• 전기학회논문지
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• 제58권11호
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• pp.2192-2199
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• 2009

This paper proposes a novel tracking algorithm for efficiency improvement of photovoltaic(PV) system using sensor method. PV system of sensor method is exactly impossible to track a sun position when insolation is low or rapidly changed by the clouds and fogs. Also, in this case, tracking device is occurred energy consumption by unnecessary operating. This statement of reason, real power of PV system is not increased than fixed PV system in specified location. Therefore, this paper proposes a novel tracking algorithm considered insolation for efficiency improvement of PV system using sensor method. And this paper analyzes the generation volume and proves the validity of proposed algorithm as compared with the conventional PV tracking system using sensor method.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2005년도 추계 학술대회 발표논문집
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• pp.59-62
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• 2005

Voice activity detection (VAD) is important in many areas of speech processing technology. Speech/nonspeech discrimination in noisy environments is a difficult task because the feature parameters used for the VAD are sensitive to the surrounding environments. Thus the VAD performance is severely degraded at low signal-to-noise ratios (SNRs). In this paper, a new VAD algorithm is proposed based on the degree of voicing and Quantile SNR (QSNR). These two feature parameters are more robust than other features such as energy and spectral entropy in noisy environments. The effectiveness of proposed algorithm is evaluated under the diverse noisy environments in the Aurora2 DB. According to out experiment, the proposed VAD outperforms the ETSI Advanced Frontend VAD.

• 전자공학회논문지CI
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• 제49권1호
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• pp.39-45
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• 2012

무선 센서 네트워크(Wireless Sensor Network)는 사람이 직접 접근하기 불가능한 군사지역이나 자연 환경의 감시, 혹은 안전감시를 위한 목적으로 각 상황의 특성에 맞는 다양한 정보를 수집하는데 많이 이용되고 있다. 지금까지 제시된 프로토콜 중 LEACH 프로토콜은 에너지의 균등한 소모를 특징으로 많이 쓰이고 있다. 하지만 거리에 따른 에너지 소모의 증가로 원거리 노드의 에너지 소모 문제가 대두되었는데, 지금까지 여러 가지 해결방안들이 제시되었는데 대부분 중앙 시스템 방식이다. 본 논문에서는 LEACH 프로토콜을 사용한 무선 센서 네트워크를 모델로 하여, 네트워크 규모가 커질수록 1-hop 전송방식에서 발생할 수 있는 원거리 센서 노드의 에너지 불균형 문제를 해결하였다. 또한, 중앙 시스템 방식이 아닌 센서 노드 자체에서 클러스터링 문제를 해결할 수 있는 분산 시스템 방식의 라이프타임 향상 알고리즘을 제안하였다.

• Smart Structures and Systems
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• 제4권5호
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• pp.697-710
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• 2008

Long steel stay cables, which are mainly used in cable-stayed bridges, are easy to vibrate because of their low inherent damping characteristics. A lot of methods for vibration reduction of stay cables have been developed, and several techniques of them have been implemented to real structures, though each has its limitations. Recently, it was reported that smart (i.e. semi-active) dampers can potentially achieve performance levels nearly the same as comparable active devices with few of the detractions. Some numerical and experimental studies on the application of smart damping systems employing an MR fluid damper, which is one of the most promising smart dampers, to a stay cable were carried out; however, most of the previous studies considered only one specific control algorithm in which they are interested. In this study, the performance verification of MR fluid damper-based smart damping systems for mitigating vibration of stay cables by considering the four commonly used semi-active control algorithms, such as the control algorithm based on Lyapunov stability theory, the maximum energy dissipation algorithm, the modulated homogeneous friction algorithm and the clipped-optimal control algorithm, is systematically carried out to find the most appropriate control strategy for the cable-damper system.

