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Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers
For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422196/ https://www.ncbi.nlm.nih.gov/pubmed/28398255 http://dx.doi.org/10.3390/s17040835 |
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author | Chang, Xiaodong Huang, Jinquan Lu, Feng |
author_facet | Chang, Xiaodong Huang, Jinquan Lu, Feng |
author_sort | Chang, Xiaodong |
collection | PubMed |
description | For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding mode observer (SMO). In this approach, one sliding mode observer is designed for engine health performance tracking, and another for sensor fault reconstruction. Both observers are employed in in-flight applications. The results of the former SMO are analyzed for post-flight updating the baseline model of the latter. This idea is practical and feasible since the updating process does not require the algorithm to be regulated or redesigned, so that ground-based intervention is avoided, and the update process is implemented in an economical and efficient way. With this setup, the robustness of the proposed scheme to the health degradation is much enhanced and the latter SMO is able to fulfill sensor fault reconstruction over the course of the engine life. The proposed sensor fault diagnostic system is applied to a nonlinear simulation of a commercial aircraft engine, and its effectiveness is evaluated in several fault scenarios. |
format | Online Article Text |
id | pubmed-5422196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54221962017-05-12 Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers Chang, Xiaodong Huang, Jinquan Lu, Feng Sensors (Basel) Article For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding mode observer (SMO). In this approach, one sliding mode observer is designed for engine health performance tracking, and another for sensor fault reconstruction. Both observers are employed in in-flight applications. The results of the former SMO are analyzed for post-flight updating the baseline model of the latter. This idea is practical and feasible since the updating process does not require the algorithm to be regulated or redesigned, so that ground-based intervention is avoided, and the update process is implemented in an economical and efficient way. With this setup, the robustness of the proposed scheme to the health degradation is much enhanced and the latter SMO is able to fulfill sensor fault reconstruction over the course of the engine life. The proposed sensor fault diagnostic system is applied to a nonlinear simulation of a commercial aircraft engine, and its effectiveness is evaluated in several fault scenarios. MDPI 2017-04-11 /pmc/articles/PMC5422196/ /pubmed/28398255 http://dx.doi.org/10.3390/s17040835 Text en © 2017 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 Chang, Xiaodong Huang, Jinquan Lu, Feng Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers |
title | Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers |
title_full | Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers |
title_fullStr | Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers |
title_full_unstemmed | Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers |
title_short | Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers |
title_sort | robust in-flight sensor fault diagnostics for aircraft engine based on sliding mode observers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422196/ https://www.ncbi.nlm.nih.gov/pubmed/28398255 http://dx.doi.org/10.3390/s17040835 |
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