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Technical Briefs

Three- and Seven-Point Optimally Weighted Recursive Median Filters for Gas Turbine Diagnostics

[+] Author and Article Information
V. N. Guruprakash

Department of Aerospace Engineering, Indian Institute of Science, Bangalore 560012, India

Ranjan Ganguli1

Department of Aerospace Engineering, Indian Institute of Science, Bangalore 560012, Indiaganguli@aero.iisc.ernet.in

1

Corresponding author.

J. Eng. Gas Turbines Power 133(10), 104502 (May 03, 2011) (4 pages) doi:10.1115/1.4003285 History: Received August 23, 2010; Revised December 15, 2010; Published May 03, 2011; Online May 03, 2011

Measured health signals incorporate significant details about any malfunction in a gas turbine. The attenuation of noise and removal of outliers from these health signals while preserving important features is an important problem in gas turbine diagnostics. The measured health signals are a time series of sensor measurements such as the low rotor speed, high rotor speed, fuel flow, and exhaust gas temperature in a gas turbine. In this article, a comparative study is done by varying the window length of acausal and unsymmetrical weighted recursive median filters and numerical results for error minimization are obtained. It is found that optimal filters exist, which can be used for engines where data are available slowly (three-point filter) and rapidly (seven-point filter). These smoothing filters are proposed as preprocessors of measurement delta signals before subjecting them to fault detection and isolation algorithms.

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Copyright © 2011 by American Society of Mechanical Engineers
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Figures

Grahic Jump Location
Figure 1

Transient signal with noise and outliers

Grahic Jump Location
Figure 2

Transient signal including noise and outliers after filtering with three-point WRM filter

Grahic Jump Location
Figure 3

Transient signal including noise and outliers after filtering with seven-point WRM filter

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