HHT 기반 신경망을 이용한 풍력터빈 고장진단 방법에 대한 연구

안명수(Ming-Shou An),강대성(Dae-Seong Kang) 한국정보기술학회 2013 한국정보기술학회논문지 Vol.11 No.11

For the wind power, the global research has been activating, and the large scale has been implementing with the development of technology. But due to the development of large-scale structure of wind turbines, the possibility of the failure was increased. So the most effective way is real time condition monitoring and advanced fault diagnosis to ensure the stable operation and reduce the maintenance costs. In this paper, the Hilbert-Huang Transform(HHT) which is the signal analysis for fault diagnosis extracts the feature information from the classified patterns of normal signal and fault signal. The extracted feature information would be used for input layer of neural network algorithm. The failure or not can be identified through the neural network training. In addition, simple faults as well as complex faults that occur over a long time can be diagnosed by proposed method of fault analysis early.

적응적 영상 차분을 이용한 움직임 영역 검출 방법

안명수(Ming-Shou An),강대성(Dae-Seong Kang) 한국정보기술학회 2010 한국정보기술학회논문지 Vol.8 No.1

In this paper, the proposed method is based on detecting moving region by applying a combined three frames difference and background subtraction. We can adaptively extract the object which is not sensitive to change of illumination and has a fast motion or slow motion by applying these two methods. In preprocess we used gaussian filter in order to obtain clear image. Moving object region was detected in using the proposed method from the image which is removed noise. About background modeling method we used MOG(Mixture Of Gaussian) method, to modeling and update the background so that applies to real-time change of background. The processing time for each frame in the experimental results of proposed method is 33.012ms, and precision is 93%. The experimental results show that the proposed method is more robust, accurate and powerful than existed methods.

색상과 Texture 정보를 이용한 Particle Filter 기반 객체 추적 방법

안명수(Ming-Shou An),하성욱(Seong-Wook Ha),강대성(Dae-Seong Kang) 한국정보기술학회 2010 한국정보기술학회논문지 Vol.8 No.11

In particle filter, the sampling initialization has many noises. Due to this problem, there are also many noises in weight update step. Therefore, it is important that extracting the feature for sampling. So far, the feature extraction method with HSV color information is already widely used. However, it is difficult to extract the feature accurately only with the color information. In our research, we proposed the method that is fusing the HSV color information and texture information to feature detection and object tracking. For this feature, we use the Particle filter to tracking effectively in brightness changes or complex background. In the experimental results, we confirmed that the proposed method can increase the precision of the Particle filter, and has the good robustness to object tracking.

다 특징 정보 융합에 의한 스테레오 기반 다중 객체 추적 기법

안명수(Ming-Shou An),강대성(Dae-Seong Kang) 한국정보기술학회 2011 한국정보기술학회논문지 Vol.9 No.7

In this paper, we propose a method that can be effectively tracking the multi-object based on stereo vision by the information fusion of color, depth and texture. A CAMShift algorithm based on the color is an representative algorithm for the object tracking. But, it is not an effective method for multi-object tracking only by backprojection image information. So, we used three features to describe the independent features of object. The first feature is the backprojection image information; the second is the depth map by stereo camera; the third is HLBP(histogram of local binary patterns). We use the method of the three features fusion through CAMShift algorithm for tracking. It is robust to the illumination changes and occlusion problems. The comparative results from experiments show the proposed method can extract the independent features of object, and track effectively.

유동상 반응기를 이용한 반도체 폐수의 불소 처리

안명기(Myeong Ki An),김금용(Keum Yong Kim),류홍덕(Hong Duck Ryu),이상일(Sang Ill Lee) 大韓環境工學會 2010 대한환경공학회지 Vol.32 No.5

