• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.116.1-116
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• 2001

In the near future, drive-by-wire systems will replace mechanical systems of vehicles. Since there would be no mechanical redundancy in the x-by-wire subsystem, it needs to improve the reliability of the system using fault diagnosis of sensors and actuators. This paper proposes a Kalman filter based fault diagnosis method for the vehicle with the drive-by-wire system, which includes steer-by-wire, brake-by-wire and throttle-by-wire systems. We will show that the proposed method is successful in fault detection and isolation for single sensor/actuator faults of the vehicle system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2594-2599
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• 2003

We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.822-831
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• 2009

The porcelain insulators are important devices, that are used to isolate electrically and hold mechanically in the high-voltage power transmission systems. The faults of the insulators induce very serious problems to the power transmission line. In this paper, we introduce techniques for fault detections of insulators by acoustic radiation noises from them. We measured radiation noises from normal state insulators and fault state insulators. The used insulators were two different type porcelain insulators, a cut out switch, two different type line posters, and a lightning arrester. Each results was compared each other in time domain, frequency domain and filter banks' outputs. We found the possibility of detection of insulators' faults and also suggested techniques for fault detections.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.2
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• pp.191-198
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• 2011

In this paper, the fault diagnosis scheme for PMSM drives has been proposed to maintain control performance under a switch open-phase fault of inverter. When the open-phase fault occurs, the stator resistances of PMSM are estimated by Extended Kalman Filter (EKF) in real time and can appear differently according to the location of fault occurrence to check the fault detection and identification. The control algorithm is configured without the additional device and low cost by adding the existing control program. Also, by using motor parameter the estimated stator resistance value improves the control performance of the controller affected by parameter variation. The feasibility of the proposed fault diagnosis algorithm is validated in simulation and experiment.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.11
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• pp.705-710
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• 2011

Fault detection has to be proceeded by steady state filtering to get rid of transient effect associated with thermal capacity. Coefficient of variance (COV), ratio of standard deviation devided by moving average, was employed as steady-state filter. Engine speed and refrigerant pressures were selected as parameters representing system dynamics. The filtered values were registered as members of steady-state DB. They were found to show good functional relationship with ambient temperature. The relationship was fitted with a second order polynomial and the distribution bounds of the data around the fitted curve were expressed by visual inspection because of varying average and random data interval. Fault data were compared with the steady-state data obtained during normal operation. The fault data were easily isolated from the fault-free one. To make such isolation reliable, tests to construct good DB should be designed in a systematic way.

• Journal of Power Electronics
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• v.13 no.2
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• pp.304-312
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• 2013

The most common power quality problems in distribution systems are related to unbalanced voltage sags. Voltage sags must be detected quickly and corrected in a minimum amount of time. One of the most widely used methods for sag detection is based on the d-q transformation. This method has the disadvantage of missing the detection of unbalanced faults, because this method uses a voltage sag level signal obtained from the average of 3 phases for sag detection. In this paper, an adaptive filter sag detection method is proposed for Dynamic Voltage Restorers (DVR) under unbalanced fault conditions. The proposed DVR controller is able to detect balanced, unbalanced and single phase voltage sags. A novel reference voltage generation method is also presented. To validate the proposed control methods, a 3-phase DSP controlling a DVR prototype with a power rating of 1.5-kVA has been developed. Finally, experimental results are presented to verify the performance of the proposed control methods.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.301-305
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• 2001

A novel approach based on parameters estimation is presented far fault detection and diagnosis in sensors. Based on known precise parameter of normal working sensors system model is built from real laboratory inputs-outputs data, sequentially residual serial is obtained. Where decision-making rule of detection the fault is given via the use of beys theory, whilst a filter least-square computative algorithm for estimating fault parameters is given. The algorithm is a fast and accurate to calculate value of sensors faults when system model contains noise and sensors outputs contain measured noise. The method can solve both gain type and bias type fault in sensors. Simulated numerical example is included to demonstrate the use of the proposed approaches.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.45.3-45
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• 2001

This paper deal with a fault detection algorithm for front wheel passenger car systems by using robust $H{\infty}$ control theory. Firstly, we present a unified formulation of vehicle dynamics for front wheel car systems and transform this formulation into state space form. Also, by considering the cornering stiffness which depends on the tyre-road contact conditions, a multiplicative uncertainty for vehicle model is described. Next, the failures of sensor and actuator for vehicle system are defined in which the fault .lter is considered. From the nominal vehicle model, an augmented system includes the multiplicative uncertainty and the model of fault filter is proposed. Lastly by using $H{\infty}$ norm property the fault detect conditions are deefi.ned, and the actuator and sensor failures are detected and isolated by designing the robust $H{\infty}$ controller, respectively.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.410-418
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• 1999

This paper describes the use of residual and parameter identification methods for fault detection in an air handling unit. Faults can be detected by comparing expected condition with the measured faulty data using residuals. Faults can also be detected by examining unmeasurable parameter changes in a model of a controlled system using a system identification technique. In this study, AutoRegressive Moving Average with seXtrnal input(ARMAX) and AutoRegressive with eXternal input(ARX) models with both single-input/single-input and multi-input/single-input structures are examined. Model parameters are determined using the Kalman filter recursive identification method. Regression equations are calculated from normal experimental data and are used to compute expected operating variables. These approaches are tested using experimental data from a laboratory's variable-air-volume air-handling-unit.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.35-38
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• 2008

This paper develops an aero engine LPV mathematical model to exactly describe aero engine dynamic process characteristics, eliminate the effect of modeling error. Design FDF with eigenstructure assignment. The simulation results of turbofan engine control system sensor fault show that this method has good performance in focusing discrimination in fault signal with modeling eror, enhancing the robustness to unknown input, detecting accuracy is high and satisfiying real-time requirement.