• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 춘계학술대회 논문집
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• pp.1440-1444
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• 2011

Memory-device is one of the auxiliary components of point-switch machine; connecting front-rod and tongue-rail. The right side and left side of memory-device are different from each other. When there would be a derailing accident of rolling stock or motor-car, the memory-device properly bends and protects the internal of point-switch machine. Memory-device is one of the important site maintenance spare parts. Memory-device for each of right and left side should be secured so that they can be installed on correct side during an exchange work. This study suggests the development of memory-device with different left and right side and the performance test of it. The study intends to contribute in the convenience improvement of maintenance by improving the unification of memory-device.

• 대한원격탐사학회지
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• 제38권5_3호
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• pp.939-951
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• 2022

자율주행차에 있어 가장 중요한 요소는 차량 주변 환경과 정확한 위치를 인식하는 것이며, 이를 위해 다양한 센서와 항법 시스템 등이 활용된다. 하지만 센서와 항법 시스템의 한계와 오차로 인해 차량 주변 환경과 위치 인식에 어려움이 있다. 이러한 한계를 극복하고 안전하고 편리한 자율주행을 위해서 고정밀의 인프라 정보를 제공하는 정밀도로지도(high definition map, HD map)의 필요성은 증대되고 있다. 정밀도로지도는 모바일 매핑 시스템(mobile mapping system, MMS)을 통해 획득된 3차원 point cloud 데이터를 이용하여 작성된다. 하지만 정밀도로지도 작성에 많은 양의 점을 필요로 하고 작성 항목이 많아 수작업이 요구되어 많은 비용과 시간이 소요된다. 본 연구는 정밀도로지도의 필수 요소인 차선을 포함한 도로, 연석, 보도, 중앙분리대, 기타 6개의 클래스로 MMS point cloud 데이터를 유의미한정보로 분할하여 정밀도로지도의 효율적인 작성에 목적을 둔다. 분할에는 머신러닝 모델인 random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN) 그리고 gradient boosting machine (GBM)을 사용하였고 MMS point cloud 데이터의 기하학적, 색상, 강도 특성과 차선 분할을 위해 추가한 도로 설계적 특성을 고려하여 11개의 변수를 선정하였다. 부산광역시 미남역 일대 5차선도로 130 m 구간의 MMS point cloud 데이터를 사용하였으며, 분할 결과 각 모델의 평균 F1 score는 RF 95.43%, SVM 92.1%, GBM 91.05%, KNN 82.63%로 나타났다. 가장 좋은 분할 성능을 보인 모델은 RF이며 클래스 별 F1 score는 도로, 보도, 연석, 중앙분리대, 차선에서 F1 score가 각각 99.3%, 95.5%, 94.5%, 93.5%, 90.1% 로 나타났다. RF 모델의 변수 중요도 결과는 본 연구에서 추가한 도로 설계적 특성의 변수 XY dist., Z dist. 모두 mean decrease accuracy (MDA), mean decrease gini (MDG)가 높게 나타났다. 이는 도로 설계적 특성을 고려한 변수가 차선을 포함한 여러 클래스 분할에 중요하게 작용하였음을 뜻한다. 본 연구를 통해 MMS point cloud를 머신러닝 기반으로 차선을 포함한 여러 클래스로 분할 가능성을 확인하고 정밀도로지도 작성 시 수작업으로 인한 비용과 시간 소모를 줄이는데 도움이 될 것으로 기대한다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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• pp.477-482
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• 2005

Recently, client computing trend has been changed from server oriented information application to network based P2P(Peer to Peer) services. The conventional client/server method has the merit of accessing abundant information, on the other side P2P has the merit of synchronized community support and information exchange. P2P has four meaning of point to point, peer to peer, person to person and path to profitability. In manufacturing system field, the second meaning is interested. P2P is classified to three type such as conventional client/server, hybrid P2P and pure P2P. The third is really peer to peer concept. The related technologies with P2P are P2P searching, XML, cooperation, IPv6, computing sharing and P2P communication. This paper describes the scheme of P2P and related contents. And through the P2P based technology, a P2P-based collaborative machine and a vertical portal machine are introduced in this paper. The scheme of the machines mentioned above is suggested for cooperation in manufacturing system and u-Manufacturing.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.43-45
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• 2004

This paper represents the improvement of floating point operation for AC servo motor controller based on fixed point operation DSP. TMS320F2812 has fixed point operation processing structure. The controller parameters are modified to the digitized data by scaling the original parameters. TMS320F 2812 is a 32-bit processor, and it could have enough accuracy to get the digitized data this procedure is implemented and the experiments controling a AC servo system.

