Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission

Fatigue failure is the main type of failure that occurs in gas turbine engine blades and an online monitoring method for detecting fatigue cracks in blades is urgently needed. Therefore, in this present study, we propose the use of acoustic emission (AE) monitoring for the online identification of t...

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Detalles Bibliográficos
Autores principales: Zhang, Zhiheng, Yang, Guoan, Hu, Kun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982231/
https://www.ncbi.nlm.nih.gov/pubmed/29693556
http://dx.doi.org/10.3390/s18051321
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author Zhang, Zhiheng
Yang, Guoan
Hu, Kun
author_facet Zhang, Zhiheng
Yang, Guoan
Hu, Kun
author_sort Zhang, Zhiheng
collection PubMed
description Fatigue failure is the main type of failure that occurs in gas turbine engine blades and an online monitoring method for detecting fatigue cracks in blades is urgently needed. Therefore, in this present study, we propose the use of acoustic emission (AE) monitoring for the online identification of the blade status. Experiments on fatigue crack propagation based on the AE monitoring of gas turbine engine blades and TC11 titanium alloy plates were conducted. The relationship between the cumulative AE hits and the fatigue crack length was established, before a method of using the AE parameters to determine the crack propagation stage was proposed. A method for predicting the degree of crack propagation and residual fatigue life based on the AE energy was obtained. The results provide a new method for the online monitoring of cracks in the gas turbine engine blade.
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spelling pubmed-59822312018-06-05 Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission Zhang, Zhiheng Yang, Guoan Hu, Kun Sensors (Basel) Article Fatigue failure is the main type of failure that occurs in gas turbine engine blades and an online monitoring method for detecting fatigue cracks in blades is urgently needed. Therefore, in this present study, we propose the use of acoustic emission (AE) monitoring for the online identification of the blade status. Experiments on fatigue crack propagation based on the AE monitoring of gas turbine engine blades and TC11 titanium alloy plates were conducted. The relationship between the cumulative AE hits and the fatigue crack length was established, before a method of using the AE parameters to determine the crack propagation stage was proposed. A method for predicting the degree of crack propagation and residual fatigue life based on the AE energy was obtained. The results provide a new method for the online monitoring of cracks in the gas turbine engine blade. MDPI 2018-04-25 /pmc/articles/PMC5982231/ /pubmed/29693556 http://dx.doi.org/10.3390/s18051321 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Zhiheng
Yang, Guoan
Hu, Kun
Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission
title Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission
title_full Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission
title_fullStr Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission
title_full_unstemmed Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission
title_short Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission
title_sort prediction of fatigue crack growth in gas turbine engine blades using acoustic emission
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982231/
https://www.ncbi.nlm.nih.gov/pubmed/29693556
http://dx.doi.org/10.3390/s18051321
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AT yangguoan predictionoffatiguecrackgrowthingasturbineenginebladesusingacousticemission
AT hukun predictionoffatiguecrackgrowthingasturbineenginebladesusingacousticemission

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