• Title/Summary/Keyword: 실내온도제어

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Temperature, Humidity, $CO_2$ Detection & Control Multicast Controller (온도.습도.$CO_2$ 검출 및 제어용 멀티캐스트 컨트롤러)

  • Kim, Myung-Ho;Lee, Tae-Bong
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.1781-1782
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    • 2007
  • 건축물의 냉방 난방 제어를 위해서 열쾌적성과 에너지 절감에 기술이 집중되어서 발생하는 실내공기 오염에 대해서 실내 냉방 난방 부하와 $CO_2$ 농도에 따라서 환기량을 조절하는 "온도 습도 $CO_2$ 검출 및 제어용 멀티캐스트 컨트롤러"(이하 "컨트롤러")를 개발하였다. 컨트롤러의 어플리케이션은 뉴런C로 프로그램 하였으며 자동제어 네트워크의 환경에 따라서 전용선, 전력선 및 무선 통신 방식을 적용할 수 있도록 모듈형태로 제작하여서 현장 적용성을 높였다. 연구 결과 온도, 습도 및 $CO_2$를 분석하여 환기량을 조절하여 낭비 에너지를 줄였고 실내 공기의 오염을 예방하게 되었고 멀티캐스트 방식으로 자동제어 네트워크의 통신트래픽이 감소되고 효율성을 높였다.

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Development of Intelligence comfortable Air Handling System Based on LonWorks (LonWorks 기반의 지능형 쾌적 공조 시스템 개발)

  • Kim, Gwan-hyung;Kang, Sung-in;Hwang, Yeong-yeun;Byun, Gi-sig
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.273-275
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    • 2009
  • In recent years, many home machines have been developed in order to design and control comfortable interior inside houses. For such task, important factors are temperature, natural and interior lights, and space and control of relative factors each other. This paper presents novel sensor module inside houses, which is designed based on these factors through the PMV (Predicted Mean Vote) standard using information about home state. Moreover, LonWorks based power line communication technique is utilized for control interior lights and air-conditioners by means of wireless remote controllers. This mechanism is systemically operated via intelligent control framework.

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Fuzzy-based Fan Control using Arduino's Temperature and Humidity for Comfortable Indoor Environment (쾌적한 실내 환경을 조성하기 위한 아두이노의 온도와 습도를 이용한 퍼지 기반의 팬 제어 연구)

  • Kim, Jaeheoung;Kim, Jaewoo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.389-392
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    • 2018
  • In this paper, we try to make a pleasant environment by adjusting the fan moving by temperature and humidity in hot and humid room. To do this, we propose a fuzzy-based fan control using room temperature and humidity, collect environment data such as indoor temperature and humidity using Arduino, transmit it to Bluetooth communication, and adjust the operation time of fan according to fuzzy logic. To do this, connect a temperature and humidity sensor to the Arduino hardware, write the source code using the Arduino program on your computer, and code it in Arduino. Then, the environmental data obtained after collecting environmental data such as humidity from Arduino is transferred to the Arduino Control Module through Bluetooth communication. We use the fuzzy logic to control the time of fan operation according to environmental data such as temperature and humidity. At the end of this process, the fan will operate according to temperature and humidity to create a pleasant environment. Through this study, Arduino was simpler and easier to use than I thought, and I think it's easy to use and can be used in real life by using Arduino hardware, data acquisition, fuzzy logic, and control.

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A Simulation of Temperature Control of Greenhouse with Hot-Water Heating System (온수난방시스템 온실의 온도제어 시뮬레이션)

  • 정태상;하종규;민영봉
    • Journal of Bio-Environment Control
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    • v.8 no.3
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    • pp.152-163
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    • 1999
  • It is required to analyze the controlled response of air temperature in greenhouse according to control techniques for precise control. In this study, a mathematical model was established for air heating of greenhouse with hot-water heating system The parameters of the model were decided by regression analysis using reference data measured at the greenhouse being heated In the simulation for the digital control of air temperature in the greenhouse, the mathematical model to evaluate the control performances was used. Tested control methods were ON-OFF contpol, p control, rl control and PID control. The mathematical model represented by inside air temperature ( T$_{i}$), hot-water temperature (T$_{w}$) in heating pipe and outside air temperature (T$_{o}$) was expressed as a following discrete time equation ; T$_{i}$($textsc{k}$+1)= 0.851.T$_{i}$($textsc{k}$)+0.055.T$_{w}$($textsc{k}$)+0.094.T$_{o}$($textsc{k}$) Control simulations for various control methods showed the settling time, the overshoot and the steady state nor as follows; infinite time, 3.5$0^{\circ}C$, 3.5$0^{\circ}C$ for ON-OFF control : 30min 2.37$^{\circ}C$, 0.51$^{\circ}C$ for P control; 21min, 0.0$0^{\circ}C$, 0.23$^{\circ}C$ for PI control; 18min 0.0$0^{\circ}C$, 0.23$^{\circ}C$ for PID control, respectively. PI and PID controls appeared to be optimal control methods. There was no effect of differential gain on the heating process but much effect of integral gain on it.on it.

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(On designing Temperature Control System of the Air-conditioner using immune system) (면역 시스템을 이용한 에어콘의 온도 제어 시스템 설계)

  • Seo, Jae-Yong;Jo, Hyeon-Chan;Jeon, Hong-Tae
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.39 no.1
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    • pp.1-6
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    • 2002
  • In this paper, we propose temperature inference system for indoor and outdoor temperature of the Air-Conditioner with limited sensors. The proposed system based on the network theory of biological immune system consists of indoor and outdoor temperature inference process. It is designed that on-line temperature inference is possible. This system is admirable for unlearned data as well as given input data by making efficient use of previous information.

