field strain measurements collected from a real concrete box-girder bridge. Temperature-induced strain is mainly regarded as the trend variation along with the ambient temperature, thus a smoothing technique based on the wavelet packet decomposition method is proposed to estimate the temperature-induced strain. However, how to effectively extract the vehicle-induced strain is always troublesome because conventional threshold setting-based methods cease to function: if the threshold is set too large, the minor response will be ignored, and if too small, noise will be introduced. Therefore, an autoencoder framework is proposed to evaluate the vehicle-induced strain. After the elimination of temperature and vehicle-induced strain, the left of which, defined as the model error, is used to assess the operational performance of the bridge. As empirical techniques fail to detect the degraded state of the structure, a clustering technique based on Gaussian Mixture Model is employed to identify the damage occurrence and the validity is verified in a simulation study.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.43-54
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• 2012

This paper presents a new localization technique of an UGV(Unmanned Ground Vehicle) by matching ortho-edge images generated from a DSM (Digital Surface Map) which represents the 3D geometric information of an outdoor navigation environment and 3D range data which is obtained from a LIDAR (Light Detection and Ranging) sensor mounted at the UGV. Recent UGV localization techniques mostly try to combine positioning sensors such as GPS (Global Positioning System), IMU (Inertial Measurement Unit), and LIDAR. Especially, ICP (Iterative Closest Point)-based geometric registration techniques have been developed for UGV localization. However, the ICP-based geometric registration techniques are subject to fail to register 3D range data between LIDAR and DSM because the sensing directions of the two data are too different. In this paper, we introduce and match ortho-edge images between two different sensor data, 3D LIDAR and DSM, for the localization of the UGV. Details of new techniques to generating and matching ortho-edge images between LIDAR and DSM are presented which are followed by experimental results from four different navigation paths. The performance of the proposed technique is compared to a conventional ICP-based technique.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.4
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• pp.51-59
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• 2016

Measurements of the automobile manufacturers are available anywhere and anytime, directly based on the criterion of failure is measured. The maintenance of high-precision production activities is direct evidence of the fact that competitive manufacturing activities are very important in determining the success of companies to recall defective starting from raw material costs. The current manufacturing sites produce calipers and clearance gauge the degree of tool only specific. Therefore, judging the quality, including the number of errors, requires a lot of attention to the dimension failures in day-to-day measurements and measurement tasks and duties repeated in difficult situations. In this paper, we aim to develop a vehicle manufacturing plant site using each of the manufacturing processes while operating a measurement tool. We display it using the Image Processing PC-based S/W with all those visual facts by management and recorded as image information a more accurate and current situation to obtain information and share visual measurements. We carry out research on the design and development vision inspection algorithm applied for pattern-recognition techniques that can help manufacturing site quality control.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.276-282
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• 2005

These studies developed system as well as its algorithm which can measure traffic flow and vehicle speed on the highway as well as road by using industrial television(ITV) system. This algorithm used the real time processing of dynamic images. The processing algorithm of dynamic images is developed and proved its validity by frame grabber. Frame grabber can process the information of a small number of sample points only instead of the whole pixel of the images. In the techniques of this algorithm, we made approximate contour of vehicle by allocating sampling points in cross-direction of image, and recognized top of contour of vehicle. Applying these technique, we measured the number of passing vehicles of one lane as well as multilane. Speed of each vehicle is measured by computing the time difference between a pair of sample points on two sample Points lines.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.12
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• pp.1084-1088
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• 2009

The measurement of dynamic stagger in electric railways is one of the key test parameters to increase speed and maintain safety in electric railways. This paper is introduces a non-contact optical-based measuring instrument of a catenary system in electric railways. The instrument is implemented by utilizing a CCD (Charge Coupled Device) camera installed on the roof of a vehicle for vision acquisition and image processing techniques including the Canny edge detector and the Hough transform to detect contact wires and calculate dynamic stagger. To check the validity of our approach for the intended application, we measured stagger of a overhead wire of a Korea Tilting Train (TTX). The non-contact optical-based measurement system proposed in this paper performs real-time stagger measurement of an activated high-voltage contact wire. By results of this paper, the instrument should be applied to assess performance and reliability of newly developed electric railway vehicles.

• Journal of the Korean Geosynthetics Society
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• v.19 no.1
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• pp.45-53
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• 2020

There is an increasing tendency to try to make predictive analysis using measurement data based on machine learning techniques in the railway industries. In this paper, it was predicted that Track quality index (TQI) using vehicle acceleration data based on the machine learning method. The XGB (XGBoost) was the most accurate with 85% in the all data sets. Unlike the SVM model with a single algorithm, the RF and XGB model with a ensemble system were considered to be good at the prediction performance. In the case of the Surface TQI, it is shown that the acceleration of the z axis is highly related to the vertical direction and is in good agreement with the previous studies. Therefore, it is appropriate to apply the model with the ensemble algorithm to predict the track quality index using the vehicle vibration acceleration data because the accuracy may vary depending on the applied model in the machine learning methods.