• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권12호
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• pp.3242-3265
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• 2023

Ensuring reliability of a machinery system involve the prediction of remaining useful life (RUL). In most RUL prediction approaches, noise is always considered for removal. Nevertheless, noise could be properly utilized to enhance the prediction capabilities. In this paper, we proposed a novel RUL prediction approach based on noise injection and a Kalman filter ensemble of modified bagging predictors. Firstly, we proposed a new method to insert Gaussian noises into both observation and feature spaces of an original training dataset, named GN-DAFC. Secondly, we developed a modified bagging method based on Kalman filter averaging, named KBAG. Then, we developed a new ensemble method which is a Kalman filter ensemble of KBAGs, named DKBAG. Finally, we proposed a novel RUL prediction approach GN-DAFC-DKBAG in which the optimal noise-injected training dataset was determined by a GN-DAFC-based searching strategy and then inputted to a DKBAG model. Our approach is validated on the NASA C-MAPSS dataset of aero-engines. Experimental results show that our approach achieves significantly better performance than a traditional Kalman filter ensemble of single learning models (KESLM) and the original DKBAG approaches. We also found that the optimal noise-injected data could improve the prediction performance of both KESLM and DKBAG. We further compare our approach with two advanced ensemble approaches, and the results indicate that the former also has better performance than the latters. Thus, our approach of combining optimal noise injection and DKBAG provides an effective solution for RUL estimation of machinery systems.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1406-1416
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• 2017

In complex and large-scale industries, properly designed fault detection and identification (FDI) systems considerably improve safety, reliability and availability of target processes. In thermal power plants (TPPs), generating units operate under very dangerous conditions; system failures can cause severe loss of life and property. In this paper, we propose a bagged auto-associative kernel regression (AAKR)-based FDI approach for steam boilers in TPPs. AAKR estimates new query vectors by online local modeling, and is suitable for TPPs operating under various load levels. By combining the bagging method, more stable and reliable estimations can be achieved, since the effects of random fluctuations decrease because of ensemble averaging. To validate performance, the proposed method and comparison methods (i.e., a clustering-based method and principal component analysis) are applied to failure data due to water wall tube leakage gathered from a 250 MW coal-fired TPP. Experimental results show that the proposed method fulfills reasonable false alarm rates and, at the same time, achieves better fault detection performance than the comparison methods. After performing fault detection, contribution analysis is carried out to identify fault variables; this helps operators to confirm the types of faults and efficiently take preventive actions.

• 전자공학회논문지SC
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• 제44권4호통권316호
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• pp.74-78
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• 2007

의료용으로 사용되는 새로운 개념의 환자감시용 센서 매트와 그 신호처리방식을 제시하였다. 제시된 센서 매트와 플라스틱 광섬유를 교차시켜 배치한 구조를 갖는 내부 센서층을 갖는 구조로 제작하였다. 플라스틱 광섬유의 대구경 특성을 이용하여 불필요한 외부환경 요인에 의하여 발생되는 잡음요소들을 평균화하여 신호성분만을 통과시키는 대역통과필터를 구현하였다. 센서 출력단에 신호처리부를 부가하여 추가로 불필요한 성분들을 제거하여 잡음제거 능력을 향상시켰고 지능형 알고리즘을 사용하여 신뢰성 있는 환자호흡감지방식을 구현하였다. 신호와 주변잡음 모두에게 고감도를 보이는 기존의 기계적인 방식을 사용하는 감지방식과는 달리 본 연구에서 제시된 방식은 신뢰성 있는 호흡 감지가 가능함을 보여주었다.

• Journal of Electrical Engineering and Technology
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• 제6권5호
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• pp.697-705
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• 2011

In this paper, a closed-loop system constructed with a linear plant and nonlinearity in the feedback connection is considered to argue against its planar orbital stability. Through a state space approach, a main result that presents a sufficient stability criterion of the limit cycle predicted by solving the harmonic balance equation is given. Preliminarily, the harmonic balance of the nonlinear feedback loop is assumed to have a solution that determines the characteristics of the limit cycle. Using a state-space approach, the nonlinear loop equation is reformulated into a linear perturbed model through the introduction of a residual operator. By considering a series of transformations, such as a modified eigenstructure decomposition, periodic averaging, change of variables, and coordinate transformation, the stability of the limit cycle can be simply tested via a scalar function and matrix. Finally, the stability criterion is addressed by constructing a composite Lyapunov function of the transformed system.

