• Journal of Power Electronics
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• v.8 no.2
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• pp.181-191
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• 2008

The task performed by induction motors grows increasingly complex in modern industry and hence improvements are sought in the field of fault diagnosis. It is essential to diagnose faults at their very inception, as unscheduled machine down time can upset critical dead lines and cause heavy financial losses. Artificial intelligence (AI) techniques have proved their ability in detection of incipient faults in electrical machines. This paper presents an application of AI techniques for the detection of inter-turn insulation and bearing wear faults in single-phase induction motors. The single-phase induction motor is considered a proto type model to create inter-turn insulation and bearing wear faults. The experimental data for motor intake current, rotor speed, stator winding temperature, bearing temperature and noise of the motor under running condition was generated in the laboratory. The different types of fault detectors were developed based upon three different AI techniques. The input parameters for these detectors were varied from two to five sequentially. The comparisons were made and the best fault detector was determined.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.363-367
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• 1996

The robustness issues in fault detection and isolation(FDI) have received considerable attenuation in recent years, due to the increasing demand for safe and reliable operation of uncertain and complex dynamic systems. The aim of this paper is to present the FDI method by using proportional integral(PI) observer and unknown input observer(UIO) under the faults of actuators and sensors. Due to this simple residual generator, the PI observer can easily detect the both faults of actuator and sensor. A simulation results show the effectiveness of this methods.

• The Transactions of the Korea Information Processing Society
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• v.4 no.5
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• pp.1371-1379
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• 1997

Undetectable faults in a digital circuit are faults that no input patterms can detect.Identifying these faults in test geferation process is very time- consuming especially for sequential circuits .In this paper we present a new algorithm to identify unedtectable faults in sequential cirouits .In the alorithm. we identify uninitializable fip-flops and then, faults that prevent intialization of the fkip-flops(FPIs)are identified, finally propagation path of the FPI is checked. Time complexity of this algorithm is porportional to the product of the number of flip flops with at lest a self loop and the number of gates in the circuit. Experiments were performed on the ISCAS89 benchmark ciruits to show the feadibility of the proposed algorithm.We could identify large amount of undetectable faults(up to 50% of the number of flip-flops)in circuits with uninitializable flip-flops. Consider-ing that most of the time in test generation is cinsumed in identifying undetecatable faults, performance of test generator can be improved by using this algorithm as a pre-processing of test generation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.3
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• pp.288-300
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• 2002

In this paper, a novel method of equalization of RF transceivers is suggested for MIMO(Multiple Input Multiple Output) antenna actively studied for high speed data transmission in the recent IMT-2000 system. The core of suggestion is in equalizing the transfer characteristics of multiple transceivers using feedback and memory during the predefined calibration time. This makes it possible to weight the signals in the intermediate frequency, which is easier in the application of recently developed DoA(Direction of Arrival) algorithms. In addition, the time varying optimum cell formation according to traffic is feasible by antenna beam-forming based on the DoA information. The suggested method of equalizing multiple transceivers are successfully verified using envelope simulation. 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 convent.
nal diagnosis methods based on tests and simulation be.
me inefficient, or even more impractical. We propose a simple and easily implementable alg？ithm for detection and isolation of the multiple crosstalk-faults in OSM. Specifically, we develop an algorithm for isolation of the source fault in switc.
ng elements whenever the multiple crosstalk-faults are.
etected in OSM. The proposed algorithm is illustrated by an example of 16$\times$16 OSM.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.28-35
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• 2002

The probabilistic seismic hazard analysis for engineering needs several active fault parameters as input data. Fault slip rates, the segmentation model for each fault, and the date of the most recent large earthquake in seismic hazard analysis are the critical pieces of information required to characterize behavior of the faults. Slip rates provide a basis for calculating earthquake recurrence intervals. Segmentation models define potential rupture lengths and are inputs to earthquake magnitude. The most recent event is used in time-dependent probability calculations. These data were assembled by expert source-characterization groups consisting of geologists, geophysicists, and seismologists evaluating the information available for earth fault. The procedures to prepare inputs for seismic hazard are illustrated with possible segmentation scenarios of capable fault models and the seismic hazards are evaluated to see the implication of considering capable faults models.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.706-709
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• 1996

In this paper, an algorithm for PLC(Programmable Logic Controller) fault diagnosis system is proposed and experimentation is conducted with a PLC and a virtual plant. Wrong output backward tracking algorithm is proposed in order to find the external faults of PLC. And query with keywords of the fault systems and specially designed test sequence programs are used. We lay emphasis on the backward tracking algorithm to diagnose the faults of PLC. It is shown experimentally that the proposed algorithm can find the faults which a typical self diagnostics in the-commercially available PLC cannot.

• 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 ...

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.8
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• pp.39-48
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• 1997

The fast redundancy identification is required to perform an efficient test pattern genration. Due to the reconvergent fanouts which make the dependency among objectives and the fault propagation blocking, there may exist redundnat faults in the cirucit. This paper presents the isomorphism identification and the pseudo dominator algorithms which are useful to identify redundant faults in combinational circuits. The isomorphism identification algorithm determines whether mandatory objectives required for fault detection cannot be simultaneously satisfied from primary input assignments or not using binary decision diagrma. The pseudo dominator algorithm determines whether faults propagation is possible or not by considering all paths at a given fanout node. Several experiments using ISCAS 85 benchmark circuits demonstrate the efficiency and practicability of the algorithms.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1972-1975
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• 2002

A new test approach based on a supply current test method is proposed for testing open faults in bipolar logic circuits. In the approach, only the open faults are detected by the supply current test method, which are difficult to be detected by functional test methods. The effectiveness of the approach is examined experimentally on open fault detection in TTL combinational circuits. The results shows that higher fault coverage can be established by applying a small number of test input vectors of the supply current test method after test vectors of functional test methods based on stuck-at models.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.97-104
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• 2008

Most of engine control systems for helicopter turboshaft engines are equipped with dual sensors. For the system with dual redundancy, analytic methods are used to detect faults based on the system dynamical model. Helicopter engine dynamics are affected by aerodynamic torque induced from the dynamics of the main rotor. In this paper an engine model including the rotor dynamics is constructed for the T700-GE-700 turboshaft engine powering UH-60 helicopter. The singular value decomposition(SVD) method is applied to the developed model in order to detect sensor faults. The SVD method which do not need an additional computation to generate residual uses the characteristics that the system outputs in direction of the left singular vector if an input is applied in direction of the right singular vector. Simulations show that the SVD method works well in detecting and isolating the sensor faults.