본 연구에서는 반도체 폐수에 함유된 불소 처리 시 유동상 반응기 (FBR)을 이용하여 불소 제거 효율을 극대화 시키는 조건에서 발생하는 슬러지의 함수율을 최소화 시키고 CaF₂의 순도를 높이고자 하였다. 이를 위해 최적 pH 및 CA₂+ 주입 몰비 ([CA₂+]/[F-])가 도출되었다. 연구 결과 pH 및 CA₂+ 주입 몰비가 증가함에 따라 불소 제거효율은 증가하였으며, 최적 조건에서 79.8%의 불소제거효율이 관찰되었다. 불소 제거 효율이 최적인 조건에서 인 제거 효율은 약 9.3% 로서 불소 제거시 CA₂+과 PO₄3--P의 부 반응이 거의 발생하지 않아 높은 순도의 CaF₂이 침전 슬러지로 발생하는 것으로 나타났다. 또한 이때 슬러지 함수율은 약 19.3%로 매우 낮은 것으로 나타나 불소 제거, 슬러지 순도 및 함수율 측면에서 FBR은 매우 효과적인 불소 제거 공정인 것으로 나타났다. This work was initiated both to maximize purity of calcium fluoride sludge and to minimize water content in the settled sludge. The sludge was produced in the process of fluoride removal of semiconductor wastewater by the addition of CA₂+ ion. Fludized bed reactor(FBR) using calcium fluoride as a seed was adapted. Optimum pH and molar ratio of CA₂+/F- were determined in lab-scale study. The experimental results showed that fluoride removal was increased as pH and molar ratio of CA₂+/F- increased, with the best removal of 79.8% in an optimum condition. In the optimum point of fluoride removal, very low PO₄ 3--P removal of 9.3% was observed. It indicates forming CaF₂ crystal of high purity, when side reaction of calcium with phosphate was minimized. In addition, water content of settled sludge was 19.3%, which is relatively low compared to other fluoride removal processes. Consequently, the FBR process proposed in this study was very effective in fluoride removal, producing good sludge of high purity and less water content.

어떻게 고객을 당신의 열성적인 팬으로 만들 것인가? 경험 품질이 브랜드에 대한 고객 행동에 미치는 영향

안명아 ( An Myoung-a ),김승화 ( Kim Seung-hwa ) 한국유통경영학회(구 한국유통정보학회) 2018 유통경영학회지 Vol.21 No.4

유통 시장의 경쟁이 치열해지면서 브랜드 경쟁력을 유지하기 위한 고객 관리의 중요성이 대두되고 있다. 고객은 기업의 자산으로, 기존 고객을 유지하는 것이 안정적인 재무적 구조를 구축하고 경쟁력을 갖추는 데 필요하게 되었다. 서비스 지배 논리에 의하면 시장 환경은 제품 중심에서 서비스 중심으로 변화하고 있으며, 이는 단편적으로 제품을 구매하는 전통적인 마케팅에서 벗어나 소비를 하나의 경험으로 제시하는 경험 경제로 변화하고 있음을 의미한다. 본 연구에서는 시장의 변화 흐름에 따라 기업에서 고객에게 제공하는 경험의 품질이 중요함을 이해하고, 이를 바탕으로 경험 기반 유통채널에서 기존 고객을 유지하는 방법을 살펴보고자 하였다. 따라서 경험 품질에 영향을 줄 수 있는 품질 요인이 무엇인지 알아보고, 어떤 선행 변수를 통해 브랜드 팬쉽이 형성되는지 그 과정을 알아보았다. 연구 결과, 결과 품질과 장소 품질이 경험 품질에 영향을 주는 것을 알 수 있었으며, 경험 품질을 통해 가치를 지각하여 브랜드에 대한 신뢰가 나타난다는 것을 알 수 있었다. 또한 신뢰를 바탕으로 브랜드 충성도가 형성되고, 이로 인해 보다 열정적으로 브랜드를 소비하는 브랜드 팬쉽이 형성됨을 확인할 수 있었다. 본 연구는 브랜드에 대한 소비를 경험의 형태로 제시하는 것이 얼마나 중요한지 이해하고, 기업의 고객경험관리에 대한 방향성을 제시한다는 점에서 의의가 있다. 브랜드에 대한 팬(fan)으로 고객을 탈바꿈하는 과정을 살펴본 본 연구의 결과가 실무에 적용되길 기대한다. Competition on the market is fierce, yet there is limited empirical research on customer experience management strategy. A key driver of the company's competitiveness is how many valuable customers they have. According to the service-dominant logic, managing the whole process of delivering services to the customer has become more important. Also, the concept of experience economy points out that experiential marketing is a better way to understand the customer. In this paper, we aim to figure out the way to retain customers and understand the influence of experiential quality on customers’ behavior towards the brand in the context of the experience-based store. The results showed that there was a significant positive relationship between experiential quality, perceived value, trust, brand loyalty and brand fanship. While trust towards brand had no significant direct effect on brand fanship. We suggest ways in which retailers and marketers can engage their customers as a fan and provide a managerial perspective of the customer experience management within the experience-based distribution channel.

