Performance Assessment of APU Based on Degradation Enhancement With On-Wing Sensing Data

被引:0
|
作者
Liu, Xiaolei [1 ]
Liu, Liansheng [1 ]
Wang, Lulu [2 ,3 ]
Peng, Xiyuan [1 ]
Liu, Datong [1 ]
机构
[1] Harbin Inst Technol, Zhengzhou Res Inst, Sch Elect & Informat Engn, Harbin 150080, Peoples R China
[2] China Southern Airlines Co Ltd, Shenyang Maintenance Base, Shenyang 110169, Peoples R China
[3] China Southern Airlines Engn Technol Res Ctr, Shenyang 110169, Peoples R China
关键词
Feature extraction; Sensors; Aircraft propulsion; Degradation; Aircraft; Maintenance; Long short term memory; Airline industry; Data mining; Safety; Auxiliary power unit (APU); degradation feature; on-wing sensing data; performance assessment; USEFUL LIFE PREDICTION; HEALTH INDEXES; FUSION;
D O I
10.1109/JSEN.2025.3539759
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The aircraft auxiliary power unit (APU) is a small turbine engine that provides power and air sources for the aircraft. Its main role is to help start the main engine and provide electric power to the aircraft. The accurate performance assessment (PA) of on-wing APUs can help improve the safety of APUs while reducing unnecessary maintenance costs for airlines. Due to the hostile operating environment and working conditions, the performance parameters are affected greatly. It is difficult to conduct the PA for on-wing APU. In this article, a multiparameter PA approach based on degradation feature enhancement is proposed to fulfill the PA of on-wing APU. First, an adaptive feature extraction variational mode decomposition is proposed to extract the degradation features from the on-wing sensing data and obtain a feature set of the monitored parameters. Then, the extracted degradation features are fused through a long short-term memory (LSTM) network for achieving PA. To evaluate the effectiveness of the proposed method, experiments are conducted based on real on-wing sensing data from airlines. The PA results show that the proposed approach can obtain better PA results.
引用
收藏
页码:11460 / 11470
页数:11
相关论文
共 50 条
  • [41] Machine Performance Degradation Assessment based on PCA-FCMAC
    Zhang Lei
    Cao Qixin
    ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 2, PROCEEDINGS, 2008, : 443 - 447
  • [42] Bearing performance degradation assessment based on optimized EWT and CNN
    Hu, Mantang
    Wang, Guofeng
    Ma, Kaile
    Cao, Zenghuan
    Yang, Shuai
    MEASUREMENT, 2021, 172
  • [43] Performance Degradation Assessment of Rolling Bearings Based on OLPP and SVDD
    Zhang Jinbao
    Zou Tiangang
    Li Xinglin
    Gui Peng
    2020 5TH INTERNATIONAL CONFERENCE ON MECHANICAL, CONTROL AND COMPUTER ENGINEERING (ICMCCE 2020), 2020, : 289 - 294
  • [44] Bearing performance degradation assessment based on the contact stress and deformation
    Hu Qingzhong
    Chu Fulei
    Proceedings of the 2016 3rd International Conference on Mechatronics and Information Technology (ICMIT), 2016, 49 : 471 - 476
  • [45] Remote sensing and GIS-based assessment of urbanisation and degradation of watershed health
    Jat, M. K.
    Khare, D.
    Garg, P. K.
    Shankar, V.
    URBAN WATER JOURNAL, 2009, 6 (03) : 251 - 263
  • [46] A remote sensing and GIS based study in assessment of the degradation risk of the Kolonnawa marsh
    Samarasinghe, Y. M. P.
    Dayawansa, N. D. K.
    JOURNAL OF THE NATIONAL SCIENCE FOUNDATION OF SRI LANKA, 2013, 41 (04): : 327 - 335
  • [47] Bearing performance degradation assessment and remaining useful life prediction based on data-driven and physical model
    Sheng, Yuanyuan
    Liu, Huanyu
    Li, Junbao
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2023, 34 (05)
  • [48] Rolling bearing performance degradation assessment based on deep belief network and improved support vector data description
    Pan, Yuna
    Cheng, Daolai
    Wei, Tingting
    Jia, Yuchen
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 181
  • [49] A Terahertz Metamaterial Sensor Based on Dual Resonant Mode and Enhancement of Sensing Performance
    Guo, Shijing
    Li, Chao
    Wang, Dong
    Chen, Wenya
    Gao, Song
    Wu, Guozheng
    Xiong, Jiaran
    PLASMONICS, 2024, 19 (04) : 2223 - 2231
  • [50] Enhancement of the Sensing Performance of Devices based on Multistimuli-Responsive Hybrid Materials
    Abu Ali, Taher
    Anzengruber, Marlene
    Unger, Katrin
    Stadlober, Barbara
    Coclite, Anna Maria
    ACS APPLIED MATERIALS & INTERFACES, 2023, 16 (45) : 61408 - 61418