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Research Papers: Gas Turbines: Controls, Diagnostics, and Instrumentation

Jet Engine Health Signal Denoising Using Optimally Weighted Recursive Median Filters

[+] Author and Article Information
Payuna Uday

Department of Electronics and Communication Engineering, National Institute of Technology, Tiruchirappalli 620015, India

Ranjan Ganguli

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

J. Eng. Gas Turbines Power 132(4), 041601 (Jan 12, 2010) (8 pages) doi:10.1115/1.3200907 History: Received October 29, 2008; Revised June 19, 2009; Published January 12, 2010; Online January 12, 2010

The removal of noise and outliers from health signals is an important problem in jet engine health monitoring. Typically, health signals are time series of damage indicators, which can be sensor measurements or features derived from such measurements. Sharp or sudden changes in health signals can represent abrupt faults and long term deterioration in the system is typical of gradual faults. Simple linear filters tend to smooth out the sharp trend shifts in jet engine signals and are also not good for outlier removal. We propose new optimally designed nonlinear weighted recursive median filters for noise removal from typical health signals of jet engines. Signals for abrupt and gradual faults and with transient data are considered. Numerical results are obtained for a jet engine and show that preprocessing of health signals using the proposed filter significantly removes Gaussian noise and outliers and could therefore greatly improve the accuracy of diagnostic systems.

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Copyright © 2010 by American Society of Mechanical Engineers
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Figures

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Figure 1

Schematic representation of health monitoring system

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Figure 2

Schematic representation of jet engine and four basic measurements

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Figure 3

Step signal representing a HPC fault and its repair

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Figure 4

Ramp signal representing a HPT fault and its repair

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Figure 5

Combination signal (step and ramp) representing a HPC fault and its repair followed by a HPT fault and its repair

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Figure 6

Transient gas path signal representing IPC fault and transient data

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Figure 7

Effect of weighted RM filters on noisy step signal with SNR=1.5

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Figure 8

Effect of weighted RM filters on noisy ramp signal with SNR=1.5

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Figure 9

Effect of weighted RM filters on noisy combination signal with SNR=1.5

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Figure 10

Effect of weighted RM filters on noisy realistic signal with SNR=1.5

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Figure 11

Effect of weighted RM filters on noisy combination signal with outliers

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Figure 12

Effect of weighted RM filters on noisy step signal with outliers

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Figure 13

Effect of weighted RM filters on noisy ramp signal with outliers

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Figure 14

Effect of weighted RM filters on noisy realistic signal with outliers

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