Gas path fault diagnosis plays an important role in guaranteeing safe, reliable and cost-effective operation for gas turbine engines. Measurements selection is among the most critical issues for diagnostic method implementation. In this paper, an integration approach for optimal measurements selection, which combines finger print diagrams analysis, health parameters correlation analysis, performance estimation uncertainty index analysis and fault cases validation based on genetic algorithm, has been proposed and applied to assess the health condition of a two-spool split flow turbofan in test bed. First, mathematical description of an engine gas path fault diagnosis process was given and the influence coefficient matrix was also calculated based on a well calibrated nonlinear engine performance simulation model. Second, the number of combination candidates was reduced from 782 to 256 and three measurements were picked out using the finger print diagrams analysis and the health parameters correlation analysis. Then, the number of the combination candidates was further narrowed down to 13 using the performance estimation uncertainty index analysis. A nonlinear genetic algorithm fault diagnosis method was applied to test the diagnostic ability of the remaining measurement candidates. Finally, an optimal measurement combination was worked out which demonstrated the effectiveness of the integration approach. This integration approach for optimal measurements selection is also applicable to other type of gas turbine engines.
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e-mail: lovehuliangquan@163.com
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July 2015
Research-Article
An Approach for Optimal Measurements Selection on Gas Turbine Engine Fault Diagnosis
Min Chen,
Min Chen
1
School of Energy and Power Engineering,
e-mail: chenmin@buaa.edu.cn
Beihang University
,Beijing 100191
, China
e-mail: chenmin@buaa.edu.cn
1Corresponding author.
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Liang Quan Hu,
Aero-Engine,
e-mail: lovehuliangquan@163.com
Liang Quan Hu
Collaborative Innovation Center of Advanced
Aero-Engine,
Beijing 100191
, China
e-mail: lovehuliangquan@163.com
Search for other works by this author on:
Hailong Tang
Hailong Tang
School of Energy and Power Engineering,
e-mail: 75249612@qq.com
Beihang University
,Beijing 100191
, China
e-mail: 75249612@qq.com
Search for other works by this author on:
Min Chen
School of Energy and Power Engineering,
e-mail: chenmin@buaa.edu.cn
Beihang University
,Beijing 100191
, China
e-mail: chenmin@buaa.edu.cn
Liang Quan Hu
Collaborative Innovation Center of Advanced
Aero-Engine,
Beijing 100191
, China
e-mail: lovehuliangquan@163.com
Hailong Tang
School of Energy and Power Engineering,
e-mail: 75249612@qq.com
Beihang University
,Beijing 100191
, China
e-mail: 75249612@qq.com
1Corresponding author.
Contributed by the Aircraft Engine Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received September 1, 2014; final manuscript received November 8, 2014; published online December 23, 2014. Editor: David Wisler.
J. Eng. Gas Turbines Power. Jul 2015, 137(7): 071203 (9 pages)
Published Online: July 1, 2015
Article history
Received:
September 1, 2014
Revision Received:
November 8, 2014
Online:
December 23, 2014
Citation
Chen, M., Quan Hu, L., and Tang, H. (July 1, 2015). "An Approach for Optimal Measurements Selection on Gas Turbine Engine Fault Diagnosis." ASME. J. Eng. Gas Turbines Power. July 2015; 137(7): 071203. https://doi.org/10.1115/1.4029171
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