Condition monitoring of electrical power plant components during operational transients

Piero Baraldi, Francesco Di Maio, Luca Pappaglione, Enrico Zio and Redouane Seraoui

Journal of Risk and Reliability, 2012, vol. 226, issue 6, 568-583

Abstract: Monitoring the condition of a component is typically based on an empirical model that estimates the values of some measurable variables (signals) in normal conditions and triggers the fault alarm when the reconstruction deviates from the measured signal. When condition monitoring is performed during plant operational transients the intrinsically dynamic behavior of the signals should be taken into account. To this purpose, two approaches are proposed in this work. The former is based on the development of several reconstruction models, each one dedicated to a different operational zone of the component. The latter is based on the preprocessing of the signals by means of Haar wavelet transforms. The performance of the two proposed approaches are compared with that of the traditional reconstruction approach used for stationary conditions, with respect to a case study concerning the condition monitoring of a gas turbine during start-up transients.

Keywords: Condition monitoring; signal reconstruction; auto-associative kernel regression; Haar transform; gas turbine; start-up transients (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:226:y:2012:i:6:p:568-583

DOI: 10.1177/1748006X12463502

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