• 한국산업융합학회 논문집
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• 제13권4호
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• pp.205-209
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• 2010

Even the domestically small-and medium-sized companies progressed development in the monitoring equipment of inspecting run out in steel wheel aiming to supply and generalize through developing the monitoring equipment for securing quality technology and enhancing quality-test level. Run-Out value in vehicle wheel was measured with Computer & Servo system by using Low-Point marking machine control system, which is this development product. Low-Point value was operated and calculated. It marked by revolving wheel as much as the demanded measurement value based on 1ST harmony curve. Thus, the shipment of inferior product, which occurs in the measurement by the existing worker, could be blocked in advance. In the existing case, 60 sec. was required for inspecting 1 product. However, it came to bring about a rise in production volume through shortening inspection time to 8 seconds and improving workers' operating environment.

• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• 한국정밀공학회지
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• 제16권12호
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• pp.109-118
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• 1999

The objective of this research is to develop an effective inspection planning strategy for sculpture surfaces in OMM(On-Machine Measurement) process. As a first step, effective measuring point locations are determined to obtain optimum results for given sampling numbers. Two measuring point selection methods are suggested in this study based on newly proposed CAD/CAM/CAI integration concept: (1) by the prediction of cutting errors, (2) by considering cutter contact points to avoid the measurement errors caused by cusps. As a next step, the TSP(Traveling Salesman Problem)algorithm is applied to minimize the probe moving distance. Appropriate simulations and experiments are performed to verify the proposed inspection planning strategy in this study, and the results are analyzed.

• Journal of the Optical Society of Korea
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• 제18권5호
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• pp.523-530
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• 2014

Machine material and structural strain are critical factors for appraising mechanical properties and safety. Particularly in three and four-point bending tests, which appraise the deflection and flexural strain of an object due to external force, measurements are made by the crosshead movement or deflection meter of a universal testing machine. The Digital Image Correlation (DIC) method is one of the non-contact measurement methods. It uses the image analyzing method that compares the reference image with the deformed image for measuring the displacement and strain of the objects caused by external force. Accordingly, the advantage of this method is that the object's surface roughness, shape, and temperature have little influence. However, its disadvantage is that it requires extensive time to compare the reference image with the deformed image for measuring the displacement and strain. In this study, an algorithm is developed for DIC that can improve the speed of image analysis for measuring the deflection and strain of an object caused by a three-point bending load. To implement this algorithm for improving the speed of image analysis, LabVIEW 2010 was used. Furthermore, to evaluate the accuracy of the developed fast correlation algorithm, the deflection of an aluminum specimen under a three-point bending load was measured by using the universal test machine and DIC measurement system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1245-1248
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• 2004

This paper presents a new technique to analyze data on the coordinate x, y, z and apply these data to design the motion control to improve the efficiency of the engraving machine so that it can engrave accordingly in 3 dimensions. First, the tool path on the x-y plane is analyzed to be synchronized with the z-axis. The digital data is then sent to the motion control to guide the movement of the engrave point on the x-y plane. Tool path moves along the x-axis with zero degree and different values of the y-axis according to the coordinate of the digital data and the analysis along z-axis to determine the depth for engraving. The depth can be specified from the gray level with the 256 levels of resolution. The data obtained includes the distances on x-axis, y-axis, and z-axis, the acceleration of the engrave point's movement, and the speed of the engrave point's movement. These data is then transfered to the motion control to guide the movement of the engrave point along the z-axis associated with the x-y plane. The results indicate that engraving using this technique is fast and continuous. The specimen obtained looks perfect in 3D view.

• 한국통신학회논문지
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• 제40권6호
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• pp.1081-1090
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• 2015

This work proposes a theoretic framework for the performance assessment of an access point in the IP network that accommodates MD (Machine Data) and HD (Human Data). First, we investigate typical resource allocation methods in LTE for MD and HD. After that we carry out a Max-Min analysis about the surplus and deficiency of network resource seen from MD and HD. Finally, we evaluate the performance via numerical experiment.