• 한국전자통신학회논문지
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• 제11권2호
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• pp.185-190
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• 2016

본 논문에서는 이동 로봇에 마커를 부착하여 이를 카메라를 통해 자동으로 추출하여 이동 로봇의 운동 특성을 분석하는 방법에 대해 다루도록 한다. 이동 로봇의 구동을 위한 제어 알고리듬의 개발이나 자율 이동 관련 알고리듬 개발시 인자값에 따른 운동 특성 분석은 중요한 부분이다. 이의 분석을 위해 본 논문에서는 네 개의 체스보드 형태의 마커를 이동 로봇에 부착하여 사용하도록 한다. 이들 네 개의 마커들은 동일 평면에 존재하도록 배치하도록 한다. 평면 호모그라피를 이용하여 로봇의 실제 이동량을 계산하도록 한다. 제시된 방법은 P3-AT 로봇을 이용하여 실험을 수행하였으며 안정적인 운동 분석이 가능하였다.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.305-308
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• 2002

More complex radiotherapy techniques using multi leaf collimation(MLC) such as intensity-modulated radiation therapy(IMRT) has been increasing the significance of verification of leaf position and motion. Due to the reliability and robustness, quality assurance(QA) of MLC is usually performed with portal films. However, the advantage of ease of use and capability of providing digital data of electronic portal imaging devices(EPIDs) have attracted many attentions as alternatives of films for routine quality assurance in spite of the concerns about their clinical feasibility, efficacy, and the cost to benefit ratio. In our work, the method of routine QA of MLC using electronic portal imaging(EPI) was developed. The verification of availability of EPI images for routine QA was performed by comparison with those of the portal films which were simultaneously obtained when radiation was delivered and known prescription input to MLC controller. Specially designed test patterns of dynamic MLC were applied to image acquisition. Quantitative off-line analysis using edge detection algorithm enhanced the verification procedure in addition to on-line qualitative visual assessment. In conclusion, the EPI is available enough for routine QA with the accuracy of portal films.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.603-608
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• 2001

In order to distinguish fault electric motors automatically in real time. an intelligent diagnosis technique may be required. This paper presents an automatic fault detection system for electric motors by using their acoustic noises. Time signals of each candidate motor were measured in an anechoic chamber for further analysis. Spectral analysis was first carried out and they showed that two typical types of fault motors could be successfully distinguished in the frequency domain; bearing faults and scratches. Unlike the trend of normal motors that shows only a single dominant peak at around 2000 ㎐, several peaks are bunched together in bearing fault motors. On the other hand, large frequency noises at around 6500 ㎐ are newly arisen in scratchy fault motors. However, the processing time for spectral analysis was rather long for a real time application in production lines. Thus, a number of band-pass filters were used in the time domain instead for a real time application. Before applying filters, the bands of filters were set from the information of spectral analysis. By applying a set of band-pass filters, the RMS values of each filtered signal were calculated, and thus the normal and damaged motors could be successfully distinguished.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2007년도 제29회 추계학술대회논문집
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• pp.55-59
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• 2007

초음파를 이용한 추진기관의 접착 계면 검사는 결함 검출 능력과 경제성이 우수하다고 알려져 있다. 하지만, 추진기관의 접착 구조는 다중 계면이므로 송신 펄스와 수신 펄스의 시간 간격이 짧아서 반사 신호의 분리가 어렵기 때문에 초음파의 신호 분석에는 많은 시간과 노력이 소요된다. 이런 이유로 추진기관의 초음파시험은 연소관과 내열재 사이의 미접착 결함과 같이 극히 제한된 영역에 대해서만 자동화 시스템으로 수행하고 있다. 본 논문에서는 기존의 초음파시험으로 검출이 불가능했던 라이너와 추진제 미접착 결함을 초음파의 공진 현상과 램파 특성을 이용하여 검출하는 새로운 기법에 대해 기술하였다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제8권3호
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• pp.243-251
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• 2016

Autonomous Underwater Vehicles (AUVs) generally work in complex marine environments. Any fault in AUVs may cause significant losses. Thus, system reliability and automatic fault diagnosis are important. To address the actuator failure of AUVs, a fault diagnosis method based on the Gaussian particle filter is proposed in this study. Six free-space motion equation mathematical models are established in accordance with the actuator configuration of AUVs. The value of the control (moment) loss parameter is adopted on the basis of these models to represent underwater vehicle malfunction, and an actuator failure model is established. An improved Gaussian particle filtering algorithm is proposed and is used to estimate the AUV failure model and motion state. Bayes algorithm is employed to perform robot fault detection. The sliding window method is adopted for fault magnitude estimation. The feasibility and validity of the proposed method are verified through simulation experiments and experimental data.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.1408-1415
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• 2007

