• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.2
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• pp.115-122
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• 2007

In this paper, a novel fault detection method for fault tolerant control is proposed when the NPC inverter has a open failure in the switching device. The open fault of switching device is detected by checking the variation of a leg-voltage in the neutral-point-clamped inverter and the two phases control method is used for continuously balance the three phases voltage to the load. It can be achieve the fault tolerant control for improving the reliability of the NPC inverter by the fault detection and reconfiguration. This method has fast detection ability and a simple realization for fault detection, compared with a conventional method. Also, this fast detection ability improved the harmful effects such as DC-link voltage unbalance and overstress to other switching devices from a delay of fault detection. The proposed method has been verified by simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.669-672
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• 2012

This paper investigates an algorithm for robust fault diagnosis in robot manipulators. The TOSM (Third Order Sliding Mode observer) provides both theoretically exact observation and unknown fault identification without filtration. The EOI (Equivalent Output Injections) of the TOSM observers can be used as residuals for the problem of fault diagnosis and to identify the unknown faults. The obtained fault information can be used for fault detection, isolation as well as fault accommodation to the self-correcting failure system. The computer simulation results for a PUMA 560 robot are shown to verify the effectiveness of the proposed strategy.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.190-199
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• 2014

In the last years, fault problem in power electronics has been more and more investigated both from theoretical and practical point of view. The fault problem can cause equipment failure, data and economical losses. And the analyze system require to ensure fault problem and also rectify failures. The current errors on these faults are applied for identified type of faults. This paper presents technique to detection and identification faults in three-phase voltage source inverter (VSI) by using time-frequency distribution (TFD). TFD capable represent time frequency representation (TFR) in temporal and spectral information. Based on TFR, signal parameters are calculated such as instantaneous average current, instantaneous root mean square current, instantaneous fundamental root mean square current and, instantaneous total current waveform distortion. From on results, the detection of VSI faults could be determined based on characteristic of parameter estimation. And also concluded that the fault detection is capable of identifying the type of inverter fault and can reduce cost maintenance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.4
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• pp.287-293
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• 2002

The unexpected failure of the induction motor makes the downtime of production, and the cost of the process cessation enormous. To reduce the downtime and increase the reliability of the motor, the vibration measurements for the fault detection have been used previously. Recently motor current signature analysis(MCSA) has been adapted for the fault detection and diagnosis of the motors. MCSA provides a powerful analysis tool for detecting the presence of mechanical and electrical faults in both the motor and driven equipment. In this paper, the fault severity of the rotor bar has been derived in terms of the resistance change which is calculated from the equivalent circuit model. Results show that the fault of the rotor can be easily detected and the measured value of the resistance change is verified by the detected fault from on-site tests using MCSA for the induction motors in an iron foundry.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1406-1416
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• 2017

In complex and large-scale industries, properly designed fault detection and identification (FDI) systems considerably improve safety, reliability and availability of target processes. In thermal power plants (TPPs), generating units operate under very dangerous conditions; system failures can cause severe loss of life and property. In this paper, we propose a bagged auto-associative kernel regression (AAKR)-based FDI approach for steam boilers in TPPs. AAKR estimates new query vectors by online local modeling, and is suitable for TPPs operating under various load levels. By combining the bagging method, more stable and reliable estimations can be achieved, since the effects of random fluctuations decrease because of ensemble averaging. To validate performance, the proposed method and comparison methods (i.e., a clustering-based method and principal component analysis) are applied to failure data due to water wall tube leakage gathered from a 250 MW coal-fired TPP. Experimental results show that the proposed method fulfills reasonable false alarm rates and, at the same time, achieves better fault detection performance than the comparison methods. After performing fault detection, contribution analysis is carried out to identify fault variables; this helps operators to confirm the types of faults and efficiently take preventive actions.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1439-1444
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• 2005

Induction motors are the most commonly used electrical drives because they are rugged, mechanically simple, adaptable to widely different operating conditions, and simple to control. The most common faults in squirrel-cage induction motors are bearing, stator and rotor faults. Surveys conducted by the IEEE and EPRI show that the most common fault in induction motor is bearing failure (${\sim}$40% of failure). Thence, this paper addresses experimental results for diagnosing faults with different rolling element bearing damage via motor current spectral analysis. Rolling element bearings generally consist of two rings, an inner and outer, between which a set of balls or rollers rotate in raceways. We set the experimental test bed to detect the rolling-element bearing misalignment of 3 type induction motors with normal condition bearing system, shaft deflection system by external force and a hole drilled through the outer race of the shaft end bearing of the four pole test motor. This paper takes the initial step of investigating the efficacy of current monitoring for bearing fault detection by incipient bearing failure. The failure modes are reviewed and the characteristics of bearing frequency associated with the physical construction of the bearings are defined. The effects on the stator current spectrum are described and related frequencies are also determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. We utilized the FFT, Wavelet analysis and averaging signal pattern by inner product tool to analyze stator current components. The test results clearly illustrate that the stator signature can be used to identify the presence of a bearing fault.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.822-829
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• 2022

