A new method of power system fault recording based on compressed sensing
Author:
Affiliation:
1. Department of Electrical Engineering, College of Electronics and Information Engineering; Tongji University; 4800, CaoAn Road, Jiading Shanghai 201804 China
Publisher
Wiley
Subject
Electrical and Electronic Engineering
Reference21 articles.
1. Fast power transformer fault classification methods based on protection signals;Babnik;IET Proceedings - Generation, Transmission and Distribution,2003
2. A framework for evaluating automatic classification of underlying causes of disturbances and its application to short-circuit faults;Morais;IEEE Transactions on Power Delivery,2010
3. Parameter identification of unsymmetrical transmission lines using fault records obtained from protective relays;Schulze;IEEE Transactions on Power Delivery,2011
4. Discrete wavelet transform and support vector machine-based parallel transmission line faults classification;Saber;IEEJ Transactions on Electrical and Electronic Engineering,2016
5. Wavelet-based data compression of power system disturbances using the minimum description length criterion;Hamid;IEEE Transactions on Power Delivery,2002
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1. Method for fault location in a low-resistance grounded distribution network based on multi-source information fusion;International Journal of Electrical Power & Energy Systems;2021-02
2. Power Quality Disturbance Classification based on Adaptive Compressed Sensing and Machine Learning;2020 IEEE Green Technologies Conference(GreenTech);2020-04-01
3. Adaptive Compressive Sensing and Machine Learning for Power System Fault Classification;2020 SoutheastCon;2020-03-28
4. State and fault estimation for nonlinear recurrent neural network systems: Experimental testing on a three‐tank system;The Canadian Journal of Chemical Engineering;2020-02-23
5. State estimation and fault reconstruction with integral measurements under partially decoupled disturbances;IET Control Theory & Applications;2018-07
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