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

Performance Model “Zooming” for In-Depth Component Fault Diagnosis

[+] Author and Article Information
N. Aretakis

Laboratory of Thermal Turbomachines, National Technical University of Athens, Iroon Polytechniou 9, Zografou, Athens 15780, Greecenaret@central.ntua.gr

I. Roumeliotis

Section of Naval Architecture and Marine Engineering, Hellenic Naval Academy, Hatzikiriakou Avenue, Hatziriakio, 18539 Piraeus, Greecejroume@central.ntua.gr

K. Mathioudakis

Laboratory of Thermal Turbomachines, National Technical University of Athens, Iroon Polytechniou 9, Zografou, Athens 15780, Greecekmathiou@central.ntua.gr

J. Eng. Gas Turbines Power 133(3), 031602 (Nov 11, 2010) (11 pages) doi:10.1115/1.4002042 History: Received May 06, 2010; Revised May 12, 2010; Published November 11, 2010; Online November 11, 2010

A method giving the possibility for a more detailed gas path component fault diagnosis by exploiting the “zooming” feature of current performance modeling techniques is presented. A diagnostic engine performance model is the main tool that points to the faulty engine component. A diagnostic component model is then used to identify the fault. The method is demonstrated on the case of compressor faults. A 1D model based on the “stage stacking” approach is used to “zoom” into the compressors, supporting a 0D engine model. A first level diagnosis determines the deviation of overall compressor performance parameters while zooming calculations allow a localization of the faulty stages of a multistage compressor. The possibility to derive more detailed information with no additional measurement data is established by the incorporation of empirical knowledge on the type of faults that are usually encountered in practice. Although the approach is based on known individual diagnostic methods, it is demonstrated that the integrated formulation provides not only higher effectiveness but also additional fault identification capabilities.

Copyright © 2011 by American Society of Mechanical Engineers
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References

Figures

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Figure 17

Compressor stage modification factors for erosion and tip clearance increase, severity 100%, and examining different fault distributions

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Figure 1

Schematic representation of a three spool gas turbine and discrimination of its components

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Figure 2

Model adaptation to multiple point performance data

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Figure 3

Flowchart of the adaptive stage stacking

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Figure 4

Coupling of stage stacking model and performance model

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Figure 5

Alternatives of POINT-TO-point correspondence for expressing modification of stage characteristics

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Figure 6

Generalized characteristic curves extracted from the results by Suder (27)

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Figure 7

Generalized characteristic curves extracted from the results by Reid and Urasek (30)

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Figure 8

Generalized characteristic curves according to Inoue (33)

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Figure 9

Fault signatures for the three examined faults at fault severity 100% and for different operating points

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Figure 10

Performance related quantity deviation in function of fault severity for the three examined faults and constant load (100%)

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Figure 11

Performance related quantity deviation in function of fault severity for the three examined faults and for constant TIT (at load 100%)

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Figure 12

Compressor and turbine map related modification factors

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Figure 13

Representation of compressor map related modification factors, suitable for fault diagnosis

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Figure 14

Calculated compressor stage modification factors for fouling severity 100%, assuming different fault distributions

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Figure 15

Calculated compressor stage modification factors for tip clearance severity 100%, examining different fault distributions

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Figure 16

Compressor stage modification factors for erosion severity 100%, examining different fault distributions

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