• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4A
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• pp.379-386
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• 2007

In this paper, we propose an efficient diagnosis algorithm for multiple stuck-at faults. Because of using vectorwise intersections as an important metric of diagnosis, the proposed diagnosis algorithm can diagnose multiple defects in single stuck-at fault simulator. In spite of multiple fault diagnosis, the number of candidate faults is drastically reduced. For identifying faults, the variable weight, positive calculations and negative calculations are used for the matching algorithm. To verify our algorithm, experiments were performed for ISCAS85 and full-scan version of ISCAS89 benchmark circuits.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.121-124
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• 2003

The conventional CNC(Computerized Numerical Controller) of machine tool, which is dependent to CNC maker, was a closed architecture type. Therefore, it is impossible to implement a special user-define function to CNC. But recently, CNC is changed to OAC(Open Architecture Controller) type increasingly and the general function of CNC can be upgrade efficiently. This paper describes web service application for remote monitoring regarding the faults or machine tool with open architecture CNC. The major faults of CNC machine tool can be defined to the operational faults to be charged over 70%. Those faults are unpredictable because of being occurred without any warning. To generalize the fault diagnosis efficiently. two diagnosis models such as SF(Switching Function) and SSF(Step Switching Function) are proposed and the function of fault diagnosis is implemented to internal function of OAC. Also, to service remotely the faults of CNC machine tool. the suitable web environment is proposed and practical function is programmed to evaluate its operation on web.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1657-1662
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• 2017

Rotor bar faults in induction machines, which are a part of main distribution of power system, can even stop the entire system by causing contact between a stator and a rotor. There are two methods of diagnosing rotor bar faults in induction motors, online and offline tests, and existing diagnosis methods have many limitations which can lead to misdiagnosis. This paper proposes a potable rotor bar faults diagnosis system based on single phase rotation test, one of offline test methods, which detects rotor bar faults through impedance interpretation by exciting AC current in a stator winding. The test was conducted on a motor of 0.4kW in the laboratory and a motor of 1500kW in industry field.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.244-251
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• 1997

In this paper, we propose a fault diagnosis algorithm to detect and isolate multiple faults in a system. The proposed fault diagnosis algorithm is based on a multiple fault classifier which consists of two ART2 NN(adaptive resonance theory2 neural network) modules and the algorithm is composed of three main parts - parameter estimation, fault detection and isolation. When a change in the system occurs, estimated parameters go through a transition zone in which residuals between the system output and the estimated output cross the threshold, and in this zone, estimated parameters are transferred to the multiple faults classifier for fault isolation. From the computer simulation results, it is verified that when the proposed diagnosis algorithm is performed successfully, it detects and isolates faults in the position control system of a DC motor.

• Journal of Mechanical Science and Technology
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• v.19 no.5
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• pp.1095-1106
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• 2005

Recently, the conventional controller of machine-tool has been increasingly replaced by the PC-based open architecture controller, which is independent of the CNC vendor and on which it is possible to implement user-defined application programs. This paper proposes CNC­implemented fault diagnosis and web-based remote services for machine-tool with open architecture CNC. The faults of CNC machine-tool are defined as the operational faults occupied by over $70{\%}$ of all faults. The operational faults are unpredictable as they occur without any warning. Two diagnostic models, the switching function and the step switching function, were proposed in order to diagnose faults efficiently. The faults were automatically diagnosed through the fault diagnosis system using the two diagnostic models. A suitable interface environment between CNC and developed application modules was constructed for the internal function of CNC. In addition, a suitable web environment was constructed for remote services. The web service functions, such as remote monitoring and remote control, were implemented, and their operability was tested through the web. The results obtained through this research could be a model of fault diagnosis and remote servicing for machine-tool with open architecture CNC.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.154-157
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• 2003

In order for testing faults of combinatorial logic circuit, the authors have developed a new diagnosis method: "Neural Network (NN) fault diagnosis", based on fm error back propagation functions. This method has proved the capability to test gate faults of wider range including so called SSA (single stuck-at) faults, without assuming neither any set of test data nor diagnosis dictionaries. In this paper, it is further shown that what kind of fault models can be detected in the NN fault diagnosis, and the simply modified one can extend to test delay faults, e.g. logic hazard as long as the delays are confined to those due to gates, not to signal lines.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.233-238
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• 2000

CNC machine tool is assembled by central processor, PLC(Programmable Logic Controller), and actuator. The sequential control of machine generally controlled by a PLC. The main fault occured at PLC in 3 control parts. In LC faults, operational fault is charged over 70%. This paper describes diagnosis model and data processing for remote monitoring and diagnosis system in machine tools with open architecture controller. Two diagnostic models based on the ladder diagram. Logical Diagnosis Model(LDM), Sequential Diagnosis Model(SDM), are proposed. Data processing structure is proposed ST(Structured Text) based on IEC1131-3. The faults from CNC are received message form open architecture controller and faults from PLC are gathered by sequential data.. To do this, CNC and PLC's logical and sequential data is constructed database.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.88-94
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• 2007

This study deals with on-line fault detection and diagnosis for heat exchanger of variable speed refrigeration system. Conventional studies about fault of heat exchanger in refrigeration system have used temperature and pressure information. The temperature and pressure are able to be used valuably for faults detection of constant speed refrigeration system. However in case of variable speed refrigeration system, the temperature and pressure are no longer useful information for fault detection due to compensation effect of feedback controller. While current information is possible to detect faults of variable speed refrigeration system. The current information was detected in an inverter, it was used after transforming rms value. The faults of variable speed refrigeration system are divided into electrical faults and mechanical faults. We performed fault detection and diagnosis about heat exchanger among mechanical faults such as condenser fouling and evaporator fan fouling through some experiments.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.801-803
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• 2003

Faults in induction motors can be categorized into mechanical faults and electrical faults, and most mechanical faults result from inferiority or damage of the bearing, while most electrical faults derive from insulation faults of stator windings and rotor bar cracks. When a crack appears on the rotor bar, its efficiency decreases, which increases energy consumption and temperature, reducing the life span of the motor. This kind of fault can only be sensed by the protection relay after the condition has worsened to a certain degree, bringing massive economic loss. This paper will deal with the diagnosis method of rotor bar faults through the load current analysis method of the motor used during operation.