• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.46-48
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• 2007

This paper presents research about improvement of fault detection algorithm in FRTU on the feeder of distribution system. FRTU(Feeder Remote Terminal Unit) is applied to fault detection schemes for phase fault, ground fault, and cold load pickup and Inrush restraint functions distinguish the fault current and the normal load current. FRTU is occurred FI(Fault Indicator) when current is over pick-up value also inrush current is occurred FRTU indicate FI. Discrete wavelet transform(DWT) analysis gives the frequency and time-scale information. The neural network system as a fault detector was trained to discriminate inrush current from the fault status by a gradient descent method. In this paper, fault detection is improved using voltage monitoring system with DWT and neural network. These data were measured in actual 22.9kV distribution system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2306-2313
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• 2010

This paper describes a model based fault detection algorithm for an Advanced ESC System which consists of Hydraulic Control Unit (HCU) with built-in wheel pressure sensors. Advanced ESC System can be used for various value-added functions such as Stop & Go Function and Regenerative Brake Function. Therefore, HCU must have a reliable fault detection. Due to the huge amount of sensor signals, existing specific sensor based fault detection of HCU cannot guarantee the safety of vehicle. However, proposed algorithm dose not require the sensors. When model based fault detection algorithm detects severe failures of the HCU, it warns the driver in advance to prevent accidents due to the failures. For this purpose, a mathematical model is developed and validated in comparison to actual data. Simulation results and data acquired from an actual system are compared with each other to obtain the information needed for the fault detection process.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2169-2178
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• 2000

This paper proposes the structure of an agent and rules for fault detection and location on LAN. To find out a reason of critical fault incurred LAN, collision detection rule, error detection rule, broadcast detection rule, system location rule, and Internet application location rule ar shown. Also, the structure of multi-agent system and state transition diagram is portrayed to have connectivity with he set of rules. To verify availability of proposed rules, the process to find a faulty system is shown by monitoring and analyzing the LAN fault occurrences from the proposed set of rules. Such an rule based agent system is helpful to an Internet manager to solve a reason of fault and make ad decision from gathering management information.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.4
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• pp.409-416
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• 2000

In case of operating two converters in parallel with ZCT operation method using one current sensor for fault tolerance by system characteristics, identifying fault detection and isolation is difficult of which converter is fault since the ZCT output is a difference of two converters' supply current when a converter has fault. This thesis suggest a fault detection and isolation method of converter in case of operating two converters in parallel for fault tolerant system and verified this suggested method through an experiment.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.3 s.18
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• pp.140-148
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• 2004

Fault detection and isolation(FDI) and reconfigurable flight control system provide better survivability even though actuator faults occur. In this study, a new fault detection and isolation algorithm is proposed using fuzzy logic. When the FDI system detects the actuator fault, the fuzzy logic investigates the state variables to find which actuator has fault. Proposed fuzzy detection algorithm detect not only a single fault but also multiple faults. After detecting the fault, the reconfigurable flight control system begins operating for compensating the effects of the fault. A numerical simulation using six degree-of-freedom nonlinear aircraft model is performed to verity the performance of the proposed fault detection and isolation scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.974-977
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• 2003

The GPS/INS integration system navigation can provide improved navigation performance and has been widely used as a main navigation system for military and commercial vehicles. When two navigation systems are tightly coupled and the structure is complicated, a fault in either the GPS or the INS can lead to a disastrous failure of the whole integration system. This paper proposes a real-time fault detection method for an AGPS/INS integration system. The proposed fault detection method comprises a BIT and a fault detection algorithm based on chi-square test. It is implemented by real-time software modules to apply the AGPS/INS integration system and van test is carried out to evaluate its performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.4
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• pp.8-17
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• 2010

In this paper, a fault tolerant control against sensor faults of electric parking brake (EPB) is proposed. Fault tolerant control method of EPB system is strongly demanded since sensor faults can endanger a driver's safety. In this paper, a clamp force estimation method is presented using motor's armature current and angular velocity. Clamp force estimation method is applied for fault detection method with parity equations. The goal of the detection method is to detect and identify faults in encoder, current sensor, force sensor, and parking cable. And a switching logic for fault tolerant control against the three sensor faults is suggested. Experimental results show that the proposed force estimation method satisfies the specifications of EPB system. The effectiveness of the fault detection method is validated with experimental results. Although a single sensor fault happens, EPB system with the proposed fault detection method does not develop into a failure on subsystem or system level.

• Journal of IKEEE
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• v.25 no.2
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• pp.330-336
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• 2021

A typical way to reduce the number of hardware redundancy configurations is to implement them as analytical techniques for detecting, identifying and accepting failures with micro-controller. In this paper, one of the analytical techniques, the fault detection filter, is applied to aircraft turbofan engine system. The fault detection filter is a special type of observer that has the advantage of being able to determine the location of failures by maintaining a constant direction in the output space in the event of a particular failure. We present a single input/output dynamic system modeling of air turbine system in turbofan engine, a fault detection filter design, and simulation results applying it. Simulation results show that fault detection can be effectively applied as a sensitivity effect to the directionality of the detection filter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.419-424
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• 2011

The system-on-board detectable and controllable the electrical fires due to ground fault(GF), arc fault and overload is implemented. The system IC for controlling and preventing the electrical fires is available to this system. The GF detection circuit for detecting the electrical leakage current, the arc fault detection circuit and the overload detection circuit controllable the input voltage for flowing the overload current are designed. The GF detection circuit and the arc fault detection circuit are good operated to the electrical leakage current and the arc signal, respectively. It is confirmed that the overload detection circuit has shown no erratic operation with the noise or the load variation and is only operated at the overload condition.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.2
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• pp.125-133
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• 2022

This paper proposes a fault detection method for a Unmanned Surface Vehicle (USV) with overactuated system. Current status information for fault detection is expressed as a scalogram image. The scalogram image is obtained by wavelet-transforming the USV's control input and sensor information. The fault detection scheme is based on Convolutional Neural Network (CNN) algorithm. The previously generated scalogram data was transferred learning to GoogLeNet algorithm. The data are generated as scalogram images in real time, and fault is detected through a learning model. The result of fault detection is very robust and highly accurate.