• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.104.1-104
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• 2001

This paper presents a technique to development load control and management system in order to limits a maximum load demand and saves electric energy consumption. The computer programming proper load forecasting algorithm associated with programmable logic control and digital power meter through inform of multidrop network RS 485 over the twisted pair, over all are contained in this system. The digital power meter can measure a load data such as V, I, pf, P, Q, kWh, kVarh, etc., to be collected in statistics data convey to data base system on microcomputer and then analyzed a moving linear regression of load to forecast load demand Eventually, the result by forecasting are used for compost of load management and shedding for demand monitoring, Cycling on/off load control, Timer control, and Direct control. In this case can effectively reduce the electric energy consumption cost for 10% ...

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.884-888
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• 1991

이 글에서는 1990년 가을 개국하여 운용되고 있는 서울우편물집중국의 우편 물 처리의 자동화 시스템의 적용을 분석, 그의 특징 등을 서술코자 한다. 본 서울우편물집중국의 자동화는 프로그래머블콘트롤러(PLC)를 적용하여 모 든 자동제어기를 통합 NETWORK화하여 1) 계층적제어 SYSTEM을 확립하 였으며 관리용 SYSTEM별의 자율적인 단위 조작과 기능적 독립을 유지하 며, 3) 분산제어 시스템화하여 우편처리에 있어 자동 일관처리 공정을 이루 는데 성공적이였으며, 이는 전적으로 PLC를 적용 계층적 분산제어에 의하여 성취되었다고 본다. 프로그래머블콘트롤러(PLC)는 확장성이 크고 강력한 우 편물 처리의 자동화 장치로서 계속적으로 우편물처리의 자동화 및 기계화 산업에 적용될 것임을 확신하는 바이다.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.309-312
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• 2001

A primitive gas classification system which can classify limited species of gas was designed and simulated. The 'electronic nose' consists of an array of 4 metal oxide gas sensors with different selectivity patterns, signal collecting unit and a signal pattern recognition and decision Part in PLD(programmable logic device) chip. Sensor array consists of four commercial, tin oxide based, semiconductor type gas sensors. BP(back propagation) neutral networks with MLP(Multilayer Perceptron) structure was designed and implemented on CPLD of fifty thousand gate level chip by VHDL language for processing the input signals from 4 gas sensors and qualification of gases in air. The network contained four input units, one hidden layer with 4 neurons and output with 4 regular neurons. The 'electronic nose' system was successfully classified 4 kinds of industrial gases in computer simulation.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1998.06a
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• pp.55-58
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• 1998

Recently, neural networks with self-adaptability like human brain have attracted much attention. It is desirable for the neuron-function to be implemented by exclusive hardware system on account of huge quantity in calculation. We have proposed a novel neuro-device composed of a MFSFET(ferroelectric gate FET) and oscillation circuit with CUJT(complimentary unijuction transistor) and PUT(programmable unijuction transistor). However, it is difficult to preserve ferroelectricity on Si due to existence of interfacial traps and/or interdiffusion of the constitutent elements, although there are a few reports on good MFS devices. In this paper, we have simulated CUJT and PUT devices instead of fabricating them and composed oscillation circuit. Finally, we have resented, as an approach to the MFSFET neuron circuit, adaptive learning function and characterized the elementary operation properties of the pulse oscillation circuit.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.72.1-72.1
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• 2011

한국우주전파관측망(Korean VLBI Network, KVN)을 이루는 21m 전파망원경 수신기들의 전파세기를 모니터링하기 위하여, 전파세기 측정기를 설계, 제작 중에 있다. 이 장치는 수신된 우주전파신호를 주파수로 변환해서, 전파관측 중의 모니터링이나 수신신호특성을 파악하는데 필요한 장치이다. 지난 연구(강용우 외, 2010)에서 이러한 회로 특성 파악과 개선을 위하여, 다양한 실험을 할 수 있게 전파세기 시험용 측정기를 제작하고 시험한 바 있다. 본 연구에서는 시험용 측정기의 시험 결과를 바탕으로, EPLD(Erasable Programmable Logic Devices)를 이용한 전파세기측정기를 새로 개발 중에 있다. 이에 지금까지의 개발 내용을 소개하고자 한다.

• Journal of Power Electronics
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• v.11 no.5
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• pp.751-758
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• 2011

This paper presents an effective robust predictive control scheme for the active power filter (APF) using a smith-predictor based current regulator, which show superior features when compared to proportional-integral (PI) controllers in terms of an enhanced closed-loop bandwidth and an improved current tracking accuracy. A moving average filter (MAF) is implemented using a field programmable gate array (FPGA) for signal pre-processing to eliminate the switching ripple contamination. An adaptive linear neural network (ADALINE) is used for individual harmonic estimation to achieve selective compensation purpose. The effectiveness and validity of the devised control algorithm are confirmed by extensive simulation and experimental results.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1599-1600
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• 2007

The DTL water skid cooling system and Resonant Control Cooling Systems (RCCS) will employ a control system that can be operated by a local, programmable logic controller (PLC), interfaced through a touch screen interface, mobile alarm SMS server system, or it can be operated through the PEFP global control system network. The RCCS is implemented using Experimental Physics and Control System (EPICS) based hardware and software and is integrated with other networked PEFP EPICS systems. This presentation discusses the features of the local control system.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.479-481
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• 2019

본 연구에서는 이미지를 분류하는 인공 신경망 가속기를 최적화했고, 이를 구현하여 기존 인공 신경망 가속기와 성능을 비교 분석했다. FPGA(Field Programmable Fate Array) 보드를 이용하여 가속기를 구현했으며, 해당 보드의 내부 메모리인 BRAM 을 FIFO(First In First Out)구조로 설계하여 메모리 시스템을 구현했다. Approximate computing 기법을 효율적으로 적용하기 위해 FWL(Fractional Word Length)최적점을 분석했고, 이를 기반으로 인공 신경망 가속기의 부동 소수점 연산을 고정 소수점 연산으로 변환했다. 구현된 인공 신경망 가속기는 기존의 인공 신경망에 비해, 약 7.4%더 효율적인 전력소모량을 보였다.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.16-23
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• 2022

Cardiac disease is the most common cause of death worldwide. Therefore, detection and classification of electrocardiogram (ECG) signals are crucial to extend life expectancy. In this study, we aimed to implement an artificial intelligence signal recognition system in field programmable gate array (FPGA), which can recognize patterns of bio-signals such as ECG in edge devices that require batteries. Despite the increment in classification accuracy, deep learning models require exorbitant computational resources and power, which makes the mapping of deep neural networks slow and implementation on wearable devices challenging. To overcome these limitations, spiking neural networks (SNNs) have been applied. SNNs are biologically inspired, event-driven neural networks that compute and transfer information using discrete spikes, which require fewer operations and less complex hardware resources. Thus, they are more energy-efficient compared to other artificial neural networks algorithms.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1085-1096
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• 2022

The manufacturing industry is continuously pursuing advanced technology and smartization as it converges with innovative technology. Improvement of manufacturing productivity is achieved by monitoring, analyzing, and controlling the facilities and processes of the manufacturing site in real time through a network. In this paper, we proposed a new OPC-UA based digital twin model for smart factory facilities. A testbed system for USB flash drive packaging facility was implemented based on the proposed digital twin model and OPC-UA data communication scheme. Through OPC-UA based digital twin model, equipment and process status information is transmitted and received from PLC to monitoring and control 3D digital models and physical models in real time. The usefulness of the developed digital twin testbed system was evaluated through usability test.