Rapid Detection of Small Faults and Oscillations in Synchronous Generator Systems Using GMDH Neural Networks and High-Gain Observers

Rapid Detection of Small Faults and Oscillations in Synchronous Generator Systems Using GMDH Neural Networks and High-Gain Observers

This paper presents a robust and efficient fault detection and diagnosis framework for handling small faults and oscillations in synchronous generator (SG) systems. The proposed framework utilizes the Brunovsky form representation of nonlinear systems to mathematically formulate the fault detection...

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Bibliographic Details
Main Authors: Pooria Ghanooni, Hamed Habibi, Amirmehdi Yazdani, Hai Wang, Somaiyeh MahmoudZadeh, Amin Mahmoudi
Format: article
Language:EN
Published: MDPI AG 2021
Subjects:
group method of data handling neural network
high-gain observer
L1-Norm criterion
output residual generation
small fault detection
synchronous generator
Electronics
TK7800-8360
Online Access:https://doaj.org/article/01bc4b52010b4eef99938b6b9d090c77
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https://doaj.org/article/01bc4b52010b4eef99938b6b9d090c77

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