• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.26 no.2
• /
• pp.51-60
• /
• 2012

An improved method for detecting fault distance in overhead transmission lines is described in this paper. Based on single-ended measurement, propagation theory of traveling waves together with the wavelet transform technique is used. In estimating fault location, a simple, but fundamental method using the time difference between the two consecutive peaks of transient signals is considered; however, a new method to enhance measurement sensitivity and its accuracy is sought. The algorithm is developed based on the lattice diagram for traveling waves. Representing both the ground mode and alpha mode of traveling waves, in a lattice diagram, several relationships to enhance recognition rate or estimation accuracy for fault location can be found. For various cases with fault types, fault locations, and fault inception angles, fault resistances are examined using the proposed algorithm on a typical transmission line configuration. As a result, it is shown that the proposed system can be used effectively to detect fault distance.

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

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.7
• /
• pp.1200-1207
• /
• 2008

In this paper, a novel fault detection method is proposed when the neutral-point-clamped inverter has a open-circuit fault in the switching device. This proposed method is configured with simple circuit and is achieved by a simple algorithm using the inherent characteristic of the continuous Pulse Width Modulation. Also, this method has the fast fault detection ability and is much simpler to embody, in comparison with conventional fault detection methods. This ability to detect fault minimizes harmful effect which are such as DC-link voltage unbalance and overstress to other switching devices. Therefore, this proposed fault detection method can improve reliability of NPC inverter system. Experimental results are presented to verify the validity of proposed fault detection method.

• Proceedings of the KIEE Conference
• /
• 1999.11b
• /
• pp.282-284
• /
• 1999

This paper presents an accurate algorithm for fault location of a single phase to earth fault on a two-parallel transmission line using only one-terminal data. It is impossible to calculate the accurate fault distance, because of the unknown fault resistance and fault current at the fault point. The faulted line circuit and the zero-sequence circuit of two-parallel line are used as a fault location model, which the source impedance of the remote end is not involved. The algorithm can eliminate the effect of load flow and the fault resistance in calculating the fault location.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.3
• /
• pp.173-180
• /
• 2016

Fault detection and diagnosis is a task to monitor the occurrence of faults and pinpoint the exact location of faults in the system. Fault detection and diagnosis is gaining importance in development of efficient, advanced and safe industrial systems. Three phase inverter is one of the most common and excessively used power electronic system in industries. A fault diagnosis system is essential for safe and efficient usage of these inverters. This paper presents a fault detection technique and fault classification algorithm. A new feature extraction approach is proposed by using three-phase load current in three-dimensional space and neural network is used to diagnose the fault. Neural network is responsible of pinpointing the fault location. Proposed method and experiment results are presented in detail.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.5
• /
• pp.1754-1763
• /
• 2017

This paper analyses the characteristics of incomplete-journey double-circuit transmission lines on the same tower formed by single-circuit lines and double-circuit lines, and then presents a fault location algorithm based on identification of fault branch. With the relationship between the three-phase system and the double-circuit line system, a phase-mode transformation matrix for double-circuit lines can be derived. Based on the derived matrix, the double-circuit lines with faults can be decoupled, and then the fault location for an incomplete-journey double-circuit line is achieved by using modal components in the mode domain. The algorithm is divided into two steps. Firstly, the fault branch is identified by comparing the relationships of voltage amplitudes at the bonding point. Then the fault location, on the basis of the identification result, is calculated by using a two-terminal method, and only the fault distance of the actual fault branch can be obtained. There is no limit on synchronization of each terminal sampling data. The results of ATP-EMTP simulation show that the proposed algorithm can be applied within the entire line and can accurately locate faults in different fault types, fault resistances, and fault distances.

• Journal of the Korean Society of Safety
• /
• v.19 no.1
• /
• pp.23-30
• /
• 2004

Modern production systems are very complex by request of automation, and failure modes that occur in thisautomatic system are very various and complex. The efficient fault diagnosis for these complex systems is essential for productivity loss prevention and cost saving. Traditional fault diagnostic system which perforns sequential fault diagnosis can cause catastrophic failure during diagnosis when fault propagation is very fast. This paper describes the Real-time Intelligent Multiple Fault Diagnosis System (RIMFDS). RIMFDS assesses current machine condition by using sensor signals. This system deals with multiple fault diagnosis, comprising of two main parts. One is a personal computer for remote signal generation and transmission and the other is a host system for multiple fault diagnosis. The signal generator generates various faulty signals and image information and sends them to the host. The host has various modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault diagnosis and graphic representation of the results. RIMFDS diagnoses multiple faults with fast fault propagation and complex physical phenomenon. The new system based on multiprocessing diagnoses by using Hierarchical Artificial Neural Network (HANN).

• KIEE International Transactions on Power Engineering
• /
• v.3A no.2
• /
• pp.79-84
• /
• 2003

Unbalanced systems, such as distribution systems, have difficulties in fault locations due to single-phase laterals and loads. This paper proposes new fault locations developed by the direct three-phase circuit analysis algorithms using matrix inverse lemma for the line-to-ground fault case and the line-to-line fault case in unbalanced systems. The fault location for balanced systems has been studied using the current distribution factor, by a conventional symmetrical transformation, but that for unbalanced systems has not been investigated due to their high complexity. The proposed algorithms overcome the limit of the conventional algorithm using the conventional symmetrical transformation, which requires the balanced system and are applicable to any power system but are particularly useful for unbalanced distribution systems. Their effectiveness has been proven through many EMTP simulations.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2183-2187
• /
• 2005

In this paper we propose a new fault detection and isolation (FDI) method for those faults of parameter change type. First, we design a residual generator based on the ${\delta}$-operator model of the plant by using the stable pseudo inverse system. Second, the parameter change is estimated by using the property of the block Hankel operator. Third, reliability with respect to stability is quantified. Fourth, the limitations for the meaningful diagnosis in our method are given. The numerical examples demonstrate the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.339-343
• /
• 1990

This paper describes a neural-network-based methodology for providing a potential solution in the area of process fault diagnosis. The existing neural network for fault diagnosis learn fault node by using pairs of single-symptom-single-cause only. But in real plants, the effect of a fault propagates continuously from it's origin; different sensor values reflect this. In this paper, we suggest a new method which can handle the effect of symptom propagation. The proposed method can find the exact origin of the fault of which the symptom is propagated continuously with time.