The Pre-Stall Behavior of a 4-Stage Transonic Compressor and Stall Monitoring Based on Artificial Neural Networks

The Pre-Stall Behavior of a 4-Stage Transonic Compressor and Stall Monitoring Based on Artificial Neural Networks

Current research concerned with the aerodynamic instability of compressors aims at an extension of the operating range of the compressor towards decreased massflow. In practice, a safety margin is maintained between operating point and stability limit to prevent the compressor from going into stall...

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Main Authors: Frank-Oliver Methling, Horst Stoff, Frank Grauer
Format: Article
Language:English
Published: Hindawi Limited 2004-01-01
Series:International Journal of Rotating Machinery
Online Access:http://dx.doi.org/10.1155/S1023621X04000399
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spelling doaj-0bb0d43b37014b93bf382eae8ef66dbe2020-11-24T23:24:51ZengHindawi LimitedInternational Journal of Rotating Machinery1023-621X2004-01-0110538739910.1155/S1023621X04000399The Pre-Stall Behavior of a 4-Stage Transonic Compressor and Stall Monitoring Based on Artificial Neural NetworksFrank-Oliver Methling0Horst Stoff1Frank Grauer2Fluid Energy Machines, Ruhr-University Bochum, GermanyFluid Energy Machines, Ruhr-University Bochum, GermanyMTU Aero Engines, Munich, GermanyCurrent research concerned with the aerodynamic instability of compressors aims at an extension of the operating range of the compressor towards decreased massflow. In practice, a safety margin is maintained between operating point and stability limit to prevent the compressor from going into stall and surge. In this article, we analyze the behavior of a 4-stage transonic axial compressor before entering the unstable range and present an approach to identifying incipient surge and stall using artificial neural networks. This method is based on measurements of the unsteady static wall pressure in front of the first rotor.http://dx.doi.org/10.1155/S1023621X04000399
collection DOAJ
language English
format Article
sources DOAJ
author Frank-Oliver Methling
Horst Stoff
Frank Grauer
spellingShingle Frank-Oliver Methling
Horst Stoff
Frank Grauer
The Pre-Stall Behavior of a 4-Stage Transonic Compressor and Stall Monitoring Based on Artificial Neural Networks
International Journal of Rotating Machinery
author_facet Frank-Oliver Methling
Horst Stoff
Frank Grauer
author_sort Frank-Oliver Methling
title The Pre-Stall Behavior of a 4-Stage Transonic Compressor and Stall Monitoring Based on Artificial Neural Networks
title_short The Pre-Stall Behavior of a 4-Stage Transonic Compressor and Stall Monitoring Based on Artificial Neural Networks
title_full The Pre-Stall Behavior of a 4-Stage Transonic Compressor and Stall Monitoring Based on Artificial Neural Networks
title_fullStr The Pre-Stall Behavior of a 4-Stage Transonic Compressor and Stall Monitoring Based on Artificial Neural Networks
title_full_unstemmed The Pre-Stall Behavior of a 4-Stage Transonic Compressor and Stall Monitoring Based on Artificial Neural Networks
title_sort pre-stall behavior of a 4-stage transonic compressor and stall monitoring based on artificial neural networks
publisher Hindawi Limited
series International Journal of Rotating Machinery
issn 1023-621X
publishDate 2004-01-01
description Current research concerned with the aerodynamic instability of compressors aims at an extension of the operating range of the compressor towards decreased massflow. In practice, a safety margin is maintained between operating point and stability limit to prevent the compressor from going into stall and surge. In this article, we analyze the behavior of a 4-stage transonic axial compressor before entering the unstable range and present an approach to identifying incipient surge and stall using artificial neural networks. This method is based on measurements of the unsteady static wall pressure in front of the first rotor.
url http://dx.doi.org/10.1155/S1023621X04000399
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