• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.600-605
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• 2011

This paper shows field test and evaluation results for a wireless vehicle detector with anisotropic magneto-resistive (AMR) sensors. The detector consists of two AMR sensors and mechanical and electronic apparatuses. The AMR sensor senses disturbance of the earth magnetic field caused by a vehicle moving over the sensor and then produces an output indicative of the moving vehicle. In this paper, vehicle speeds are calculated by using two AMR sensors fixed on a board, with constant distance. To test and evaluate the accuracy of the detector in real traffic situations, the detector was installed on a local highway and vehicle speeds and volumes were measured both in a free running and a highly congested traffic. The measurements from the detector are compared with the reference measurements obtained from a traffic camera with the Mean Absolute Percentage Errors (MAPE), which has proved the usefulness of the detector in the field.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.27-32
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• 2002

This paper describes a fuzzy steering controller for an outdoor autonomous mobile robot using MR(magneto-resistive) sensor. Using the magnetic field difference values(dBy, dBz) obtained from the MR sensor, we designed fuzzy logic controller for driving the robot on the road center and proposed a method to eliminate the Earth magnetic field. To develop an autonomous mobile robot simulation program, we have done modeling MR sensor, mobile robot and coordinate transformation. A computer simulation of the robot including mobile robot dynamics and steering was used to verify the driving performance of the mobile robot controller using the fuzzy logic. So, we confirmed the robustness of the proposed fuzzy controller by computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.587-590
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• 2000

By using the information obtained from output of the MR(Magneto Resistive) sensor for an unmanned vehicle system which is used in the Local Position System. We develop an algorithm that decides the distance and directions between the guideline made by magnets and vehicle, and make an unmanned vehicle driving system that is steered by PD controller and MR sensor

• Journal of Sensor Science and Technology
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• v.18 no.5
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• pp.393-401
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• 2009

This paper describes development of a new displacement sensor for intelligent suspension system in which the damping force has been controlled by MR fluid. Most of the current vehicle height sensors have been installed at external place of the damper and connected to that by mechanical linkages so far. The developed sensor has a new mechanism which detects movement of the sensor rod same as connecting rod in the suspension damper by using a GMR Sensor and converts it to the relative displacement from an initial position.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.279-282
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• 2004

본 논문에서는 자기저항 센서를 이용하여 자율주행 시스템에서 필요로 하는 자석의 종류에 따른 자계의 특성을 분석하였다 분석결과 거리에 따라 자계의 특성이 변화하고, 자석에 근접할수록 자계의 변화가 급격하게 나타난다. 센서가 자석에서 멀어질수록 지자계의 값에 가까워진다 또한 페라이트자석 보다 네오디뮴 자석의 자계특성이 우수함을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.6-6
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• 2000

By using the information obtained from the outputs of MR(MagnetoResistive) sensors for an Unmanned Vehicle Driving System, we develop an algorithm that decides the distance and direction between vehicle and the guideline which is made by the magnet. To improve the robust tracking properties of the closed loop system, we introduce H$\infty$ controller and its application for the Unmanned Vehicle Driving System.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2385-2387
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• 2002

종래 도로상의 차량검지기들은 기후변화 및 도로환경의 변화, 물리적인 변화에 영향을 받아 감지의 정확도가 떨어져 신뢰도 높은 교통정보를 생성하기가 어렵고, 제품의 가격이 고가이며, 설치 및 유지, 보수에 많은 비용과 인력이 요구된다. 본 연구에서는 종래의 차량 검지기가 지니는 문제점들을 해결하여 어떠한 환경하에서도 신뢰성 있는 차량 주행정보를 제공하며 동시에 유지, 보수 비용이 저렴한 검지기로서 AMR(Anisotropic Magneto-Resistive) 센서를 이용하여 도로상의 차량 이동에 따른 지구자기장(Earth Magnetic Field) 변화를 감지하고 차량의 이동상태를 파악하는 교통량 계측장치를 제시한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.211-214
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\sub$x/, B$\sub$y/, B$\sub$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, learning itself, and the adequacy of the design controller. Also, the performance of the controller can be verified through simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1063-1066
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• 2003

A flow-meter and its measurement controller was developed for a hydraulic system. This study, for development of positive displacement flow-meter, consist of PIC(Peripheral Interface Controller) controller with MR(Magneto-resistive) sensors. This flow-meter is used valve position indicator for valve control system by hydraulic. The MR sensors are used for the rotation of OVAL gear that detecting device. In the ship environments, consideration that necessary explosive proof. Thus electro device or electro flow-meter needs explosion design for electric circuit. We designed noncontact type flow-meter and evaluated the safety and measuring abilities.