This paper summarizes an analysis of data obtained from an instrumented compressor of an operational, heavy duty industrial gas turbine; the goal of the aforementioned analysis is to understand some of the fundamental drivers, which may lead to compressor blade vibration. Methodologies are needed to (1) understand the fundamental drivers of compressor blade vibration, (2) quantify the severity of “events,” which accelerate the likelihood of failure and reduce the remaining life of the blade, and (3) proactively detect when these issues are occurring so that the operator can take corrective action. The motivation for this analysis lies in understanding the correlations between different sensors, which may be used to measure the fundamental drivers and blade vibrations. In this study, a variety of dynamic data was acquired from an operating engine, including acoustic pressure, bearing vibration, tip timing, and traditional gas path measurements. The acoustic pressure sensors were installed on the first four compressor stages, while the tip timing was installed on the first stage only. These data show the presence of rotating stall instabilities in the front stages of the compressor, occurring during every startup and shutdown, and manifesting itself as increased amplitude oscillations in the dynamic pressure measurements, which are manifested in blade and bearing vibrations. The data that lead to these observations were acquired during several startup and shutdown events, and clearly show that the amplitude of these instabilities and the rpm at which they occur can vary substantially.
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November 2015
Research-Article
Correlation Analysis of Multiple Sensors for Industrial Gas Turbine Compressor Blade Health Monitoring
Brian Kestner,
Brian Kestner
1
School of Aerospace Engineering,
e-mail: bkkestner@yahoo.com
Georgia Institute of Technology
,270 Ferst Drive
,Atlanta, GA 30332-0150
e-mail: bkkestner@yahoo.com
1Primary employer—work performed as consultant to EPRI.
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Tim Lieuwen,
Tim Lieuwen
1
School of Aerospace Engineering,
e-mail: tim.lieuwen@aerospace.gatech.edu
Georgia Institute of Technology
,270 Ferst Drive
,Atlanta, GA 30332-0150
e-mail: tim.lieuwen@aerospace.gatech.edu
1Primary employer—work performed as consultant to EPRI.
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Chris Hill,
e-mail: chill@agilis.com
Chris Hill
Agilis Measurement Systems, Inc.
,3930 RCA Blvd Suite 3000
,Palm Beach Gardens, FL 33410
e-mail: chill@agilis.com
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Christopher A. Perullo
Christopher A. Perullo
School of Aerospace Engineering,
e-mail: chris.perullo@ae.gatech.edu
Georgia Institute of Technology
,270 Ferst Drive
,Atlanta, GA 30332-0150
e-mail: chris.perullo@ae.gatech.edu
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Brian Kestner
School of Aerospace Engineering,
e-mail: bkkestner@yahoo.com
Georgia Institute of Technology
,270 Ferst Drive
,Atlanta, GA 30332-0150
e-mail: bkkestner@yahoo.com
Tim Lieuwen
School of Aerospace Engineering,
e-mail: tim.lieuwen@aerospace.gatech.edu
Georgia Institute of Technology
,270 Ferst Drive
,Atlanta, GA 30332-0150
e-mail: tim.lieuwen@aerospace.gatech.edu
Chris Hill
Agilis Measurement Systems, Inc.
,3930 RCA Blvd Suite 3000
,Palm Beach Gardens, FL 33410
e-mail: chill@agilis.com
Leonard Angello
Josh Barron
Christopher A. Perullo
School of Aerospace Engineering,
e-mail: chris.perullo@ae.gatech.edu
Georgia Institute of Technology
,270 Ferst Drive
,Atlanta, GA 30332-0150
e-mail: chris.perullo@ae.gatech.edu
1Primary employer—work performed as consultant to EPRI.
2Corresponding author.
Contributed by the Turbomachinery Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received January 26, 2015; final manuscript received March 24, 2015; published online May 12, 2015. Editor: David Wisler.
J. Eng. Gas Turbines Power. Nov 2015, 137(11): 112605 (11 pages)
Published Online: November 1, 2015
Article history
Received:
January 26, 2015
Revision Received:
March 24, 2015
Online:
May 12, 2015
Citation
Kestner, B., Lieuwen, T., Hill, C., Angello, L., Barron, J., and Perullo, C. A. (November 1, 2015). "Correlation Analysis of Multiple Sensors for Industrial Gas Turbine Compressor Blade Health Monitoring." ASME. J. Eng. Gas Turbines Power. November 2015; 137(11): 112605. https://doi.org/10.1115/1.4030350
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