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TECHNICAL PAPERS: Gas Turbines: Controls, Diagnostics, and Instrumentation

Nonlinear Engine Component Fault Diagnosis From a Limited Number of Measurements Using a Combinatorial Approach

[+] Author and Article Information
N. Aretakis, K. Mathioudakis, A. Stamatis

Laboratory of Thermal Turbomachines, National Technical University of Athens, Iroon Polytechniou 9, Athens 15773, Greece

J. Eng. Gas Turbines Power 125(3), 642-650 (Aug 15, 2003) (9 pages) doi:10.1115/1.1582494 History: Received December 01, 2001; Revised March 01, 2002; Online August 15, 2003
Copyright © 2003 by ASME
Topics: Measurement , Engines
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References

Figures

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Estimated fault signatures: (a) fault C, (b) fault J, second pass, noise-free data
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(a) Estimated fault signature and (b) corresponding diagnostic index, second pass, noisy data, fault A
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(a) Estimated fault signature and (b) corresponding diagnostic index, second pass, noisy data, fault G
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Comparison between second pass and best fit procedure estimation results for fault A and noisy data
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Estimated fault signatures in the case of using additional measurements: (a) fault C, (b) fault J, second pass, noise-free data
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Derivation of component condition parameters using an adaptive engine model
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Layout of a turbofan engine and station numbering for positions of interest
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Health parameter deviations using a combination that (a) contains all actual fault parameters, (b) doesn’t contain all actual fault parameters
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Deviations of estimated fault parameter values using different combinations, for parameter (a) SE2 (actually affected), (b) SW26 (not affected)
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Parameter distribution calculation for SE2, data of Fig. 4(a)
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The way of producing the most probable fault signature
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Estimated fault signatures: (a) first pass, (b) second pass, noise-free data, fault L

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