TY - GEN
T1 - Aircraft APU failure rate prediction based on improved Weibull-based GRP
AU - Zhang, Yujie
AU - Peng, Yu
AU - Wang, Peng
AU - Wang, Lulu
AU - Wang, Shaonian
AU - Liao, Haitao
N1 - Funding Information:
This work was partially supported by National Natural Science Foundation of China under Grant No. 61571160 and the New Direction of Subject Development in Harbin Institute of Technology under Grant No. 01509421.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/20
Y1 - 2017/10/20
N2 - 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.
AB - 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.
KW - Condition-based maintenance
KW - Failure Rate Prediction
KW - Repairable systems
KW - Weibull-based GRP
KW - aircraft APU
KW - degradation
UR - http://www.scopus.com/inward/record.url?scp=85039970855&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85039970855&partnerID=8YFLogxK
U2 - 10.1109/PHM.2017.8079158
DO - 10.1109/PHM.2017.8079158
M3 - Conference contribution
AN - SCOPUS:85039970855
T3 - 2017 Prognostics and System Health Management Conference, PHM-Harbin 2017 - Proceedings
BT - 2017 Prognostics and System Health Management Conference, PHM-Harbin 2017 - Proceedings
A2 - Zhang, Bin
A2 - Peng, Yu
A2 - Liao, Haitao
A2 - Liu, Datong
A2 - Wang, Shaojun
A2 - Miao, Qiang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE Prognostics and System Health Management Conference, PHM-Harbin 2017
Y2 - 9 July 2017 through 12 July 2017
ER -