• 한국인공지능학회지
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• 제11권3호
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

• 한국동물위생학회지
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• 제16권2호
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• pp.111-119
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• 1993

In this study, we carried out the rapid diagnostic system based on indirect fluorescent anti-body technique (IFAT) for detection of bacterial diseases in cultured freshwater fishes. 1. When the fishes were tested with graded dilution of Edwardsiella tarda FPC 470 bacteria detection from ten fishes Injected with $4.1{\times}10^3$colony forming unit(CFU) /ml, all of them were detected by IFAT but only two fishes were recognizable by the culture method in the tested fishes injected with $4.1{\times}10^3$CFU /ml. 2. The bacteria E. tarda could be detected by IFAT method from 1 to 48hrs after Injection in the tissues tested such as kidney, liver and spleen of the fishes, whereas detection by culture method could be recognized from 1 to 48hrs after injection In the kidney and spleen but it was not possible from preinjection to 1 hr in the liver. 3. Thus, IFAT proved to be more useful technique than plate culture method in the diagnosis of Edwardsiellosis in the freshwater fishes.

• 한국음향학회지
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• 제20권2호
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• pp.86-92
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• 2001

소음원 위치와 방위를 규명하기 위해 다양한 배열처리기술이 발전되어 왔다. 배열처리기술의 기본은 두 개의 수신센서에 수신된 신호의 시간차를 이용하여 소음원의 위치와 방위를 구하는 것으로 응용분야나 신호처리방법에 따라 고유의 특성을 갖는 빔형성기법, 상관함수기법 및 NAH (Near-Field Acoustic Holography) 등이 있다 본 연구에서는 이러한 기법들 중 광대역 소음원 탐지에 적용되는 상관함수기법을 채택하여 소음원의 대역폭과 측정 잡음원 간의 상관 관계가 위치나 방위 탐지 정확도에 미치는 영향을 분석하여 효과적인 소음원 탐지기법을 제안한다. 본 연구에서 채택한 배열의 기하학적 형상은 위치나 방위의 3차원적 모호성을 없애기 위한 3차원 비선형이며 제안된 기법의 타당성은 수치모의 실험 및 실제 실험으로 검증되었다.

• 전기학회논문지
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• 제66권6호
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• pp.995-1000
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• 2017

In this paper, we present an electrical arc detection algorithm using the mash-up analysis technique which is the core technology for the autonomous electrical safety management system(AESMS) of the multi-unit dwellings. The mash-up analysis technique analyzes the voltage, load current, zero phase current data simultaneously to judge arc faults. In order to develop the arc fault detection algorithm, the characteristics of series arc and parallel arc were analyzed. Also, we propose the mash-up analysis technique that analyzes waveforms of voltage, load current, and zero phase current at the same time. The arc fault detection algorithm was developed using the mash-up analysis technique. The developed algorithm can prevent electrical disasters in an effective way through accident prediction, and it will be used as a basic technology to introduce an autonomous electrical safety management system.

• Wind and Structures
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• 제21권6호
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• pp.709-726
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• 2015

In this study, a novel vision-based bolt-loosening monitoring technique is proposed for bolted joints connecting tubular steel segments of the wind turbine tower (WTT) structure. Firstly, a bolt-loosening detection algorithm based on image processing techniques is developed. The algorithm consists of five steps: image acquisition, segmentation of each nut, line detection of each nut, nut angle estimation, and bolt-loosening detection. Secondly, experimental tests are conducted on a lab-scale bolted joint model under various bolt-loosening scenarios. The bolted joint model, which is consisted of a ring flange and 32 sets of bolt and nut, is used for simulating the real bolted joint connecting steel tower segments in the WTT. Finally, the feasibility of the proposed vision-based technique is evaluated by bolt-loosening monitoring in the lab-scale bolted joint model.