분할된 영상에서의 칼라 코렐로그램을 이용한 내용기반 영상검색

안명석,조석제,An, Myung-Seok,Cho, Seok-Je 한국정보과학회 2001 정보과학회논문지 : 시스템 및 이론 Vol.28 No.10

최근 효과적인 내용기반 영상검색을 위한 특징 추출 방법이 많이 연구되고 있다. 특히, 칼라정보를 이용하여 특징을 얻는 방법은 여러 가지 장점 때문에 연구가 활발히 진행되고 있다. 본 논문에서는 칼라정보를 이용해서 얻을 수 있는 칼라코렐로 그램을 이용한 영상검색 성능을 향상시키기 위해, 칼라 코렐로그램 기반의 새로운 특정 추출 방법을 제안한다. 제안한 방법은 영상을 복잡한 부분과 그렇지 않은 부분으로 분할학고, 각각의 칼라 코렐로그램을 얻는 방법 . 제안한 방법은 기존의 칼라 코렐로그램을 이용한 영상검색보다 우수한 성능을 나타냄을 실험을 통하여 확인하였다. 확인하였다. Recently, there has been studied on feature extraction method for efficient content-based image retrieval. Especially, many researchers have been studying on extracting from color information, because of its advantages. This paper proposes a feature and its extraction method based on color information in an image. The proposed method is computed from the image segmented into two parts: the complex part and the plan part. Our experiments show that the performance of the proposed method is better as compared with the original color correlogram method.

몰입형 인터페이스를 위한 손동작 인식 알고리즘에 관한 연구

안명수(Ming-Shou An),강대성(Dae-Seong Kang) 한국정보기술학회 2012 한국정보기술학회논문지 Vol.10 No.3

Immersive hand gesture interface is mostly used for augmented reality and kinect game environment which are introduced recently. Implementing hand gesture interface in this domain requires not only the region of hand must be recognized quickly in real time, but also a high degree of accuracy. In this paper, the hand detection and tracking methods are proposed for immersive hand gesture interface. For detecting the region of hand correctly, the detection method uses the data trained by Adaboost algorithm with Haar-like feature. We improved the pairwise geometrical histogram(PGH) algorithm for recognizing the hand. The advantage of this algorithm is that processing speed is high due to efficient calculation and the recognition accuracy is high. Experimental results show that the recognition rate for test image data is high.

자동차 번호판의 문자/숫자 영역을 인식하기 위한 해마 학습 알고리즘 구현

안명수(Ming-Shou An),임혜연(Hye-Youn Lim),김장희(Jang-Hui Kim),강대성(Dae-Seong Kang) 한국정보기술학회 2008 Proceedings of KIIT Conference Vol.2008 No.-

개선된 MOG 모델과 예측 방법에 의한 실시간 움직임 객체 검출 및 추적에 대한 연구

안명수(Ming-Shou An),강대성(Dae-Seong Kang) 한국정보기술학회 2009 한국정보기술학회논문지 Vol.7 No.4

The analysis of the moving object is based on the detection system and the problem which is to have a challenge and widely applied in the tracking and safety. how to detect moving objects has recently studied a lot. In this paper, MOG (Mixture Of Gaussian), a way of Modeling the background, is described using statistical characteristics of the information obtained over time surveillance zone. And the Modeling background and the object are detected by proposing how to improve the MOG (Mixture Of Gaussian) of the disadvantages. The noise process is practiced by applying the operation morphology in extracted object image. The experiment to track the moving object is progressed by calculating the special features of detected objects accurately and appling the block matching and the Kalman Filter prediction methods for proving.