• 대한건축학회연합논문집
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• 제20권6호
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• pp.113-119
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• 2018

Occupancy-based heating control is effective in reducing heating energy by preventing unnecessary heating during unoccupied period. Various technologies on detecting human occupancy have been developed using complicated machine learning algorithm and stochastic methodologies. This study aims at deriving low-cost and simple algorithm of occupancy inference that can be implemented to residential buildings. The core concept of the algorithm is to combine the occupancy probabilities based on indoor CO2 concentration and PIR(passive infrared) signals. The probability was estimated by applying different levels of decrement ratio depending on CO2 concentration change rate and aggregated PIR signals. The developed algorithm was validated by comparing the inference results with the occupancy schedule in a real residential building. The results showed that the inference algorithm can achieve the accuracy of 75~99%, which would be successfully implemented to the control of residential heating systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4808-4824
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• 2016

Signal individual reconnaissance and identification is an extremely important research topic in non-cooperative domains such as electronic countermeasures and intelligence reconnaissance. Facing the characteristics of the complexity and changeability of current communication environment, how to realize radiation source signal individual identification under the low SNR conditions is an emphasis of research. A novel emitter individual identification method combined bi-spectrum analysis with wavelet feature is presented in this paper. It makes a feature fusion of bi-spectrum slice characteristics and energy variance characteristics of the secondary wavelet transform coefficient to identify MFSK signals under the low SNR (signal-to-noise ratios) environment. Theoretical analyses and computer simulation results show that the proposed algorithm has good recognition performance with the ability to suppress noise and interference, and reaches the recognition rate of more than 90% when the SNR is -6dB.

• 한국컴퓨터정보학회논문지
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• 제14권5호
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• pp.141-148
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• 2009

무선 센서 네트워크는 다양한 센서 기술의 발전으로 환경 분석이나 산업현자에서 다양하게 적용되고 있다. 또한 무선 센서 네트워크는 설치된 지역에서의 센서를 자동적으로 모니터링 한다. 특히 매우 작은 센서들은 최근환경 분석을 위해 보다 많은 전은을 요구하며 개발되고 있다. 이러한 이유로 보다 상세한 측정 방법을 위해 다양한 재료와 어플리케이션에 의해 개발되었다. 또한 센서노드들은 저가의 저전력을 요구하는 필드를 위해 적은 전원으로 동작한다. 전원 효율은 무선 센서 네트워크의 생존시간에 매우 중요한 요소이다. 때문에 센서 노드들은 복구되기 어렵고 광범위한지역에 설치된다. 본 논문에서는 저전력과 효율을 고려한 센서 노드에 적용된 무선 센서 네트워크 알고리즘을 제안하였다.

• 센서학회지
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• 제27권2호
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• pp.93-98
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• 2018

In this paper, an energy-efficient 11.49-bit successive approximation register (SAR) capacitance-to-digital converter (CDC) for capacitive sensors with a figure of merit (FoM) of 31.6 pJ/conversion-step is presented. The CDC employs a SAR algorithm to obtain low power consumption and a simplified structure. The proposed circuit uses a capacitive sensing amplifier (CSA) and a dynamic latch comparator to achieve parasitic capacitance-insensitive operation. The CSA adopts a correlated double sampling (CDS) technique to reduce flicker (1/f) noise to achieve low-noise characteristics. The SAR algorithm is implemented in dual operating mode, using an 8-bit coarse programmable capacitor array in the capacitance-domain and an 8-bit R-2R digital-to-analog converter (DAC) in the charge-domain. The proposed CDC achieves a wide input capacitance range of 29.4 pF and a high resolution of 0.449 fF. The CDC is fabricated in a $0.18-{\mu}m$ 1P6M complementary metal-oxide-semiconductor (CMOS) process with an active area of 0.55 mm2. The total power consumption of the CDC is $86.4{\mu}W$ with a 1.8-V supply. The SAR CDC achieves a measured 11.49-bit resolution within a conversion time of 1.025 ms and an energy-efficiency FoM of 31.6 pJ/step.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.433-440
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• 2014

In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.550-558
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• 2014

Direct Torque controlled induction motor (DTC-IM) drives use stator resistance of the motor for stator flux estimation. So, stator resistance estimation properly is very important for a stable and effective operation of the induction motor. Stator resistance variations because of changing in temperature make DTC operation difficult mainly at low speed. A method based on artificial neural network (ANN) to estimate the stator resistance online of IM for DTC drive is modeled and verified in this paper. To train the neural network a back propagation algorithm is used. Weight adjustment of neural network is done by back propagating the error signal between measured and estimated stator current. An extensive simulation has been carried out in MATLAB/SIMULINK to prove the efficacy of the proposed stator resistance estimator. The simulation & experimental result reveals that proposed method is able to obtain precise torque and flux control at low speed.