Aircraft APU failure rate prediction based on improved Weibull-based GRP

Yujie Zhang, Yu Peng, Peng Wang, Lulu Wang, Shaonian Wang, Haitao Liao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Auxiliary Power Unit (APU) is an essential component of civil aircraft. In order to meet demands for aircraft APU maintenance, failure rate of aircraft APU should be predicted. Since aircraft APU is a repairable system, its performance degradation can be considered as a Generalized Renewal Process (GRP). Therefore, aircraft APU failure rate prediction can be implemented by utilizing Weibull-based GRP. However, Aircraft APU maintenance effect which is required in Weibull-based GRP is difficult to quantify. In order to solve this problem, an improved Weibull-based Generalized Renewal Process (IWGRP) model is proposed in this work. To be specific, utilizing some key test parameters after repairs, aircraft APU maintenance effect is estimated. Based on aircraft APU maintenance effect, conditional failure rate and hazard rate of aircraft APU can be obtained. Then, conditional failure rate and hazard rate are utilized to predict aircraft APU failure rate. Finally, the performance of IWGRP is validated by real data from China Southern Airlines (CSA). Experiment results demonstrate that IWGRP is suitable for aircraft APU failure rate prediction.

Original languageEnglish (US)
Title of host publication2017 Prognostics and System Health Management Conference, PHM-Harbin 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538603703
DOIs
StatePublished - Oct 20 2017
Externally publishedYes
Event8th IEEE Prognostics and System Health Management Conference, PHM-Harbin 2017 - Harbin, China
Duration: Jul 9 2017Jul 12 2017

Other

Other8th IEEE Prognostics and System Health Management Conference, PHM-Harbin 2017
CountryChina
CityHarbin
Period7/9/177/12/17

Keywords

  • aircraft APU
  • Condition-based maintenance
  • degradation
  • Failure Rate Prediction
  • Repairable systems
  • Weibull-based GRP

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Transportation

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  • Cite this

    Zhang, Y., Peng, Y., Wang, P., Wang, L., Wang, S., & Liao, H. (2017). Aircraft APU failure rate prediction based on improved Weibull-based GRP. In 2017 Prognostics and System Health Management Conference, PHM-Harbin 2017 - Proceedings [8079158] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PHM.2017.8079158