• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1913-1920
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• 2009

An intelligent accurate sun tracking controller for solar lighting system was developed. This controller can detect the faulty sensor and correct the error signal based on Principle Component Analysis theory. A fuzzy controller was developed to control the tracker by using the collected sensor signal for precise position control. Also a multiple range searching sensor module for sun tracking was designed. To show the validity of the developed system, some experiments in the field were illustrated.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.329-336
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• 2007

This paper considers a fault accommodation problem for inertial navigation systems (INS) that have redundant inertial sensors such as gyroscopes and accelerometers. It is wellknown that the more sensors are used, the smaller the navigation error of INS is, which means that the error covariance of the position estimate becomes less. Thus, when it is decided that double faults occur in the inertial sensors due to fault detection and isolation (FDI), it is necessary to decide whether the faulty sensors should be excluded or not. A new accommodation rule for double faults is proposed based on the error covariance of triad-solution of redundant inertial sensors, which is related to the navigation accuracy of INS. The proposed accommodation rule provides decision rules to determine which sensors should be excluded among faulty sensors. Monte Carlo simulation is performed for dodecahedron configuration, in which case the proposed accommodation rule can be drawn in the decision space of the two-dimensional Cartesian coordinate system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1005-1018
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• 2017

This paper proposes an App Visualization (AppV) based on IoT Self-diagnosis Micro Control Unit (ISMCU) for accident prevention. It collects a current status of a vehicle through a sensor, visualizes it on a smart phone and prevents vehicles from accident. The AppV consists of 5 components. First, a Sensor Layer (SL) judges noxious gas from a current vehicle and a driver's driving habit by collecting data from various sensors such as an Accelerator Position Sensor, an O2 sensor, an Oil Pressure Sensor, etc. and computing the concentration of the CO collected by a semiconductor gas sensor. Second, a Wireless Sensor Communication Layer (WSCL) supports Zigbee, Wi-Fi, and Bluetooth protocol so that it may transfer the sensor data collected in the SL to ISMCU and the data in the ISMCU to a Mobile. Third, an ISMCU integrates the transferred sensor information and transfers the integrated result to a Mobile. Fourth, a Mobile App Block Programming Tool (MABPT) is an independent App generation tool that changes to visual data just the vehicle information which drivers want from a smart phone. Fifth, an Embedded Module (EM) records the data collected through a Smart Phone real time in a Cloud Server. Therefore, because the AppV checks a vehicle' fault and bad driving habits that are not known from sensors and performs self-diagnosis through a mobile, it can reduce time and cost spending on accidents caused by a vehicle's fault and noxious gas emitted to the outside.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.2
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• pp.89-95
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• 2003

We consider a problem of application of analytical redundancy to engine synchronization process of spark ignition engines, which is critical to timing for every ECU process including ignition and injection. The engine synchronization process we consider here is performed using the pulse signal obtained by the revolution of crankshaft trigger wheel (CTW) coupled to crank shaft. We propose a discrete-time linear model for the signal, for which we construct FDI (Fault Detection & Isolation) system consisting residual generator and threshold based on linear observer.

• Journal of the Society of Naval Architects of Korea
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• v.30 no.4
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• pp.8-16
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• 1993

Auto-Pilot System uses heading angle information via the position sensor and the rudder device to control the ship direction. Most of the control logics are composed of the state estimation and control algorithms assuming that the measurement device and the actuator have no fault except the measurement noise. But such asumptions could bring the danger in real situation. For example, if the heading angle measuring device is out of order the control action based on those false position information could bring serious safety problem. In this study, the control system including improved method for processing the position information is applied to the Auto-Pilot System. To show the difference between general state estimator and F.D.F., BJDFs for the sensor and the actuator failure detection are designed and the performance are tested. And it is shown that bias error in sensor could be detected by state-augmented estimator. So the residual confined in the 2-dim in the presence of the sensor failure could be unidirectional in output space and bias sensor error is much easier to be detected.

• KSTLE International Journal
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• v.4 no.2
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• pp.37-42
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• 2003

One of the obstacles for a magnetic bearing to be used in the wide range of industrial applications is the failure modes associated with magnetic bearings, which we don't expect for conventional passive bearings. These failure modes include electric power outage, power amplifier faults, position sensor faults, and the malfunction of controllers. Fault-tolerant magnetic bearing systems have been proposed so that the system can operate in spite of some faults in the system. In this paper, we designed a fault-tolerant magnetic bearing system for a turbo-molecular vacuum pump. The system can cope with the actuator/amplifier faults which are the most common faults in a magnetic bearing system. We implemented the existing fault-tolerant algorithms to experimentally prove the adequacy of the algorithms for industrial applications. As it turns out, the system can operate even with three simultaneously failing poles out of eight actuator poles.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2011-2013
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• 2003

The effects of sensor faults on motor variables and control performance in induction motor drives are analyzed by both theoretical approach and simulation study, Vector control and direct torque control method for induction motor are well known. To control speed or position, the informations on rotor speed and rotor or stator flux are required in these control algorithms. The speed is measured by encoder. and the rotor or stator flux is estimated using motor parameters and measured currents. The control input generated based on the information from a faulted sensor should be far from the desired value and deteriorates the overall control performance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.126-133
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• 2003

High performance induction motor drives are driven by two advanced control methods: vector control and direct torque control (DTC). In order to apply the control methods to the speed/position control systems, the informations on rotor speed and rotor or stator flux are required. The speed is measured by encoder, and the rotor or stator flux is estimated by using the motor parameters and measured currents. The control input generated on the basis of the information that is provided by abnormal sensors should be far from the desired value and deteriorates the overall control perfonnance. In this paper, the effects of sensor faults on the motor variables and the control performance of induction motor drives are analyzed by both theoretical approach and simulation study. The presented analysis results could be utilized for the purpose of developing a fault detection and isolation scheme in induction motor drives.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.2103-2105
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• 1998

Switched Reluctance Motor is simple structure which used Accel/Decel application field because of cheap cost and High efficiency. For driving this motor, it is essential to need position sensor and driving converter. so, many topology and sensor have been studied untill now. Asymmetric Bridge Converter which has been known for the best control and efficiency is used chopping to control current of motor coil according to changing of motor speed. But this is embossed as a fault because it come to bring switching loss due to rapid switching frequency. In this paper, I applied to Soft Switching Mode by Partial Resonant Method to compensate these fault and to show the usabilityness of low switching device.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.58-63
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• 2014

Most of light duty AGVs(AGCs) using tape of magnetic for the guide path have digital guidance magnetic sensor. Digital guidance magnetic sensor using magnet-tape is on/off type and has positioning error of magnet-tape as 10~50 mm. AGC using this sensor doesn't induce accurate position of magnet-line which is magnet-tape because of magnetic field which motor in AGC creates, outer magnetic field, earth's magnetic field, etc. AGC when driving wobbles due to this error and this error can cause path deviation. In this paper, we propose fuzzy inference system for improvement of bipolar analog magnetic guidance sensor performance. Fuzzy is suitable in term of fault tolerance, uncertainty tolerance, real-time operation, and Nonlinearity as compared with other algorithms. In previous research, we produced bipolar magnetic guidance sensor and we set the threshold in order to calculate digital values of magnet position. Fuzzy inference system is designed using outputs of Analog hall sensors. Magnet position calculated by digital method is improved by outputs of this system. In result, proposed method was verified by improving performance of magnetic guidance sensor.