• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.683-690
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• 1999

This paper deals with a fault-tolerant control method for robust control of RPV(Remotely Piloted Vehicle). To design the flight control system, the 6-DOF simulation program has been developed based on the dynamic model of RPV. A robust fault detection and diagnosis method proposed by Kwon et al. [8]-[10] is adopted to detect the actuator fault of RPV and to make the controller reconfiguration. The Hoo control method is applied to the flight control system. An integrated simulation for performance evaluation of the fault-tolerat\nt control system designed is performed via 6 DOF simulation and shows that the control system works even under the actuator fault.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.127.1-127
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• 2001

In this paper we propose an input/output model based fault diagnosis method to detect and isolate single faults in the robot arm control system. The proposed algorithm is functionally composed of three main parts-parameter estimation, fault detection, and isolation, When a change in the system occurs, the errors between the system output and the estimated output cross a predetermined threshold, and once a fault in the system is detected, and in this zone the estimated parameters are transferred to the fault classifier by ART2(adaptive resonance theory 2) neural network for fault isolation. Since ART2 neural network is an unsupervised neural network fault classifier does not require the knowledge of all possible faults to isolate the faults occurred in the system. Simulations are carried out to evaluate the performance of the proposed ...

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.211-214
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• 1998

A detection filter assigns a specific direction to the response with respect to each fault, by which it can detect the occurrence of the several faults. The separability of a detection filter can be determined by the orthogonality among these directions. In this paper, we define the separability of a detection filter as the orthogonality of the directions in output space, and present it mathematically by using conditions number. An algorithm to determine the optimal sensor gain to maximize separability is proposed and applied to the PWR nuclear reactor model.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.135-141
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• 2000

The major role of temperature sensors in thermal error compensation system of machine tools is improving machining accuracy by supplying reliable temperature data on the machine structure. This paper presents a new method for fault diagnosis of temperature sensors and recovery of faulted data to establish the reliability of thermal error compensation system. The detection of fault and its location is based on the correlation coefficients among temperature data from the sensors. The multiple linear regression model which is prepared using complete normal data is also used fur the recovery of faulted data. The effectiveness of this method was tested by comparing the computer simulation results and measured data in a CNC machining center.

• Tribology and Lubricants
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• v.14 no.3
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• pp.74-80
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• 1998

The morphologies of the wear particles are directly indicative of wear process occuring in the machine. The analysis of wear particle morphology can therefore provide very early detection of a fault and can also ofen facilitate a dignosis. For this work, the neural network was applied to identify friction coefficient through four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris generated from the machine. The averages of these parameters were used as inputs to the network. It is shown that collect identification of friction coefficient depends on the ranges of these shape parameters learned. The various kinds of the wear debris had a different pattern characteristics and recognized relation between the friction condition and materials very well by neural network. We discuss how the network determines difference in wear debris feature, and this approach can be applied for machine condition monitoring and fault diagnosis.

• Journal of the Semiconductor & Display Technology
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• v.9 no.4
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• pp.93-97
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• 2010

Fast incipient fault diagnosis is becoming one of the key requirements for economical and optimal process operation management in high-tech industries. Artificial neural networks have been used to detect faults for a number of years and shown to be highly successful in this application area. This paper presents a novel test technique for fault detection and classification for module process of TFT-LCD manufacture using support vector machines (SVMs). In order to evaluate SVMs, this paper examines the performance of the proposed method by comparing it with that of multilayer perception, one of the artificial neural network techniques, based on real benchmarking data.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1127-1132
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• 2000

Impulsive acoustic and vibration signals within rotating machinery are often induced by irregular impacting. The detection of these impulses can be useful for fault diagnosis purposes. Recently there has been an increasing trend towards the use of higher order statistics for fault detection within mechanical systems based on the observation that impulsive signals tend to increase the kurtosis values. This paper considers the use of the third and fourth order Wigner moment spectra, called the Wigner bi- and tri- spectra receptively, for analysing such signals. Expressions for the auto-and cross-terms in these distributions are presented and discussed. It is shown that the Wigner trispectrum is a more suitable analysis tool and it performance is compared to its second order counterpart for detecting impulsive signals. These methods are also applied to measured data sets from an industrial gearbox.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1279-1289
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• 1992

Fault-tolerant system in improved the reliability and safety by using hardware and software redundancy. Fault mask and detection, identification techniques are conditionally used with system's application areas. Here DMR system is operated with standby and fail-safe module method that has minimal hardware and software redundancy, then its reliablity and safety comparison is presented respectively. Also this paper proposed an effective methods of dealing with transient faults as compared system's MTTFs to transient faults tolerance capabilities of self-diagnosis program.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.643-649
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• 2012

The diagnosis technique of stator winding faults based on Motor Current Signature Analysis(MCSA) was suggested. Park's vector pattern, the circle that is drawn by d-q transformed currents($i_d$, $i_q$), is widely used for stator winding faults detection. The current Distortion Ratio(DR), defined by the ratio of max axis and min axis of ellipse of Park's vector's pattern, was more simple and powerful method than the Park's vector pattern. In this study, a calculation method of distortion ratio of Park's vector pattern was suggested for auto diagnosis of stator winding short fault and usefulness of suggested calculation method of distortion ratio was verified through simulation using LabVIEW program.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.251-258
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• 2003

Optical Switching Matrix (OSM) or Optical Multistage Interconnection Networks (OMINs) comprising photonic switches have been studied extensively as important interconnecting blocks for Optical Cross Connects (OXC) based on Optical Burst Switching (OBS). A basic element of photonic switching networks is a 2$\times$2 directional coupler with two inputs and two outputs. This paper is concerned with the diagnosis of multiple crosstalk-faults in OSM. As the network size becomes larger in these days, the conventional diagnosis methods based on tests and simulation become inefficient, or even more impractical. We propose a simple and easily implementable algorithm for detection and isolation of the multiple crosstalk-faults in OSM. Specifically. we develop an algorithm for isolation of the source fault in switching elements whenever the multiple crosstalk-faults arc detected in OSM. The proposed algorithm is illustrated by an example of 16$\times$16 OSM.