• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.93-94
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• 2011

This paper analyzes the shaft torsion of a doubly-fed induction generator (DFIG) for a wind farm collector system fault. When a fault occurs, the active power of the DFIG cannot be transmitted to the grid and thus accelerates the rotation of both the blade and the rotor. Due to the different inertia of these, the angle of deviation fluctuates and the shaft torsion is occurred. This becomes much severe when the rotational speed of the blade exceeds a threshold, which activating the pitch control to reduce the mechanical power. The torque, which can be sixty times larger than that in the steady state, may destroy the shaft. The shaft torsion phenomena are simulated using the EMTP-RV simulator. The results indicate that when a wind farm collector system fault occurs, a severe shaft torsion is occurred due to the activation of the pitch control.

• Journal of Power Electronics
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• v.14 no.5
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• pp.859-865
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• 2014

This study presents an electromagnetic model for predicting shaft voltages in a 2-pole field-excited synchronous generator. After the first observations on shaft voltages were made more than a century ago, extensive work has been conducted on eliminating, mitigating, and integrating the aforementioned phenomena. Given that emphasis has been placed on modeling shaft- and bearing-induced voltages in AC motors driven by variable frequency drives, similar efforts toward a model that is dedicated to generators are insubstantial. This work endeavors to improve current physical interpretation and prediction methods for shaft-induced voltages in generators through semi-analytical derivation. Aside from the experimental validation of the model, investigations regarding the behavior of shaft voltages under varying machine complexities and operating conditions clarify previous uncertainties regarding these phenomena. The performance of the numerical method is also assessed for application in eccentricity fault diagnosis.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.126-131
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• 2005

This paper presents experimental results by using the machinery fault simulator which is monitoring its conditions with an acceleration signal. Components of the machinery, for example, motor, belt pulley, belt, bearing, and gear, with artificial defects were used for the experiment.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.74-81
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• 2004

In this study, static end loading tests with load transfer measurement were accomplished for large diameter drilled shaft constructed in fault zone. Yield pile capacity (or ultimate pile capacity) from load-settlement curve was determined and axial load transfer behavior was measurd. The end bearing capacity was increased 2 times due to grouting the toe ground under pile base.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.2
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• pp.185-190
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• 2010

Condition monitoring(CM) is a method based on non-destructive test(NDT). So, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days because of high sensitivity than common accelerometers and detectable low energy vibration signals. And crack is considered one of severe fault in the rotating machine. Therefore, in this paper, study on early detection using AE has been accomplished for the crack of the low-speed shaft. There is a seeded initial crack on the shaft then the AE signal had been measured with low-speed rotation as the applied load condition. The signal detected from crack in rotating machine was detected by the AE transducer then the trend of crack growth had found out by using some of feature values such as peak value, skewness, kurtosis, crest factor, frequency center value(FC), variance frequency value(VF) and so on.

• Journal of the Korean Geotechnical Society
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• v.20 no.5
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• pp.135-143
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• 2004

In the land section of marine bridge construction site, to confirm the end bearing of large diameter drilled shaft constructed in the fault zone which was discovered unexpectedly, the hi-directional end loading tests were performed. The objectives of this study are to confirm the end bearing of the pile constructed in fault zone and the increasing effect of end bearing after grouting the base ground beneath the pile toe. After grouting the pile base ground, the settlement of pile base decreased considerably and the pile base resistance increased more than twice.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.24-30
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• 2000

The aim of this paper is to describe an advanced method of the fault diagnosis using Control Theory with reference to a crack detection, a new way to localize the crack position under influence of the plant disturbance and white measurement noise on a rotating shaft. As the first step, the shaft is physically modelled with a finite element method as usual and the dynamic mathematical model is derived from it using the Hamilton-principle and in this way the system is modelled by various subsystems. The equations of motions with a crack are established by the adaption of the local stiffness change through breathing and gaping[1] from the crack to the equation of motion with an undamaged shaft. This is supposed to be regarded as a reference system for the given system. Based on the fictitious model of the time behaviour induced from vibration phenomena measured at the bearings, a nonlinear state observer is designed in order to detect the crack on the shaft. This is the elementary NL-observer(EOB). Using the elementary observer, an Estimator(Observer Bank) is established and arranged at the certain position on the shaft. In case, a crack is found and its position is known, the procedure, fro the estimation of the depth is going to begin.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.301-307
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• 1998

The goal of this paper is to describe an advanced method of the fault diagnois using Control Theory with reference to a crack detection, a new way to localize the crack position under infulence of the plant disturbance and white measurement noise on a rotating shaft. As a first step, the shaft is physically modelled with a finite element method as usual and the dynamic mathematical model is derived from it using the Hamilton - principle and in this way the system is modelled by various subsystems. The equations of motion with crack is established by adaption of the local stiffness change through breathing and gaping from the crack to the equation of motion with un-damaged shaft. This is supposed to be regarded as reference for the given system. Based on the fictitious model of the time behaviour induced from vibration phenomena measured at the bearings, a nonlinear State Observer is designed in order to detect the crack on the shaft. This is elementary NL- observer(EOB). Using the elementary observer, an Estimator(Observer) Bank is established and arranged at the certain position on the shaft. In case a crack is found and its position is known, the procedure for the estimation of the depth is going to begin.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.11a
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• pp.192-195
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• 2008

A sensor fault detection method for small turbo shaft engine considering multiple trim conditions is proposed. This engine is used in a helicopter. Firstly, under multiple trim conditions, we derive the linearized models from a nonlinear model which includes engine, rotor and feedback control loop. As a fault detection method, we adopt the Kalman filter based method. To keep continuity of estimates between the changes of trim conditions, we reconfigure the initial values of state variables at trim changes. We detect the faults with two steps that when the first filter does not alarm the faults for some sensors, the second filter is runned for other sensor. Via some simulations we show that the proposed method works well under multiple trim conditions.