Indoor Environment Control System Utilizing The Internet of Things (사물인터넷을 활용한 실내 환경 제어 시스템)

  • An, Yoon-Jung;Kim, Dong-Hyeok;Lee, Jee-Hyun;Lee, Boong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.4
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    • pp.645-650
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    • 2017
  • It is a system that controls temperature, humidity and fine-dust to make interior environment more comfortable for modern people who spend 90% of the time in indoor. In an experiment of finding which one of temperature and humidity influence more to discomfort index, for a fixed temperature of 21, discomfort index increased by 0.1 with a 1 change of humidity, and for a fixed humidity of 40, discomfort index increased by 1.2 with a 1 change of temperature. As a result, it was found that the temperature is more influential than the humidity to discomfort index. In an experiment of measuring communicational limitation of Bluetooth, the communication was possible for at most 30 meters without obstacles. With high obstacles like walls or steel bars, it was able to penetrate at most 2 obstacles and maximum distance which it can communicate was 10 meters for just one high molecule obstacle.

Building Indoor Temperature Control Using PSO Algorithm (PSO 알고리즘을 이용한 건물 실내온도 제어)

  • Kim, Jeong-Hyuk;Kim, Ho-Chan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.5
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    • pp.2536-2543
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    • 2013
  • In this paper, we proposed the modeling in one zone buildings and the energy efficient temperature control algorithm using particle swarm optimization (PSO). A control horizon switching method with PSO is used for optimal control, and the TOU tariff is included to calculate the energy costs. Simulation results show that the reductions of energy cost and peak power can be obtained using proposed algorithms.

Temperature and Wind Control of Virtual Warmth Image Using Fuzzy Reasoning Rule (퍼지 추론 규칙을 이용한 가상의 열 영상 온도와 풍향 제어)

  • Kang, Kyoung-Min;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.10a
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    • pp.387-392
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    • 2008
  • 본 논문에서는 에너지 절약을 위한 방법으로 여름철 냉방의 적정 온도 및 풍향을 제어하기 위한 가상의 시뮬레이션을 목적으로 열 영상과 퍼지 추론 규칙을 적용한 온도 및 풍향 제어 기법을 제안한다. 온도 제어를 위한 가상 시뮬레이션에서 열 영상을 분석하기 위해서 영상을 $300{\times}400$의 크기를 가지는 색상 분포 영상으로 변환한다. 색상 분포 영상은 Red, Magenta, Yellow, Green, Sky, Blue의 온도 값을 가지는 R, G, B 값이며 각 색상은 $ 24.0^{\circ}C$에서 $27.0^{\circ}C$의 분포의 온도 값을 가진다. 색상 분포 영상은 아래 계층부터 레벨1에서 레벨10의 높이 계층으로 분류한다. 분류한 각 계층은 고유의 색상 분포도를 가지며 색상이 가지는 온도 수치에 따라서 계층별로 온도를 구성한다. 풍향 제어를 위한 각 계층의 높이는 레벨1에서 레벨3까지는 하위층이며, 레벨 4부터 레벨 7은 중간층, 레벨 8부터 레벨 10은 상위층으로 분류한다. 각 계층의 온도와 높이 레벨 값은 온도 조절과 풍향의 우선 순위, 강도 조절, 지속 시간을 구하기 위한 파라미터이다. 실내 공간의 전체적인 온도의 균형과 풍향을 제어하는 과정으로 풍향의 방향, 지속시간을 적용하고 풍향의 강도를 구하기 위해서 색상 분포영상의 각 구간의 온도 및 높이의 특징을 적용하여 퍼지 소속 함수를 설계한 후, 소속 함수의 소속도를 구하고 퍼지 추론 규칙을 적용하여 풍향의 강도를 구한다.

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A Study on the State feedback with Integral Control for a Variable Air Volume Unit (가변 풍량 유닛에 대한 적분기를 가진 상태 궤환 제어에 관한 연구)

  • 박세화
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.1 no.2
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    • pp.9-14
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    • 2000
  • State feedback with integral control for a variable air volume(VAV) unit which is recently taken notice of for the energy efficiency and saving in the building is studied to investigate the performance of the digital control methodology for the possible practical application. The digital controller which acquires the targat zone temperature and the air flow rate of the supplied air to the zone controls the opening of the damper in the VAV unit. Simulation results are performed for the conditions including reference changes and external thermal variations. In the simulation. simplified conditioned zone and the damper actuator modelling is considered. and relationships between controller gain Parameters and the system dynamics are investigated.

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Intelligent Algorithms for the Effective Control of High-side Pressure and Indoor Air Temperature of a $CO_2$ Automotive Air Conditioner System (자동차 $CO_2$ 냉방시스템의 고압과 실내온도의 효과적인 제어를 위한 지능알고리즘)

  • Jang, Kyung-Chang;Han, Do-Young
    • Proceedings of the SAREK Conference
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    • 2005.11a
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    • pp.480-485
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    • 2005
  • In the respect of the environmental protection viewpoint, the $CO_2$ may be regarded as one of the most attractive alternative refrigerants for an automotive air-conditioning system. Control methods for a $CO_2$ system should be newly developed, because properties of $CO_2$ are different compared with those of classical refrigerants. Especially, high-side pressure of a $CO_2$ system should be controlled for the effective operation of the system. In this study, intelligent control algorithms for a $CO_2$ system were developed ‘ These are a high-side pressure control algorithm and an indoor air temperature control algorithm. These algorithms were analysised by using dynamic models of a $CO_2$ system.

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