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Condition Monitoring of Gas Turbines using Acoustic Emissions


Condition Monitoring of Gas Turbines using Acoustic Emissions

Shahkar, Shahram (2018) Condition Monitoring of Gas Turbines using Acoustic Emissions. Masters thesis, Concordia University.

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Acoustic emission (AE) technology has recently found its way in condition monitoring of rotary equipment due to its advantage of earlier detection of defects and anoma- lies in comparison to vibration analysis. However, there has been very little industrial application of AE signals for condition monitoring of safety-critical equipment if any, partly due to the diffculty in processing, interpreting and classifying the acquired data in a highly reliable fashion. The motivation in this thesis was to develop a methodol- ogy for inferring health related information in a gas turbine without intruding the engine.
Our work has targeted a broad class of rotary equipment known as cyclostationary processes, therefore, instead of analyzing particular AE samples of gas turbines we have tried to build a mathematical framework that would suit any arbitrary machine comply- ing certain conditions. The result of our work mainly encompasses a feature extraction technique that eliminates the random e↵ects associated with a gas turbine AE signal, and a hypothetical testing method for classification of AE signals with any desirable level of certainty, subject to a set of assumptions and conditions.
We have validated our methodologies and derivations using actual real-life gas turbine AE signals, and compared our solutions with some of the techniques published in the literature.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Shahkar, Shahram
Institution:Concordia University
Degree Name:M. Sc.
Program:Electrical and Computer Engineering
Date:12 June 2018
Thesis Supervisor(s):Khorasani, Khashayar
Keywords:Acoustic Emissions, Condition Monitoring,
ID Code:983945
Deposited By: Shahram Shahkar
Deposited On:16 Nov 2018 16:18
Last Modified:16 Nov 2018 16:18
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