TECHNICAL PAPERS: Gas Turbines: Controls, Diagnostics & Instrumentation

Assessment of the Effectiveness of Gas Path Diagnostic Schemes

[+] Author and Article Information
K. Mathioudakis, Ph. Kamboukos

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

J. Eng. Gas Turbines Power 128(1), 57-63 (Mar 01, 2004) (7 pages) doi:10.1115/1.1924535 History: Received October 01, 2003; Revised March 01, 2004

A variety of methods can be used for the diagnosis of faults in gas path components of gas turbines. Problems that are common for diagnostic method implementation are the choice of measured quantities, choice of health parameters, and choice of operating conditions for data retrieval. The present paper introduces some general principles for evaluation of the effectiveness of different diagnostic schemes. They encompass criteria proposed in past publications, while they offer additional possibilities for assessment of diagnostic effectiveness in various situations. The method is based on the evaluation of the behavior of linear systems, which are a good approximation of the nonlinear ones for small deviations and employs the concept of system condition number to formulate criteria. The determination of limits for this number for establishing system condition criteria and quantification of observability is examined, on the basis of uncertainty propagation. Sample problems evaluated are: maximizing effectiveness of individual component identification from a multiplicity of available measurements, selection of individual operating points for multipoint applications.

Copyright © 2006 by American Society of Mechanical Engineers
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Figure 1

Layout and station numbering for simple turbojet

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Figure 2

Condition numbers of systems employing four measurements, for a turbojet

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Figure 3

Uncertainty in estimated parameters for the different measurement combinations

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Figure 4

Average parameter standard deviation (σ=(σf12+σf22+⋯+σfN2)∕N), as a function of the condition number of the system used for estimation

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Figure 5

Condition numbers for health parameter combinations (11×7) with 7 given measurements, for the case of a turbofan

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Figure 6

Overall health parameter estimation uncertainty as a function of condition number for the different parameter combinations. Turbofan test case.

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Figure 7

Different operating points along the compressor of a turbofan engine

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Figure 8

Condition numbers of systems employing measurements at two operating points, and related overall estimation uncertainty

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Figure 9

Condition numbers of systems employing measurements at increasing number of operating points, and related overall estimation uncertainty

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Figure 10

Condition numbers for the WLS type of problems

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Figure 11

Nonlinear diagnostic method convergence histories for a small and a large condition number, from Table 1



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