• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1109-1114
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• 1992

Modern chemical processes are becoming more complicated. The sophisticated chemical processes have needed the fault diagnosis pxpert systems that can detect and diagnose the fault diagnosis expert systems that can detect and diagnose the faults of some processes and give and advice to the operator in the event of process faults. We present the Time-Delay Neural Network(TDNN) approach for on-line fautl diagnosis. The on-line fault diagnosis system finds the exact origin of the fault of which the symptom is propagated continuously with time. The proposed method has been applied to a pilot distillation column to show the merits and applicability of the TDNN.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.3
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• pp.176-186
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• 1996

As the density of VLSI increases, the conventional logic testing is not sufficient to completely detect the new faults generated in design and fabrication processing. Recently, IDDQ testing becomes very attractive since it can overcome the limitations of logic testing. In this paper, G-ATPG (gyeongsang automatic test pattern genrator) is designed which is able to be adapted to IDDQ testing for combinational CMOS VLSI. In G-ATPG, stuck-at, transistor stuck-on, GOS (gate oxide short)or bridging faults which can occur within priitive gate or XOR is modelled to primitive fault patterns and the concept of a fault-sensitizing gate is used to simulate only gates that need to sensitize the faulty gate because IDDQ test does not require the process of fault propagation. Primitive fault patterns are graded to reduce CPU time for the gates in a circuit whenever a test pattern is generated. the simulation results in bench mark circuits show that CPU time and fault coverage are enhanced more than the conventional ATPG using IDDQ test.

• 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.

• ETRI Journal
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• v.30 no.4
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• pp.555-564
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• 2008

This paper proposes a test algorithm that can detect and diagnose all the faults occurring in dual-port memories that can be accessed simultaneously through two ports. In this paper, we develop a new diagnosis algorithm that classifies faults in detail when they are detected while the test process is being developed. The algorithm is particularly efficient because it uses information that can be obtained by test results as well as results using an additional diagnosis pattern. The algorithm can also diagnose various fault models for dual-port memories.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.927-930
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• 2005

ACSR is a timed process algebra for the specification and analysis of real-time systems, which supports synchronous timed actions and asynchronous instantaneous events. PACSR is an extended ACSR with the notion of probabilities in selection operation. Using PACSR, this paper represents a system fault occurrence and recovery from the fault in the general resource alteration system. The result shows that system fault occurrence can be analyzed from the fault occurrence probability and the recovery probability.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.640-641
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• 2007

In this paper, the discrete wavelet transform (DWT) was applied a fault detection of a synchronous generator being superior to a transient state signal analysis and being easy to real time realization. The fault signals after executing a terminal fault modeling collect using a MATLAB package, and calculate the wavelet coefficients through the process of a multi-level decomposition (MLD). The proposed algorithm of a fault detection of a generator using Daubechies WT (wavelet transform) was executed with a C language for the commend line function and for the real time realization after analyzing MATLAB's graphical interface.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.1093-1096
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• 2004

Bearings are elementary machinery component which loads and do rotating motion. Excessive loads or many other reasons can cause incipient faults to be created and grown in each component. Moreover, it happens that incipient faults which were caused by manufacturing or assembling process' errors of the bearings are created. Finding the incipient faults as early as possible is necessary to the bearings in severe condition: high speed or frequently varying load condition, etc. How early we can detect the faults has to do with how the detection algorithm finds the fault information from measured signal. Fortunately, the bearing fault signal makes periodic impulse train. This information allows us to find the faults regardless how much noise contaminates the signal. This paper shows the basic signal processing idea and experimental results that demonstrate how good the method is.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.870-881
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• 2020

Because SCADA monitoring data of wind turbines are large and fast changing, the unbalanced proportion of data in various working conditions makes it difficult to process fault feature data. The existing methods mainly introduce new and non-repeating instances by interpolating adjacent minority samples. In order to overcome the shortcomings of these methods which does not consider boundary conditions in balancing data, an improved over-sampling balancing algorithm SC-SMOTE (safe circle synthetic minority oversampling technology) is proposed to optimize data sets. Then, for the balanced data sets, a fault diagnosis method based on improved k-nearest neighbors (kNN) classification for wind turbine blade icing is adopted. Compared with the SMOTE algorithm, the experimental results show that the method is effective in the diagnosis of fan blade icing fault and improves the accuracy of diagnosis.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1486-1495
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• 2019

Dealing with the DC link fault poses a technical problem for an HVDC based on a modular multilevel converter. The fault suppressing mechanisms of several sub-module topologies with DC fault current blocking capacity are examined in this paper. An improved half-bridge sub-module topology with double direction control switch is also designed to address the additional power consumption problem, and a sub-module topology called hybrid double direction blocking sub module (HDDBSM) is proposed. The DC fault suppression characteristics and sub-module capacitor voltage balance problem is also analyzed, and a self-startup method is designed according to the number of capacitors. The simulation model in PSCAD/EMTDC is built to verify the self-startup process and the DC link fault suppression features.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.4 no.3
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• pp.57-62
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• 2005

Neural networks, which have learning and self-organizing abilities, can be advantageously used in the pattern recognition. Neural network techniques have been widely used in monitoring and diagnosis, and compare favourable with traditional statistical pattern recognition algorithms, heuristic rule-based approaches, and fuzzy logic approaches. In this study the fault diagnosis of the face-milling using the artificial neural network was investigated. After training, the sample which measure load current was monitored by constant output results.