• Korean Journal of Computational Design and Engineering
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• v.18 no.4
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• pp.250-257
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• 2013

This paper introduces a failure analysis procedure that underpins real-time fault prognosis. In the previous study, we developed a systematic eventization procedure which makes it possible to reduce the original data size into a manageable one in the form of event logs and eventually to extract failure patterns efficiently from the reduced data. Failure patterns are then extracted in the form of event sequences by sequence-mining algorithms, (e.g. FP-Tree algorithm). Extracted patterns are stored in a failure pattern library, and eventually, we use the stored failure pattern information to predict potential failures. The two practical case studies (marine diesel engine and SIRIUS-II car engine) provide empirical support for the performance of the proposed failure analysis procedure. This procedure can be easily extended for wide application fields of failure analysis such as vehicle and machine diagnostics. Furthermore, it can be applied to human health monitoring & prognosis, so that human body signals could be efficiently analyzed.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.7
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• pp.679-686
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• 2013

The reduction unit is one of the most important components in railway cars, due to the transmission of torque from the motor to the wheels. Faulty reduction gears in high-speed trains result from excessive wear on the gear or damage to the gear. These types of gear defects have a significant effect on high-speed rail operation and safety; thus, a diagnosis system for the reduction unit is needed. Vibration diagnosis technology is one of the most effective diagnostics. In this paper, the vibration parameters of a reduction unit were evaluated during a driving-gear test and a full-vehicle test, using kurtosis and the crest factor. These tests were performed under normal operating conditions; a specimen tester was used to diagnose problems in defective gears.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.215-220
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• 2013

Recently, death number of heart attack in the world is increasing rapidly. Therefore, to solve these problem, it is trend that is making mandatory automatic defibrillator AED establishment to airport, school, at home. However, AED use in an emergency or equipment failure caused malfunctions if equipped with AED may even become obsolete. In this paper, in order to improve this problem, AED Simulator using the fuzzy simulation technique in comparison to existing methods Tilt ambient temperature conditions and in consideration of the conditions, self-diagnostics, error detection at the time to determine whether the development of intelligent simulation. Moreover, in this paper, it proved that fuzzy AED Simulation improved fault detection probability results 30% more than conventional method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.115-120
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• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.

• Smart Structures and Systems
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• v.4 no.4
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• pp.429-438
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• 2008

The aim of this paper is to define the required measurements and processing tools necessary for developing a maintenance approach applied to rotating machines in the presence of multiple faults. The system responses measured were accelerations and transmission errors. Acceleration measurements provide most of the information on bearing conditions, while transmission error measurements provide pertinent information on gear conditions. The measurements were carried out for several operating conditions (loads and speeds). System responses were processed in several analyzing domains (Time, Spectrum, and Cepstrum domains). The approach developed enables the detection and identification of combined faults and it can be applied to other types of rotating machines once the critical elements and their associated faults have been defined.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.61-66
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• 1992

In this paper, a method for implementing software for the control system with dual structure in processor module is proposed and implemented to enhance its reliability. In this implementation the multi-tasking function which is provided by a real-time operating system is applied. The overall softwre is divided into five tasks and is performed in each of the dual processor module, independently. By this, the processor module with dual structure can achieve a control objective and fault diagnostics effectively. An experimental result shows that the backup processor module can be substituted for the primary processor module immediately when it happens to fail, because data relating the failure information are exchanged continuously done via shared memories.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.244-250
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• 1997

The mean time to failure (MTTF) expressing the mean value of the system life is a measure of system effectiveness. To estimate the remaining life of component and/or system, the dynamic mean time to failure concept is suggested. It is the time-dependent Property depending on the status of components. The Kalman filter is used to estimate the reliability of components using the on-line information (directly measured sensor output or device-specific diagnostics in the intelligent sensor) in form of the numerical value (state factor). This factor considers the persistency of the fault condition and confidence level in measurement. If there is a complex system with many components, each calculated reliability's or components are combined, which results in the dynamic MTTF or system. The illustrative examples are discussed. The results show that the dynamic MTTF can well express the component and system failure behaviour whether any kinds of failure are occurred or not.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.643-646
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• 2005

The paper discusses the main problems in induction motor diagnosis by motor current and vibration signals, possible faults and effects produced by these faults in the signal spectrums. Decision Tree is introduced as a tool to diagnose the motor status, this expert system is implemented to detect the incipient defects, supervise and predict them, and plan the maintenance of the motor.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.05a
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• pp.403-405
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• 1999

Power transformers have a tendency of ultra-high voltage and huge capacity as power demand increases day after day. Therefore, the fault by insulation destruction gives rise to large area of power failure in huge capacity transformers. On-line predictive diagnostics is very important In power transformers because of economic loss and its spreading effect. Hence, this study presents experiments of partial discharge method using ultrasonic sensor in order to confirm the possibility of ultrasonic sensor in power transformers. It carries out the experiments of measuring delay time between ultrasonic sensor and transducer, sensitiities by temperature change of oil and by barriers inside transformers. It is also Included wave analysis by ultrasonic sensor for needle-plate electrode powered on through high-voltage equipments.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1903-1905
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• 2000

Power transformers have a tendency of ultra-high voltage capacity as power demand increases day after day KEPCO also will have plan to supply transmission power from 345KV to 765KV in the early of 2000. Therefore, the fault by insulation destruction gives rise to large area of power failure in huge capacity transformers. On-line predictive diagnostics is very important in power transformers because of economic loss and its spreading effect. This study presents the algorithm for transformer oil analysis used KEPCO code, IEC code, gas pattern method and Dornenburg & Roger Ratio method. We also describe the MMI display of expert system programmed by Element Expert Tool(Neuron Data Inc.).