• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.199-200
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• 2008

Demand for reliability and safety in modem systems has been increased in the research on fault detection and isolation. At traditional approaches to fault detection, redundant sensors have been used. More advanced methods are the residual analysis of signals which are created by the comparison between the actual plant behavior and the output response of a mathematical model. However, mathematical system models are difficult to obtain by using physical laws. These problems can be solved by system identification. In this paper, the transfer function of a direct current motor is estimated by using the system identification. And, the efficiency of the fault detector design is verified by using experiments.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.42-45
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• 2001

In the speed-sensorless induction motor control systems, only a few percents of error in current measurement badly deteriorates the control performance. And early detection and accomodation of the faults of current sensor is very important to enhance the reliability of the induction motor control system. In this paper, we propose two sensor fault detection schemes having desired functions; fault detection, isolation of failed sensor and compensation of fault effect. The two schemes operate in real-time and employ EKFs (Extended Kalman Filter) for residual generation. Simulation results show that the proposed schemes are very useful in maintaining the control performance of the induction motor driven servo systems even in the face of sensor faults.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.107-116
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• 2003

This paper presents a systematic design methodology for fault tolerant controller against a fault in actuators and sensors of linear stochastic systems with uncertainties. The scheme is based on fault detection and diagnosis(isolation and estimation) using a bank of robust two-stage Kalman filters, and accommodation of the actuator fault by eigenstructure assignment and immediate compensation of the sensor's faulty measurement. In order to clarify the fault feature in test statistics of residual, noise reduction method is given by multi-scale discrete wavelet transform. The effectiveness of our approach Is shown via simulations for a VTOL(vertical take-off and landing) aircraft subjected to parameter variations, external disturbances, process and sensor noises.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.4
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• pp.880-888
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• 2001

This paper presents a fault detection asnd isolation algorithm for highly reliable gantry crane system. The algorithm is constructed by multiple PI observer technique, and the magnitude of actuator fault can be estimated by using integrated estimated output error. Also, the complex actuator and /or sensor fault can be detected and isolated by monitoring the integrated error and the estimated state error. Considering the actuator and/or the sensor fault, we verify that these fault can be detected and isolated through simulation. Lastly, we show a simple reliable control method by using the detected fault signal and an added observer.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.4
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• pp.366-376
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• 2002

A sensor fault detection and isolation scheme(SFDIS) is adopted to improve the reliability of direct torque controlled induction motor drives and the experimental results are discussed. Major contributions include: experimental analysis of a few important sensor faults. design and implementation of the proposed SFDIS, and the fault tolerant control system(FTCS). Although the adopted SFDIS employs only one observer for residual generation, the system has the function of fault isolation that only multiple observer schemes can have. To verify the performance of the proposed scheme, the speed control system is designed for the 2.2kW direct torque controlled Induction motor. Hardware of the control system consists of a control board using TMS320OVC33 and a power stack using IPM. Experimental results for various type of sensor faults show the effectiveness of the SFDIS and the FTCS.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.769-772
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• 1999

In this paper we propose an FDI(fault detection and isolation) algorithm to detect and isolate single faults in linear systems. When a change in the system occurs the errors between the system output and the estimated output cross a threshold, and once a fault in the system is detected, the FCFM statistically isolates the fault by using the error between each neural network based fault model output and the system output.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.142-148
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• 2008

In this paper, we deal with the problem of reducing the order of the detection filter for the linear time-invariant system. Even if the detection filter is generally designed in the form of full order linear observer, we show that it is possible to reduce its order when the response of fault signals is limited to a subspace of the estimation state space. We propose a method to extract the subspace using the observer canonical form considering the dynamics related to the remaining subspace acts as a disturbance. We designed a reduced order detection filter to reject the disturbance as well as to guarantee fault detection and isolation. A simulation result for a 5th order system is presented as an illustrative example of the proposed design method.

• Advances in robotics research
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• v.2 no.1
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• pp.99-112
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• 2018

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1225-1231
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• 2009

One reaction wheel cluster of satellite usually has four reaction wheels. Each wheel is not arranged parallel to the attitude axis of satellite. Therefore, if one reaction wheel is broken, it is very hard to isolate the fault except using the sensors of wheel itself. In this paper, the isolator of satellite reaction wheel cluster is designed. Using a dual filter, FDP(Fault Detection Parameter) is made to detect fault, and using a multi-hypothesis extended Kalman filter, fault isolation of wheel cluster is done. We verify the improvement of isolation performance of wheel cluster by simulation with 4-reaction wheel cluster.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.689-691
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• 1995

In this paper, a fault detection and isolation unit(FDIU) for a centrifugal pump system driven by DC-motor is proposed. The proposed scheme can be classified into the dedicated observer scheme(DOS). A fuzzy logic based inference engine is adopted for the isolation of each faults. Having the fuzzy inference engine, the proposed FDIU resolve a few important problems of the conventional DOSs with conventional two valued logic. The ouputs of the proposed FDIU are not "ith fault occurred" but the grade of memberships that indicate the consistency of observered symptoms(residuals) with each fault symptoms stored in the rule base. The ouputs can easily be transferred to the ranking of the fault possibilities and it will provide very useful informations in monitoring the process. The simulation results show that the FDIU has very good diagnostic ability even in the noisy environment.