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Research Papers: Gas Turbines: Turbomachinery

Correlation Analysis of Multiple Sensors for Industrial Gas Turbine Compressor Blade Health Monitoring

[+] Author and Article Information
Brian Kestner

School of Aerospace Engineering,
Georgia Institute of Technology,
270 Ferst Drive,
Atlanta, GA 30332-0150
e-mail: bkkestner@yahoo.com

Tim Lieuwen

School of Aerospace Engineering,
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

Electric Power Research Institute,
3420 Hillview Avenue,
Palo Alto, CA 94304
e-mail: langello@epri.com

Josh Barron

Southern Company,
600 North 18th Street,
Birmingham, AL 35203
e-mail: jbarron@southernco.com

Christopher A. Perullo

School of Aerospace Engineering,
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 137(11), 112605 (Nov 01, 2015) (11 pages) Paper No: GTP-15-1026; doi: 10.1115/1.4030350 History: Received January 26, 2015; Revised March 24, 2015; Online May 12, 2015

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.

Copyright © 2015 by ASME
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References

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Figures

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Fig. 1

Hypothetical Campbell diagram showing sources of vibration [2]

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Fig. 2

FFT of single and two cell rotating stall [5]

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Fig. 3

PCB sensor installation on stage 1–4

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Fig. 4

Tip timing sensor installation

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Fig. 5

Dynamic deflections measured during shutdown #1

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Fig. 6

Pressure and vibration Fourier magnitude versus rpm for startup #2

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Fig. 7

Startup #1 mode 1 NSV with points of comparison

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Fig. 8

Startup #1 PCB1 low frequency FFT at tip timing points of interest

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Fig. 9

Startup #1 compressor X bearing vibration low frequency FFT at tip timing points of interest

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Fig. 10

Startup #2 Mode 1 NSV with points of comparison

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Fig. 11

Startup #2 PCB1 low frequency FFT at tip timing points of interest

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Fig. 12

Startup #2 compressor X bearing vibration low frequency FFT at tip timing points of interest

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Fig. 13

Startup #4 Mode 1 NSV with points of comparison

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Fig. 14

Startup #4 PCB1 low frequency FFT at tip timing points of interest

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Fig. 15

Startup #4 compressor X bearing vibrations low frequency FFT at tip timing points of interest

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Fig. 16

Mode 1 NSV regions of interest

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