Probabilistic Life Assessment of Gas Turbine Blades
Probabilistic Life Assessment of Gas Turbine Blades
This paper addresses the problem of analyzing measurement data to estimate the variations in turbine blade life in the presence of manufacturing variability. A methodologythat employs existing denoising techniques, namely, Principal Component Analysis and Fast Fourier Transform analysis, is proposed for filtering measurement error from the measured data set. An approach for dimensionality reduction is employed that uses prior knowledge on the measurement error obtained from analyzing repeated measurements. The proposed methodology also helps in capturing the effects of manufacturing drift with time and the blade to blade manufacturing error. The filtered data is then used for generating three-dimensional representations of probable manufactured blade shapesfrom the limited number of available measurements. This is accomplished by using a Free-Form Deformation based approach for deforming a nominal mesh to the desiredshapes. Estimations of life on the probable turbine blade shapes manufactured over a span of 1 year indicate a reduction of around 1.7% in the mean life relative to thenominal life, with a maximum relative reduction of around 3.7%, due to the effects of manufacturing variability
121005-[9pp]
Thakur, Nikita
3b863526-fe12-4bf0-ac3e-681256d3e318
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Nair, P.B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Rao, A.
48e0dfb7-cd0d-4055-a40f-b5cab3789bb4
December 2010
Thakur, Nikita
3b863526-fe12-4bf0-ac3e-681256d3e318
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Nair, P.B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Rao, A.
48e0dfb7-cd0d-4055-a40f-b5cab3789bb4
Thakur, Nikita, Keane, A.J., Nair, P.B. and Rao, A.
(2010)
Probabilistic Life Assessment of Gas Turbine Blades.
Journal of Mechanical Design, 132 (12), .
(doi:10.1115/1.4002806).
Abstract
This paper addresses the problem of analyzing measurement data to estimate the variations in turbine blade life in the presence of manufacturing variability. A methodologythat employs existing denoising techniques, namely, Principal Component Analysis and Fast Fourier Transform analysis, is proposed for filtering measurement error from the measured data set. An approach for dimensionality reduction is employed that uses prior knowledge on the measurement error obtained from analyzing repeated measurements. The proposed methodology also helps in capturing the effects of manufacturing drift with time and the blade to blade manufacturing error. The filtered data is then used for generating three-dimensional representations of probable manufactured blade shapesfrom the limited number of available measurements. This is accomplished by using a Free-Form Deformation based approach for deforming a nominal mesh to the desiredshapes. Estimations of life on the probable turbine blade shapes manufactured over a span of 1 year indicate a reduction of around 1.7% in the mean life relative to thenominal life, with a maximum relative reduction of around 3.7%, due to the effects of manufacturing variability
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Published date: December 2010
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Local EPrints ID: 169021
URI: http://eprints.soton.ac.uk/id/eprint/169021
ISSN: 1050-0472
PURE UUID: 8c7c317b-3a64-491a-ba17-08d31ee0f815
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Date deposited: 08 Dec 2010 14:57
Last modified: 14 Mar 2024 02:39
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Author:
Nikita Thakur
Author:
P.B. Nair
Author:
A. Rao
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