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Journal ArticleDOI

Adaptive Kalman filter and neural network based high impedance fault detection in power distribution networks

TLDR
In this article, an intelligent approach for high impedance fault detection in power distribution feeders using combined Adaptive Extended Kalman Filter (AEKF) and probabilistic neural network (PNN) is presented.
About
This article is published in International Journal of Electrical Power & Energy Systems.The article was published on 2009-05-01. It has received 65 citations till now. The article focuses on the topics: Probabilistic neural network & Extended Kalman filter.

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Citations
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Journal ArticleDOI

High impedance fault detection: A review

TL;DR: A review of the literature related to the HIF phenomenon can be found in this paper, where the authors categorized, evaluated, and compared the existing HIF detection techniques and HIF location techniques.
Journal ArticleDOI

Statistical decision-tree based fault classification scheme for protection of power transmission lines

TL;DR: The proposed algorithm is based upon the wavelet transform of three phase currents measured at the sending end of a line and the Classification and Regression Tree (CART) method, a commonly available statistical method.
Journal ArticleDOI

Wavelet entropy based algorithm for fault detection and classification in FACTS compensated transmission line

TL;DR: A new algorithm is proposed to detect and classify the fault and identify the fault position in a transmission line with respect to a FACTS device placed in the midpoint of the transmission line.
Journal ArticleDOI

Transmission lines distance protection using artificial neural networks

TL;DR: This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection that does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems.
Journal ArticleDOI

Fault detection in transmission networks of power systems

TL;DR: In this article, an online fault detection scheme for a sample power system is introduced based on the use of a variable structure system called "sliding mode observer" where information contained in the output measurements is utilized to detect the onset of faults in the transmission network of the sample power systems in real time and online.
References
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Journal ArticleDOI

Joint estimation of PN code delay and multipath using the extended Kalman filter

TL;DR: It is shown that the extended Kalman filter (EKF) can be used to obtain joint estimates of time-of-arrival and multipath coefficients for deterministic signals when the channel can be modeled as a tapped-delay line.
Journal ArticleDOI

A de-noising scheme for enhancing wavelet-based power quality monitoring system

TL;DR: In this paper, a threshold of eliminating the influences of noises is determined adaptively according to the background noises, and the abilities of the wavelet transform in detecting and localizing the disturbances can hence be restored.
Journal ArticleDOI

Training fuzzy systems with the extended Kalman filter

TL;DR: It is demonstrated that the Kalman filter can be an effective tool for improving the performance of a fuzzy system and is compared with gradient descent and adaptive neuro-fuzzy inference system (ANFIS) based optimization of fuzzy membership functions.
Journal ArticleDOI

A digital signal processing algorithm for detecting arcing faults on power distribution feeders

TL;DR: Signal processing hardware and software that can be used to improve the detection of certain power system faults using computer relays are discussed and the use of a knowledge-based environment to modify protection criteria is suggested.
Journal ArticleDOI

Detecting arcing downed-wires using fault current flicker and half-cycle asymmetry

TL;DR: In this paper, a simple approach was taken to design an arcing fault detector, which utilizes the random behavior of the fault current, and calculated the asymmetry of the current by comparing the positive and negative current peaks in one cycle to those in the next cycle to measure the flicker in the current signal.
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