• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2474-2479
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• 2012

A sensorless vector control of an induction motor provides a good performance in the middle and high speed region. However, in the low speed region, it is very difficult to implement the sensorless vector controller because the feeding voltage measured by the motor is very low. In this paper, to improve the performance of a sensorless vector control of an induction motor in the low speed region under 3Hz, we proposed the fuzzy logic controller using the zooming algorithm. To verify the performance of the proposed controller, an experiment has been performed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.1
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• pp.68-73
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• 2003

This paper describes a newly developed vector drive system without the speed sensor using theory of a flus observer and based on the field oriented vector control. The new method of speed estimation is presented to operate with the position and magnitude of the secondary flux vector which obtain to the observer md detected current. As the speed of estimation is determined to the flux and the motor constants, this method don't need to adjust the gain of the parameter and is operated simply. On basic the derived theory for vector control, sensorless speed control system for induction motor drive is design and realized. It is determined a controllers gain and observer gain by simulation and the experiment of sensorless vector drive is realized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.944-946
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• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. We modified the existing Support vector machine algorithm to fit into the distributed hadoop architecture system for localization of a sensor node. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.150-156
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• 2001

This paper proposed a speed estimator using MRAC(Model Reference Adaptive Control) for sensorless vector control. It is robust for parameter variation or disturbance and the estimated speed is used as feedback in a vector control system. Experiment is presented to confirm the theoretical analysis.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.6
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• pp.552-559
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• 2000

Most of the sensorless vector control methods use the equivalent circuit of induction motors. Therefore parameter auto-measurement of drive motor is essential function in commercial sensorless vector control inverters. The accuracy of motor parameter measurement greatly affects the performance of sensorless vector control. In this paper limitations of conventional measurement methods are examined, and new measurement methods are proposed to solve those limitations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1142-1146
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• 2004

This paper describes sensorless vector control of induction motor using speed observer in steady state. In sensorless vector control of induction motor, the proposed speed observer is consists of q-axis voltage of controller and real current. This paper investigates the speed characteristics when a step change of speed reference. This is verified by simulations and experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2885-2890
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• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.8 no.4
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• pp.46-54
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• 1994

Exhbitlon hghting design be done aftrr due consideration of the photochermcal reaction and h ~ ~ i i tc~.fficits~ upn exposure to light. In this study the balanced judgement is as follows. The most light-susceptible material shouid be illu~stratrui less than 50[k] (illurnlnance-hours per year : 120, 000k.h)and the illuminance of moderately sensitive rriatcrinl k 200[1x] (illuminance hours per year : 480, 0001x.h). Moreover to minimize damage the sources of light shoulcl not only contribute as little as heat possible but remove ultraviolt radiation by filters. Also the sources of light must have good color rendering and low color temperature.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2003.05a
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• pp.402-407
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• 2003

IPMSM은 회전자 위치의 정확한 정보를 알기 위하여 엔코더와 리졸버와 같은 위치센서를 사용한다. 이러한 센서는 무게와 부피가 증가하고 가격이 높으며 온도와 외란 등에 매우 민감하다. 따라서 AC 드라이브의 센서리스 벡터제어에 많은 관심을 가지게 되었다. 센서리스는 수학적 모델, 물리적인 현상 및 제어이론을 이용하는 방법으로 분류되어 연구되고 있다. 수학적인 모델을 이용하는 방법에는 고장자 전압에서 고정자 저항에 의한 전압 강하분을 제거한 항을 적분하여 자속의 위치를 추정한다.(중략)

• The Journal of the Acoustical Society of Korea
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• v.32 no.6
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• pp.484-493
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• 2013

Typical underwater acoustic sensors can measure the scalar quantity of sound-pressure-magnitude with the limitation of being unable to identify the direction of an incoming wave. This paper proposes a method to detect the direction of the sound wave with a ring sensor. The sensor of the proposed structure has a piezoceramic ring divided into eight elements, and distinguishes the direction of the sound wave by properly combining the output voltages of the piezoceramic elements. Further, through the analysis of the effects of the structural parameters like the ring radius and length, and piezoceramic thickness, we have suggested the way to improve the sensitivity of the vector sensor.