Paper Title:
Identification and Fault Diagnosis of an Industrial Gas Turbine Using State-Space Methods
  Abstract

The objective of this paper is to identify, detect and isolate faults to an industrial gas turbine. The detection scheme is based on the generation of so-called "residuals" that are errors between estimated and measured variables of the process. A State-Space model is used for identification and some observer-based methods are used for residual generation, while for residual evaluation a neural network classifier for MLP is used. The proposed fault detection and isolation tool has been tested on a single-shaft industrial gas turbine simulator.

  Info
Periodical
Advanced Materials Research (Volumes 383-390)
Chapter
Chapter 5: Computer-Aided Design in Materials Engineering
Edited by
Wu Fan
Pages
1000-1006
DOI
10.4028/www.scientific.net/AMR.383-390.1000
Citation
I. Yousefi, H. Khaloozadeh, A. Ashraf-Modarres, "Identification and Fault Diagnosis of an Industrial Gas Turbine Using State-Space Methods", Advanced Materials Research, Vols. 383-390, pp. 1000-1006, 2012
Online since
November 2011
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Price
$32.00
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