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Prediction and Measurement for Harmonics on the Test Track of Seoul-Pusan High-speed Railway
오광해(K.H. Oh),이장무(C.M. Lee),한문섭(M.S. Han),이기원(K.W. Lee),권삼영(K.S. Kwon),창상훈(S.H. Chang),김길상(K.S. Kim) 한국철도학회 2000 한국철도학회 학술발표대회논문집 Vol.- No.-
This paper proposes a new model for harmonic analysis in 2×25㎸ traction power supply system including inverted feeder, contact line, rails and auto-transformer. The system model is based on four-port representation which is an extension of two-port network theory. In order to verify the proposed approach, we have analysed and tested real traction power feeding system focused on the amplification of harmonic current. The calculation results from the proposed approach and the measurement data from the test are widely described in the paper.
오광일,김성은,배영환,박경환,권영수,Oh, K.I.,Kim, S.E.,Bae, Y.H.,Park, K.H.,Kwon, Y.S. 한국전자통신연구원 2020 전자통신동향분석 Vol.35 No.3
Neuromorphic hardware refers to brain-inspired computers or components that model an artificial neural network comprising densely connected parallel neurons and synapses. The major element in the widespread deployment of neural networks in embedded devices are efficient architecture for neuromorphic hardware with regard to performance, power consumption, and chip area. Spiking neural networks (SiNNs) are brain-inspired in which the communication among neurons is modeled in the form of spikes. Owing to brainlike operating modes, SNNs can be power efficient. However, issues still exist with research and actual application of SNNs. In this issue, we focus on the technology development cases and market trends of two typical tracks, which are listed above, from the point of view of artificial intelligence neuromorphic circuits and subsequently describe their future development prospects.
오광해(K.H. Oh),이장무(C.M. Lee),창상훈(S.H. Chang),한문섭(M.S. Han),김길상(K.S. Kim) 한국철도학회 1999 한국철도학회 학술발표대회논문집 Vol.- No.-
Modern AC electric car has PWM(Pulse Width Modulation)-controlled converters, which give rise to higher harmonics. The current harmonics injected from AC electric car is propagated through power feeding circuit. As the feeding circuit is a distributed constant circuit composed of RLC, the capacitance of the feeding circuit and the inductance on the side of power system cause a parallel resonance and a magnification of current harmonics at a specific frequency. The magnified current harmonics usually brings about various problems. That is, the current harmonics makes interference in the adjacent lines of communications and the railway signalling system. Furthermore, in case it flows on the side of power system, not only overheating and vibration at the power capacitors but also wrong operation at the protective devices can occur. Therefore, the exact assessment of the harmonic current flow must be undertaken at design and planning stage for the electric traction systems. From these point of view, this study presents an approach to model and to analyse traction power feeding system focused on the amplification of harmonic current The proposed algorithm is applied to a standard AT(Auto-transformer)-fed test system in which electric car with PWM-controlled converters is running.
오광일,김성은,배영환,박성모,이재진,강성원,Oh, K.I.,Kim, S.E.,Bae, Y.H.,Park, S.M.,Lee, J.J.,Kang, S.W. 한국전자통신연구원 2018 전자통신동향분석 Vol.33 No.6
In the age of IoT, in which everything is connected to a network, there have been increases in the amount of data traffic, latency, and the risk of personal privacy breaches that conventional cloud computing technology cannot cope with. The idea of edge computing has emerged as a solution to these issues, and furthermore, the concept of ultra-low power edge intelligent semiconductors in which the IoT device itself performs intelligent decisions and processes data has been established. The key elements of this function are an intelligent semiconductor based on artificial intelligence, connectivity for the efficient connection of neurons and synapses, and a large-scale spiking neural network simulation framework for the performance prediction of a neural network. This paper covers the current trends in ultra-low power edge intelligent semiconductors including issues regarding their technology and application.