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...

Full description

Bibliographic Details
Main Authors: Liansheng Liu, Qing Guo, Lulu Wang, Datong Liu
Format: Article
Language:English
Published: SAGE Publishing 2020-03-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814020911475
id doaj-37ec0379de524a5095efceba3f36db22
record_format Article
spelling 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
work_keys_str_mv AT lianshengliu insituremainingusefullifepredictionofaircraftauxiliarypowerunitbasedonquantitativeanalysisofonwingsensingdata
AT qingguo insituremainingusefullifepredictionofaircraftauxiliarypowerunitbasedonquantitativeanalysisofonwingsensingdata
AT luluwang insituremainingusefullifepredictionofaircraftauxiliarypowerunitbasedonquantitativeanalysisofonwingsensingdata
AT datongliu insituremainingusefullifepredictionofaircraftauxiliarypowerunitbasedonquantitativeanalysisofonwingsensingdata
_version_ 1724472909087375360