Počet záznamů: 1  

Semiparametric Statistical Analysis of the Blade Tip Timing Data for Detection of Turbine Rotor Speed Instabilities

  1. 1.
    SYSNO ASEP0490148
    Druh ASEPJ - Článek v odborném periodiku
    Zařazení RIVJ - Článek v odborném periodiku
    Poddruh JČlánek ve WOS
    NázevSemiparametric Statistical Analysis of the Blade Tip Timing Data for Detection of Turbine Rotor Speed Instabilities
    Tvůrce(i) Brabec, Marek (UIVT-O) RID, SAI, ORCID
    Procházka, Pavel (UT-L) RID, ORCID
    Maturkanič, Dušan (UT-L)
    Zdroj.dok.Quality and Reliability Engineering International. - : Wiley - ISSN 0748-8017
    Roč. 34, č. 7 (2018), s. 1308-1314
    Poč.str.7 s.
    Jazyk dok.eng - angličtina
    Země vyd.GB - Velká Británie
    Klíč. slovaBTT ; GAM ; semiparametric model ; state-space model ; vibrodiagnostics ; turbine rotor ; rotating speed instability ; non-contact vibration diagnostics ; time-varying-coefficient model
    Vědní obor RIVBB - Aplikovaná statistika, operační výzkum
    Obor OECDStatistics and probability
    Vědní obor RIV – spolupráceÚstav termomechaniky - Senzory, čidla, měření a regulace
    Institucionální podporaUIVT-O - RVO:67985807 ; UT-L - RVO:61388998
    UT WOS000445334700002
    EID SCOPUS85053641718
    DOI10.1002/qre.2327
    AnotaceIn this paper, we propose an extension of an existing standard approach to the blade tip timing data when analyzing turbine rotor vibrations. Instabilities related to the non‐constant trigonometric coefficients at prominent frequencies might not be noticed in the traditional analyses. Our methodology is based on time‐varying coefficient statistical models, and hence it allows a full formalization of the estimation and other inferential tasks (uncertainty assessments, hypothesis tests etc.). First, we formulate a univariate generalized additive model that is useful for investigation of vibration behavior of individual blades. It can extract trajectories of the trigonometric coefficients. Using the trajectories, one can investigate time changes of power at a given frequency. In the second approach, we use a multivariate model for simultaneous assessment of all of the rotor blades. The model acknowledges similarity of the vibration behavior of closely located blades. It is formulated as a state‐space model, and hence it allows for a wide range of prediction, smoothing, and filtering tasks. We illustrate the performance and practical usefulness of our models on real blade tip timing turbine monitoring data obtained from the Czech nuclear power plant Temelin.
    PracovištěÚstav informatiky
    KontaktTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Rok sběru2019
Počet záznamů: 1  

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