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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 Lp periodogram. This procedure's results are very appropriate for analysing some critical cases of electromechanical oscillations, because of the Lp 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

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