Title :
Remaining useful life prognostic estimation for aircraft subsystems or components: A review
Author :
Xiongzi, Chen ; Jinsong, Yu ; Diyin, Tang ; Yingxun, Wang
Author_Institution :
Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China
Abstract :
The techniques of remaining useful life (RUL) estimation are playing a more and more important role in aircraft safety and condition based maintenance. This paper gives an overview of RUL prognostic estimation approaches applied to aircraft subsystems or components. Existing RUL estimation approaches are categorized into three types, namely model-based approaches, data-driven approaches and fusion approaches and their characteristics are comprehensively introduced. Moreover, three common and promising methods: particle filtering, neural network and relevant vector machine as well as their advantages and disadvantages are discussed in details. Finally, the future challenges concerned with RUL prediction are also presented.
Keywords :
aerospace computing; aircraft instrumentation; aircraft maintenance; neural nets; particle filtering (numerical methods); RUL prognostic estimation; aircraft components; aircraft safety; aircraft subsystems; condition based maintenance; neural network; particle filtering; remaining useful life prognostic estimation; vector machine; Aerospace electronics; Aircraft; Aircraft propulsion; Atmospheric modeling; Estimation; Hidden Markov models; Predictive models; aircraft component; fusion approach; prognostic estimation; remaining useful life;
Conference_Titel :
Electronic Measurement & Instruments (ICEMI), 2011 10th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-8158-3
DOI :
10.1109/ICEMI.2011.6037773