According to existing study into the remote fault diagnosis procedure, the current diagnostic approach has an imperfect decision model, which only supports communication in a close distance. An Internet of Things (IoT)-based remote fault diagnostic approach for wind power equipment is created to address this issue and expand the communication distance of fault diagnosis. Specifically, a decision model for active power coordination is built with the mechanical energy storage of power generation equipment with a remote diagnosis mode set by decision tree algorithms. These models help calculate the failure frequency of bearings in power generation equipment, summarize the characteristics of failure types and detect the operation status of wind power equipment through IoT. In addition, they can also generate the point inspection data and evaluate the equipment status. The findings demonstrate that the average communication distances of the designed remote diagnosis method and the other two remote diagnosis methods are 587.46 m, 435.61 m, and 454.32 m, respectively, indicating its application value.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.2
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• pp.199-204
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• 2013

Recently, the demand for fuel efficient electric vehicles (EVs) and hybrid electric vehicles (HEVs) has been growing globally. Due to the increased number of switching devices in the electrified vehicles, the probability of the semiconductor device failure is much higher than in other application areas. A sudden failure in one of the power switches and insufficient power management ability in the systems not only decreases system performance, but also leads to critical safety problems. In this paper, novel switch open circuit fault detection method is proposed, and the proposed approach is verified by experiments.

• Proceedings of the KSR Conference
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• 2000.05a
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• pp.336-343
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• 2000

This paper proposes the failsafe control logic. which has applied to the voting on the TMR system by using FPGA The self-detection circuit is also designed for detecting a characteristic of fault at TMR system. The fault producing in the self-detection system is largely classified among an intermittent fault, a transient fault and a permanent fault. If it is happened to the permanent fault, the system can be failed. Therefore, it is designed the logic circuit which is not transferred the permanent fault to the system after shut off output. The control logic of the Fail Safe proposed in the paper is required for a circuit integrate of device to minimize the failure happened. Therefore, it makes to design FPGA with modeling of VHDL. The circuit of the Fail Safe of TMR system is able to apply to nuclear system, rail-way system, aerospace and aircraft system which is required for high reliability.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.2
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• pp.189-197
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• 2024

Galileo is a European Global Navigation Satellite System (GNSS) that has offered the Galileo Open Service since 2016. Consequently, the standardization of GNSS augmentation systems, such as Satellite Based Augmentation System (SBAS), Ground Based Augmentation System (GBAS), and Aircraft Based Augmentation System (ABAS) for Galileo signals, is ongoing. In 2023, the European Union Space Programme Agency (EUSPA) released prior probabilities of a satellite fault and a constellation fault for Galileo, which are 3×10^-5 and 2×10^-4 per hour, respectively. In particular, the prior probability of a Galileo constellation fault is significantly higher than that for the GPS constellation fault, which is defined as 1×10^-8 per hour. This raised concerns about its potential impact on GBAS integrity monitoring. According to the Global Positioning System (GPS) Standard Positioning Service Performance Standard (SPS PS), a constellation fault is classified as a wide fault. A wide fault refers to a fault that affects more than two satellites due to a common cause. Such a fault can be caused by a failure in the Earth Orientation Parameter (EOP). The EOP is used when transforming the inertial axis, on which the orbit determination is based, to Earth Centered Earth Fixed (ECEF) axis, accounting for the irregularities in the rotation of the Earth. Therefore, a faulty EOP can introduce errors when computing a satellite position with respect to the ECEF axis. In GNSS, the ephemeris parameters are estimated based on the positions of satellites and are transmitted to navigation satellites. Subsequently, these ephemeris parameters are broadcasted via the navigation message to users. Therefore, a faulty EOP results in erroneous broadcast ephemeris data. In this paper, we assess the conventional ephemeris fault detection monitor currently employed in GBAS for wide faults, as current GBAS considers only single failure cases. In addition to the existing requirements defined in the standards on the Probability of Missed Detection (PMD), we derive a new PMD requirement tailored for a wide fault. The compliance of the current ephemeris monitor to the derived requirement is evaluated through a simulation. Our findings confirm that the conventional monitor meets the requirement even for wide fault scenarios.