• International Journal of Aeronautical and Space Sciences
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• 제7권1호
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• pp.73-83
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• 2006

In this paper, a redundancy management system for aircraft is studied, and fault detection and isolation algorithms of inertial sensor system are proposed. Contrary to the conventional aircraft systems, UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional fault detection and isolation (FDI) method cannot isolate multiple faults in a triple redundancy system. In this paper, two FDI techniques are proposed. First, hardware based FDI technique is proposed, which combines a parity equation approach with a wavelet based technique. Second, analytic FDI technique based on the Kalman filter is proposed, which is a model-based FDI method utilizing the threshold value and the confirmation time. To provide the reference value for detecting the fault, residuals are calculated using the extended Kalman filter. To verify the effectiveness of the proposed FDI methods, numerical simulations are performed.

• 한국컴퓨터정보학회논문지
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• 제11권3호
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• pp.187-192
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• 2006

PC환경에서 슈팅게임 시에 충돌이벤트에 대한 내용과 충돌감지 알고리즘에 대하여 소개하였고, 기존의 사각형 충돌감지 알고리즘 기법에서 단순한 사각형 충돌의 단점을 보완한, 작은 사각형 단위의 충돌 체크 기법을 제안하여 화면디자인과 함께 단순한 슈팅게임을 구현하였다. 실험과 실제 구현한 게임 화면 디자인을 통하여 제안한 알고리즘이 실제 게임에서 적용할 수 있음과 기존의 알고리즘보다 제안한 알고리즘이 우수함을 보였다.

• 스마트미디어저널
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• 제7권4호
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• pp.79-89
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• 2018

In recent years, falls among elderly people have gained serious attention as a major cause of injuries. Falls often lead to fatal consequences due to lack of prompt response and rescue. Therefore, a more accurate fall detection system and an effective feature extraction technique are required to prevent and reduce the risk of such incidents. In this paper, we proposed an efficient feature extraction technique based on multiple sliding windows and validated it through a series of experiments using supervised learning algorithms. The experiments were conducted using the public datasets obtained from tri-axial accelerometers. The results depicted that extraction of the feature from adjacent sliding windows led to high accuracy in supervised machine learning-based fall detection. Also, the experiments conducted in this study suggested that the best accuracy can be achieved by keeping the window size as small as 2 seconds. With the kNN classifier and dataset from wearable sensors, the experiments achieved accuracy rates of 94%.

• 한국항해항만학회지
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• 제37권5호
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• pp.527-533
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• 2013

본 논문은 구조물의 동적특성인 모드형상과 고유진동수를 이용한 손상탐지와 유효 물성치 추정을 통하여 콘크리트 축소모형과 실제 콘크리트 부유식 구조물 함체의 건전성을 평가하였다. 손상탐지의 경우 콘크리트 축소모형에 대한 동적실험을 수행하여 모드형상을 추출한 후 손상탐지기법에 적용하여 실용성을 증명하였다. 또한 실제 콘크리트 부유식 구조물 함체의 모드형상 및 고유진동수를 실험을 통하여 구한 후 구조계추정기법을 이용하여 콘크리트의 유효 물성치를 추정하였다. 손상탐지기법을 이용하여 축소모형의 손상부재를 정확히 찾아내었으며, 구조계추정기법을 이용하여 실제 콘크리트 부유식 함체의 현재 유효 물성치를 추정하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.411-414
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• 2009

화재로 인해 많은 물적 인적 피해가 발생한다. 본 연구에서는 영상처리기법과 고속의 DSP 프로세서 기술 그리고 IT 기술을 활용하여 발화 초기에 화재를 인식하고 경보를 발생하여 화재에 조기 대응하는 화재 검출 알고리즘을 실장한 지능형 화재검출 시스템을 제안한다. 제안하는 지능형 시스템의 화재 검출 알고리즘은 화염검출과 연기검출 알고리즘으로 구성되어진다. 화염 또는 연기만 발생하는 경우에는, 각각의 경보를 관리용 컴퓨터에 전송한다. 화염과 연기가 동시에 발생하면 화재경보를 발생하도록 하였다. 다양한 환경에서의 실제 실험을 통해 오작동 없이 잘 동작하는 것을 확인할 수 있었다.