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On Hilbert transform methods for low frequency oscillations detection

Content Provider	IET Digital Library
Author	Lauria, Davide Pisani, Cosimo
Abstract	This study tackles the issue of electromechanical modes identification through a measurement-based methodology employing a novel signal decomposition theorem based upon the Hilbert transform. The methodology aims to answer in a simpler and more pragmatic manner to the main weaknesses of the Hilbert–Huang transform with respect to the major refinements in the relevant literature. These weak points are discussed with sufficient detailed degree in the study. The main contribution of this study consists in combining a recent signal decomposition theorem for separating an assigned signal into elemental ones, each of them characterised by a single frequency component and a robust preliminary non-linear spectral analyser, named L p periodogram. This procedure's results are very appropriate for analysing some critical cases of electromechanical oscillations, because of the L p periodogram robustness against heavy-tailed noise and also its intrinsic ability in estimating closely spaced frequency components. The proposed approach is found to be inherently simple, reliable and consistent in performance as well as characterised by low computational burden. Some numerical applications validate the methodology and assess its own performance on synthetic signals, near real-life signals acquired by IEEE test networks and on a real measured signal from a wide-area monitoring system currently in operation.
Starting Page	1061
Ending Page	1074
Page Count	14
ISSN	17518687
Volume Number	8
e-ISSN	17518695
Issue Number	Issue 6, Jun (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/8/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2013.0545
Journal	IET Generation, Transmission & Distribution
Publisher Date	2014-02-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Electromechanical Mode Identification Hilbert Transform Hilbert-Huang Transform IEEE Test Network Integral Transforms in Numerical Analysis Low Frequency Oscillations Detection Lp Periodogram Measurement System Measurement-based Methodology Near Real-life Signal Network And Spectrum Analysers Numerical Application Robust Preliminary Nonlinear Spectral Analyser Signal Decomposition Theorem Signal Processing Signal Processing And Detection Single Frequency Component Spectral Analysers Synthetic Signal Wide-area Monitoring System
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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