In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data
The in-situ prognostics and health management of aircraft auxiliary power unit faces difficulty using the sparse on-wing sensing data. As the key technology of prognostics and health management, remaining useful life prediction of in-situ aircraft auxiliary power unit is hard to achieve accurate res...
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Series: | Advances in Mechanical Engineering |
Online Access: | https://doi.org/10.1177/1687814020911475 |
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doaj-37ec0379de524a5095efceba3f36db222020-11-25T03:54:35ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402020-03-011210.1177/1687814020911475In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing dataLiansheng Liu0Qing Guo1Lulu Wang2Datong Liu3School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, ChinaSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, ChinaChina Southern Airlines Engineering Technology Research Center, Shenyang, ChinaSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, ChinaThe in-situ prognostics and health management of aircraft auxiliary power unit faces difficulty using the sparse on-wing sensing data. As the key technology of prognostics and health management, remaining useful life prediction of in-situ aircraft auxiliary power unit is hard to achieve accurate results. To solve this problem, we propose one kind of quantitative analysis of its on-wing sensing data to implement remaining useful life prediction of auxiliary power unit. Except the most important performance parameter exhaust gas temperature , the other potential parameters are utilized based on mutual information, which can be used as the quantitative metric. In this way, the quantitative threshold of mutual information for enhancing remaining useful life prediction result can be determined. The implemented cross-validation experiments verify the effectiveness of the proposed method. The real on-wing sensing data of auxiliary power unit for experiment are from China Southern Airlines Company Limited Shenyang Maintenance Base, which spends over $6.5 million on auxiliary power unit maintenance and repair each year for the fleet of over 500 aircrafts. Although the relative improvement is not too large, it is helpful to reduce the maintenance and repair cost.https://doi.org/10.1177/1687814020911475 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Liansheng Liu Qing Guo Lulu Wang Datong Liu |
spellingShingle |
Liansheng Liu Qing Guo Lulu Wang Datong Liu In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data Advances in Mechanical Engineering |
author_facet |
Liansheng Liu Qing Guo Lulu Wang Datong Liu |
author_sort |
Liansheng Liu |
title |
In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data |
title_short |
In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data |
title_full |
In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data |
title_fullStr |
In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data |
title_full_unstemmed |
In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data |
title_sort |
in-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data |
publisher |
SAGE Publishing |
series |
Advances in Mechanical Engineering |
issn |
1687-8140 |
publishDate |
2020-03-01 |
description |
The in-situ prognostics and health management of aircraft auxiliary power unit faces difficulty using the sparse on-wing sensing data. As the key technology of prognostics and health management, remaining useful life prediction of in-situ aircraft auxiliary power unit is hard to achieve accurate results. To solve this problem, we propose one kind of quantitative analysis of its on-wing sensing data to implement remaining useful life prediction of auxiliary power unit. Except the most important performance parameter exhaust gas temperature , the other potential parameters are utilized based on mutual information, which can be used as the quantitative metric. In this way, the quantitative threshold of mutual information for enhancing remaining useful life prediction result can be determined. The implemented cross-validation experiments verify the effectiveness of the proposed method. The real on-wing sensing data of auxiliary power unit for experiment are from China Southern Airlines Company Limited Shenyang Maintenance Base, which spends over $6.5 million on auxiliary power unit maintenance and repair each year for the fleet of over 500 aircrafts. Although the relative improvement is not too large, it is helpful to reduce the maintenance and repair cost. |
url |
https://doi.org/10.1177/1687814020911475 |
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