The removal of noise and outliers from measurement signals is a major problem in jet engine health monitoring. In this study, we look at the myriad filter as a substitute for the moving average filter which is widely used in the gas turbine industry. The three ideal test signals used in this study are the step signal which simulates a single fault in gas turbine, while ramp and quadratic signals simulate long term deterioration. Results show that the myriad filter performs better in noise reduction and outlier removal when compared to the moving average filter. Further, an adaptive weighted myriad filter algorithm that adapts to the quality of incoming data is studied. The filters are demonstrated on simulated clean and deteriorated engine data obtained from an acceleration process from idle to maximum thrust condition. This data was obtained from published literature and was simulated using a transient performance prediction code. The deteriorated engine had single component faults in the low pressure turbine and intermediate pressure compressor. The signals are obtained from T2 (IPC total outlet temperature) and T6 (LPT total outlet temperature) engine sensors with their non-repeatability values which were used as noise levels. The weighted myriad filter shows even greater noise reduction and outlier removal when compared to the sample myriad and FIR filter in the gas turbine diagnosis. Adaptive filters such as those considered in this study are also useful for online health monitoring as they can adapt to changes in quality of incoming data.
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ASME Turbo Expo 2004: Power for Land, Sea, and Air
June 14–17, 2004
Vienna, Austria
Conference Sponsors:
- International Gas Turbine Institute
ISBN:
0-7918-4167-7
PROCEEDINGS PAPER
Adaptive Myriad Filter for Improved Gas Turbine Condition Monitoring Using Transient Data
Vellore P. Surender,
Vellore P. Surender
Indian Institute of Science, Bangalore, India
Search for other works by this author on:
Ranjan Ganguli
Ranjan Ganguli
Indian Institute of Science, Bangalore, India
Search for other works by this author on:
Vellore P. Surender
Indian Institute of Science, Bangalore, India
Ranjan Ganguli
Indian Institute of Science, Bangalore, India
Paper No:
GT2004-53080, pp. 479-489; 11 pages
Published Online:
November 24, 2008
Citation
Surender, VP, & Ganguli, R. "Adaptive Myriad Filter for Improved Gas Turbine Condition Monitoring Using Transient Data." Proceedings of the ASME Turbo Expo 2004: Power for Land, Sea, and Air. Volume 2: Turbo Expo 2004. Vienna, Austria. June 14–17, 2004. pp. 479-489. ASME. https://doi.org/10.1115/GT2004-53080
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