• 한국해안해양공학회지
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• 제4권4호
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• pp.201-207
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• 1992

Yeo(1987)에 의하여 유도된 평균된 비선형괴의 표현식을 이론 및 실험적 분석을 통하여 난류구조의 특성을 밝혔다. 일반 평균정의식으로부터 가우스형 필터함수를 사용하여 얻어진 이 식에 의하면 종래와 같이 비선형항을 4개의 항으로 분리하여 각각을 해석할 필요가 없으며 기존 난류모형이 갖는 Closure문제로 인한 한계성도 극복할 수 있는 가능공을 보여주고 있다. 새로이 유도된 표현식으로부터 종래 개염적으로만 인식되어 왔던 vortex stretching현상을 이논적으로 도출할 수 있었으며 실제 난류자료의 분석결업 이들의 영향이 지배적임을 입증하였다. 따라서 vortex stretching의 영향을 무시한 난류모형은 그 타당성을 상설하게 된다. 또한 LES모형에 적용시킨 결과 일반적 형태의 에너지 표현식을 얻을 수 있었으며 기존의 Smagorinsky모형, 회전모형및 SGS에너지 모형은 완전히 별개의 것이 아니라 난류에너지 중 변형 및 회전에 의한 영향의 고려 가부에 따라 구분되어짐을 보였다.

• 한국해안·해양공학회논문집
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• 제30권6호
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• pp.319-325
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• 2018

본 연구는 도수(hydraulic jump)의 롤러(roller)의 거동을 분석하기 위해 영상기법을 이용한 실험연구를 수행하였다. 조석단파(tidal bore)의 거동 특성의 이해에 적용하기 위해 하류심 상승에 따른 도수 전면부의 파형과 변동성을 검토하였다. 도수의 변동성을 고려한 앙상블평균 기법을 적용하여 얻은 파형을 제시하여 시간평균 결과와 비교하였다. 앙상블평균의 기준이 된 도수시작점의 시간적 변화로부터 도수 전면부의 변동성을 통계적으로 분석하였다. 하류심 상승에 따라 전면 파형은 완만해지는 것으로 나타났으며, 시작점 변동성은 감소하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.551-554
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• 2002

The paper discusses new approach for machining operation simulation using enhanced Z map algorithm. To extract the required geometric information from NC code, suggested algorithm uses supersampling method to enhance the efficiency of a simulation process. By executing redundant Boolean operations in a grid cell and averaging down calculated data, presented algorithm can accurately represent material removal volume though tool swept volume is negligibly small. Supersampling method is the most common form of antialiasing and usually used with polygon mesh rendering in computer graphics. The key advantage of enhanced Z map model is that the data structure is same with conventional Z map model, though it can acquire higher accuracy and reliability with same or lower computation time. By simulating machining operation efficiently, this system can be used to improve the reliability and efficiency of NC machining process as well as the quality of the final product.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.571-574
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• 2005

In this paper, we propose an efficient image segmentation technique for large-sized monochrome images using a hybrid approach which combines threshold and region-based techniques. First, an image is partitioned into fixed-size blocks and for each block the representative intensity is determined by averaging pixel intensities within the block. Next, the neighborhood blocks that have similar characteristics with respect to a specific threshold are merged in order to form candidate regions. Finally, those candidate regions are refined to get final target object regions by merging regions considering the spatial locality and certain criteria. We have performed experiments on images selected from various domains and showed that our technique was able to extract target object regions appropriately from most images.

• Communications for Statistical Applications and Methods
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• 제7권2호
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• pp.533-540
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• 2000

The problem of information related to I poission experiments, each having a distinct failure rate $\theta$i I=1,2,…,I, is considered. Instead of using a standard exchangeable prior for $\theta$=($\theta$1,$\theta$2,…,$\theta$I), we consider a partition of the experiments and take the $\theta$i's belonging to the same partition subgroup to be exchangeable and the $\theta$i's belonging to distinct subgroups to be independent. And we perform Gibbs sampling approach for Bayesian inference on $\theta$ conditional on a partition. Numerical study using real data is provided.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.506-509
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• 2005

An adaptive ${\alpha}-{\beta}$ tracker is proposed for tracking maneuvering targets with a track-while-scan radar system. The tracker gain is updated on-line corresponding to the adjusted process noise variance which is obtained via time averaging of the process over a sliding window. The adjusted process noise variance is used to compute the maneuverability index for the tracker gain based on the steady-state Kalman filter equation for each epoch. It is shown via simulation that the proposed approach provides robust and accurate position estimates during the target maneuver while the performance of the conventional ${\alpha}-{\beta}$ tracker is shown much degraded.