To operate Platform Screen Door (PSD) automatically, the operational data of PSD and the train must be interfaced properly. PSD and train are operated together by the signaling system in Automatic Train Operation (ATO) signaling system zone where interfaces are provided between PSD and train. However, the additional PSD interface system with train is required in train operating zone without the interface between PSD and train. For the PSD interface, the wireless communication system or the train status (train correct stop status / train door status) detection system has been used. Seoul Metro line No.2. has the PSD wireless communication system using 447MHz band RF. For the safety of PSD operation, it is required to prevent RF interference in the subway environment where many frequencies exist. In this paper, the PSD wireless communication system is developed using 2.4GHz band RF to prevent the interference of the wireless communication and increase the traffic of the PSD interface. Furthermore, the improved system can store, manage and display the PSD and train operational data using Human Machine Interface (HMI) in the train's driver cab.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1104-1120
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• 2020

The chest X-rays are a common way to diagnose lung cancer or pneumonia. In particular, the finding of a lung nodule is the most important problem in the early detection of lung cancer. Recently, a lot of automatic diagnosis algorithms have been studied to find the lung nodules missed by doctors. The algorithms are typically based on segmentation network like U-Net. However, the occurrence of false positives that similar to lung nodules present outside the lungs can severely degrade performance. In this study, we propose a multi-task learning method that simultaneously learns the lung region and nodule-labeled data based on the prior knowledge that lung nodules exist only in the lung. The proposed method significantly reduces false positives outside the lung and improves the recognition rate of lung nodules to 83.8 F1 score compared to 66.6 F1 score of single task learning with U-net model. The experimental results on the JSRT public dataset demonstrate the effectiveness of the proposed method compared with other baseline methods.

• 한국가시화정보학회지
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• 제13권3호
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• pp.15-19
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• 2015

We developed a high-throughput microscopy (HTM) method which enabled us to replace a conventional phase contrast microscopy (PCM) method that has been used as a standard analytical method for airborne asbestos. We could obtain the concentration of airborne asbestos fibers under detection limit by automated image processing and analysis using HTM method. Here we propose an improved image processing algorithm with variable parameters to enhance the accuracy of the HTM analysis. Since the variable parameters that compensate the difference of the brightness are applied to the individual images in our new image processing method, it is possible to enhance the accuracy of the automatic image analysis method for sample slides with low asbestos concentration that caused errors in binary image processing. We demonstrated that enumeration of fibers by improved image processing algorithm remarkably enhanced the accuracy of HTM analysis in comparison with PCM. The improved HTM method can be a potential alternative to conventional PCM.

• Journal of Welding and Joining
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• 제18권4호
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• pp.70-75
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• 2000

The weld seam tracking system for arc welding process uses various kinds of sensors such as arc sensor, vision sensor, laser displacement and so on. Among the variety of sensors available, electro-magnetic sensor is one of the most useful methods especially in sheet metal butt-joint arc welding, primarily because it is hardly affected by the intense arc light and fume generated during the welding process, and also by the surface condition of weldments. In this study, a dual-electromagnetic sensor, which utilizes the induced current variation in the sensing coil due to the eddy current variation of the metal near the sensor, was developed for arc welding of sheet metal butt-joints. The dual-electromagnetic sensor thus detects the offset displacement of weld line from the center of sensor head even though there's no clearance in the joint. A set of design variables of the sensor were determined for the maximum sensing capability through the repeated experiments. Seam tracking is performed by correcting the position of sensor to the amount of offset displacement every sampling period. From the experimental results, the developed sensor showed the excellent capability of weld seam detection when the sensor to workpiece distance is near less than 5 mm, and it was revealed that the system has excellent seam tracking ability for the butt-joint of sheet metal.

• 한국ITS학회 논문지
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• 제2권2호
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• pp.23-29
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• 2003

본 연구는 지능형 교통시스템(ITS)의 정보수집 및 제공기술 중, 통행시간 산출과 제공을 위한 요소기술인 주행차량자동인식시스템(AVI)의 현장시험 적용과 평가에 관한 실험 연구이다. 일반국도에서의 현장평가는 비접촉 방식의 차량검출과 이를 통해 얻은 자료로부터 구간 통행시간을 산출하는 방식을 제안하고, 실측데이터를 통해 현장 적용 성능을 검토하였다 본 연구는 현장 적용성능 평가 방법과 이를 통해 실측 데이터의 검지율과 인식율 그리고 통행시간을 분석하였다.