Fault indicator

About: Fault indicator is a research topic. Over the lifetime, 10057 publications have been published within this topic receiving 143482 citations. The topic is also known as: FCI & power line fault indicator.

Data-mining-based fault during power swing identification in power transmission system

Abstract: This study proposes a decision-tree-based scheme for detection and classification of fault during power swing in double circuit transmission lines. The power swing may result due to switching in/out of heavy loads, switching of lines, clearance of short-circuit faults, generator tripping or load shedding. The proposed decision tree approach makes the discrimination among no fault situation/power swing and fault during power swing. The fundamental components of currents and voltages and zero sequence currents measured at only one end of the double circuit line are used as input to decision tree. To ascertain validity of the proposed scheme, it is tested for variation in fault type, fault inception angle, fault location and fault resistance. The main advantage of this proposed scheme is that it detects fault during power swing within half cycle time and classify the type of fault and identify the faulty phase also.

The Fault Detection Problem

Abstract: One of the most important challenges in distributed computing is ensuring that services are correct and available despite faults. Recently it has been argued that fault detection can be factored out from computation, and that a generic fault detection service can be a useful abstraction for building distributed systems. However, while fault detection has been extensively studied for crash faults, little is known about detecting more general kinds of faults. This paper explores the power and the inherent costs of generic fault detection in a distributed system. We propose a formal framework that allows us to partition the set of all faults that can possibly occur in a distributed computation into several fault classes . Then we formulate the fault detection problem for a given fault class, and we show that this problem can be solved for only two specific fault classes, namely omission faults and commission faults . Finally, we derive tight lower bounds on the cost of solving the problem for these two classes in asynchronous message-passing systems.

A model-based approach to fault localisation in power transmission networks

Abstract: The basic idea of model-based diagnosis is to exploit knowledge about the structure and behaviour of the physical system to be diagnosed in order to identify diagnoses from discrepancies between observed and predicted behaviour. In this paper, we describe the application of model-based diagnosis to the problem of fault localisation in power transmission networks. We also show that the resulting system, DPNet, has an extended competence w.r.t. rule-based approaches (treatment of unknown and multiple faults) while requiring less development effort because of the use of component libraries in the model-based approach.

Complex Field Fault Modeling-Based Optimal Frequency Selection in Linear Analog Circuit Fault Diagnosis

Abstract: Owing to the lack of feasible fault modeling method, hard (open and short) faults, and discretized parametric faults are still the mostly used fault models. These models cannot characterize all soft (parameter shifting) faults because that the parameter of analog element be of continuity character. To address this concern, a complex field fault modeling method is presented first. If fault happens to passive element xi in linear analog circuit, the real (Ur) and imaginary (Uj) parts of faulty voltage phasor U°(U°=Ur+j Uj) must satisfy binary quadratic function Fi(Ur,Uj)=0, which is independent from the value of element xi and uniquely determined by its location and the nominal circuit under test. Hence, the binary quadratic function can model any continuous parameter shifting (soft) or hard fault. Second, to avoid calculating the explicit expression of binary quadratic function, a simulation-based method is given to obtain the locus of the change in the function Fz in the complex plane. Besides, the nominal (fault-free) point, the loci determined by the binary quadratic functions might intersect with each other. It is referred to as aliasing problem in this paper. This problem can be solved by adjusting the frequency of the input signal. Therefore, a constraint optimization method is proposed to select optimal test frequencies. The proposed test generation and compression methods, when combined with the complex field modeling method, can pinpoint much more fault components with less test points and frequencies when compared with the other methods.

Network fault information management system in which fault nodes are displayed in tree form

Abstract: A network fault managing system for a network including network elements as nodes includes a fault node indication data storage section, a fault indication data storage section, a flag, a fault node indication data processing section, a fault indication data processing section and an output unit. The fault node indication data storage section stores a fault node indication data set in which fault nodes are managed in a tree form. The fault node indication data processing section receives a fault association notice having a fault occurrence position identifier and a fault indication data, the fault occurrence position identifier indicating a fault node in which a fault has occurred, and the fault indication data indicating data associated with the fault, and determines whether a fault node indication data corresponding to the fault node specified by the fault occurrence position identifier of the fault association notice is present in the fault node indication data set. Also, the fault node indication data processing section generates the fault node indication data based on the fault occurrence position identifier to store in the fault node indication data set of the fault node indication data storage section, when the fault node indication data is not present in the fault node indication data set, and sets the flag.