• Title/Summary/Keyword: Sensor Control Module

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Development of Control Simulator for Integrated Sensor Module of Vehicle (차량용 통합 센서 모듈 제어를 위한 시뮬레이터 개발)

  • Jeon, Jin-Young;Park, Jeong-Yeon;Byun, Hyung-Gi
    • Journal of Sensor Science and Technology
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    • v.22 no.1
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    • pp.65-70
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    • 2013
  • The integrated sensor module of vehicle combines the functions of rain sensor, auto defog sensor, and sun angle sensor into a single module. These functions originally were applied to work separatively. This integrated sensor module should meet the each performance which appears from the individual modules up to the same level or higher. Therefore, it is important to verify the stability and the accuracy considering the characteristics of the integrated sensor module according to various situations. For the verification, we need to use the actual data of integrated sensor module measured but, a lot of time and money is needed to collect data measured under various circumstances when operating. Thus, through the development of this simulator for the control of the integrated sensor module, we can use it effectively for the initial verification of integrated sensor module by implementing the various situations. In this paper, the simulator for controlling the integrated sensor module which combines vision-based rain sensor, auto defog sensor, auto light sensor, and sun angle sensor has been developed.

Quality Monitoring Method Analysis for GNSS Ground Station Monitoring and Control Subsystem (위성항법 지상국 감시제어시스템 품질 감시 기법 분석)

  • Jeong, Seong-Kyun;Lee, Sang-Uk
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.18 no.1
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    • pp.11-18
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    • 2010
  • GNSS(Global Navigation Satellite System) Ground Station performs GNSS signal acquisition and processing. This system generates error correction information and distributes them to GNSS users. GNSS Ground Station consists of sensor station which contains receiver and meteorological sensor, monitoring and control subsystem which monitors and controls sensor station, control center which generates error correction information, and uplink station which transmits correction information to navigation satellites. Monitoring and control subsystem acquires and processes navigation data from sensor station. The processed data is transmitted to GNSS control center. Monitoring and control subsystem consists of data acquisition module, data formatting and archiving module, data error correction module, navigation determination module, independent quality monitoring module, and system maintenance and management module. The independent quality monitoring module inspects navigation signal, data, and measurement. This paper introduces independent quality monitoring and performs the analysis using measurement data.

A Study of Fire Shunt Guidance Based on Wireless Sensor Networks (무선 센서 네트워크 기반의 화재 대피 유도 연구)

  • Kim, Yong-Woo;Kim, Do-Hyeon;Kwak, Ho-Young;Park, Hee-Dong
    • Journal of Korea Multimedia Society
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    • v.11 no.11
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    • pp.1547-1554
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    • 2008
  • This paper proposes a fire shunt guidance system model based on rule, it presents suitable shunt route in real-time according to collected fire information of the building inside using wireless sensor networks. So, this system model is composed of the sensor alert module, the behavior suggestion module, and the emergency device control module. The sensor alert module uses rule-base algorithm that monitored the information to collect periodically in wireless sensor networks. And, the behavior suggestion module proposed a suitable behavior, this module supports to judge the fire area with danger sensor list. Additional, the emergency device control module controls a related emergency device according to the suggested behavior and to present on a control screen. We experiment the fire shunt guidance system based on Internet Web for operation verification of the proposed system. Consequently, this study supports people safety with the behavior suggestion according to the context information when an emergency situation happens.

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Development of an Illumination Measurement Device for Color Distribution Based on a CIE 1931 XYZ Sensor

  • Son, Do-Ky;Cho, Eun-Byeol;Moon, In-Kyu;Park, You-Sang;Lee, Chung-Ghiu
    • Journal of the Optical Society of Korea
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    • v.15 no.1
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    • pp.44-51
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    • 2011
  • In this paper, an easy-to-use measurement device for illumination distribution is developed. The device consists of a sensor array module, a control module, and a PC interface. The sensor array module incorporates CIE 1931 color sensors and the ARM-based 96 MHz microcontroller in the control module for measurement and data processing. The sensor array module contains 64 color sensors arranged in a $16{\times}4$ array. The sensitivity of the sensor array module can be adjusted depending on the illumination level to be measured. The measurement data and control signals are exchanged via USB 2.0 standard. To demonstrate the performance of the device, the illumination distribution is measured for colors of red, green, and blue and is graphically shown. The device can be used for measurement of the illumination distribution, design and adjustment of LED illumination.

