ENBIS-17 in Naples

9 – 14 September 2017; Naples (Italy) Abstract submission: 21 November 2016 – 10 May 2017

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

11 September 2017, 12:40 – 13:00


Submitted by
Marek Brabec
Marek Brabec (Institute of computer science, Czech Academy of Sciences), Pavel Prochazka (Institute of Thermomechanivs, Czech Academy of Sciences), Dusan Maturkanic (Institute of Thermomechanivs, Czech Academy of Sciences)
We will present a semiparametric statistical model for detecting instabilities in a turbine rotor speed. The modeling and detection uses data obtained from the now standard BTT (Blade Tip Timing) contactless measurement method. The model is based on time-varying coefficient model formulated as a GAM (Generalized Additive Model) with appropriately selected penalty. Our approach can be perceived as a fully formalized time-varying statistical extension of the traditional Fourier analysis. As such, it can reveal important rotor instabilities not readily apparent in the traditional approaches. After presenting the underlying statistical modeling framework, we will illustrate the performance of our methodology on experimental data measured on a test turbine via magneto-resistive BTT technology. The research is supported from the AV21 Strategy of the Academy of Sciences of the Czech Republic.

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