Algorithm for Reducing the Effect of Network Delay of Sensor Data in Network-Based AC Motor Drives

  • Chun, Tae-Won;Ahn, Jung-Ryol;Lee, Hong-Hee;Kim, Heung-Geun;Nho, Eui-Cheol
    • Journal of Power Electronics
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    • v.11 no.3
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    • pp.279-284
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    • 2011
  • Network-based controls for ac motor drive systems are becoming increasingly important. In this paper, an ac motor control system is implemented by a motor control module and three sensor modules such as a voltage sensor module, a current sensor module, and an encoder module. There will inevitably be network time delays from the sensor modules to the motor control system, which often degrades and even destabilizes the motor drive system. As a result, it becomes very difficult to estimate the network delayed ac sensor data. An algorithm to reduce the effects of network time delays on sensor data is proposed, using both a synchronization signal and a simple method for estimating the sensor data. The algorithm is applied to a vector controlled induction motor drive system, and the performance of the proposed algorithm is verified with experiments.

Wireless Sensors Module for Remote Room Environment Monitoring

  • Lee, Dae-Seok;Chung, Wan-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.449-452
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    • 2005
  • For home networking system with a function of air quality monitoring, a wireless sensor module with several air quality monitoring sensors was developed for indoor environment monitoring system in home networking. The module has various enlargements for various kinds of sensors such as humidity sensor, temperature sensor, CO2 sensor, flying dust sensor, and etc. The developed wireless module is very convenient to be installed on the wall of a room or office, and the sensors in the module can be easily replaced due to well designed module structure and RF connection method. To reduce the system cost, only one RF transmission block was used for sensors' signal transmission to 8051 microcontroller board in time sharing method. In this home networking system, various indoor environmental parameters could be monitored in real time from RF wireless sensor module. Indoor vision was transferred to client PC or PDA from surveillance camera installed indoor or desired site. Web server using Oracle DB was used for saving the visions by web-camera and various data from wireless sensor module.

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Development of data processing module of intelligent sensor (지능형 센서의 데이터 처리 모듈 개발)

  • Kim, In-Uk;Lim, Dong-Jin
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.954-956
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    • 1999
  • In the case of using sensor in the industrial control systems, the location of sensor is not close to the system which utilizes the sensor data. Two main functions of intelligent sensor are data processing and communication. In this paper, we will show that the developed result of intelligent sensor, which process the sensor data inside of the sensor module, except for the communication function. For this, we refered to the Profibus and Fieldbus Foundation standard.

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Intelligent AQS System with Artificial Neural Network Algorithm and ATmega128 Chip in Automobile (신경회로망 알고리즘과 ATmega128칩을 활용한 자동차용 지능형 AQS 시스템)

  • Chung Wan-Young;Lee Seung-Chul
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.6
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    • pp.539-546
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    • 2006
  • The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. The sensor module which includes two independent sensing elements for responding to diesel and gasoline exhaust gases, and temperature sensor and humidity sensor was designed for intelligent AQS in automobile. With this sensor module, AVR microcontroller was designed with back propagation neural network to a powerful gas/vapor pattern recognition when the motor vehicles pass a pollution area. Momentum back propagation algorithm was used in this study instead of normal backpropagation to reduce the teaming time of neural network. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation in this study. One chip microcontroller, ATmega 128L(ATmega Ltd., USA) was used for the control and display. And our developed system can intelligently reduce the malfunction of AQS from the dampness of air or dense fog with the backpropagation neural network and the input sensor module with four sensing elements such as reducing gas sensing element, oxidizing gas sensing element, temperature sensing element and humidity sensing element.

Intelligent Air Quality Sensor System with Back Propagation Neural Network in Automobile

  • Lee, Seung-Chul;Chung, Wan-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.468-471
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    • 2005
  • The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. One chip sensor module which include above two sensing elements, humidity sensor and bad odor sensor was developed for AQS (air quality sensor) in automobile. With this sensor module, PIC microcontroller was designed with back propagation neural network to reduce detecting error when the motor vehicles pass through the dense fog area. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation. One chip microcontroller, Atmega128L (ATmega Ltd., USA) was used. For the control and display. And our developed system can intelligently detect the bad odor when the motor vehicles pass through the polluted air zone such as cattle farm.

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Sensor Node Control Algorithm Based on TinyOS (TinyOS 기반의 센서 노드 제어 알고리즘)

  • Boo, Jun-Pil;Yang, Hyeon-Gyu;Kim, Do-Hyeon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.8 no.4
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    • pp.1-8
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    • 2008
  • Recently, there is developing various ubiquitous application services using sensor networks based on TinyOS represented the operating system of sensor node. These sensor networks perform the collection and the transmission of sensing data from sensor node to get the context information. In this paper, we proposes the sensor node control algorithm which converts a sensor node to sleep, active, power off mode according to monitoring result of the voltage state of sensor node. Also, we designs and implement the sensor control module on server, sink, sensor node of sensor networks using this algorithm. It designs a sensor voltage control module of sensor node, data receive and display module of USN server using a java language and TinyOS. And, it checks the voltage state of sensor node, and it changes one of the sleep or power off modes in case of high voltage loss. Accordingly, we effectively use the power of sensor nodes as changing control modes of sensor nodes.

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