On Construction of Early Warning Systems for Predictive Maintenance in Aerospace Industry

被引：5
作者：
Burnaev, E. V. [1 ,2 ]
机构：
[1] Skolkovo Inst Sci & Technol, Moscow, Russia
[2] Inst Informat Transmiss Problems, Moscow, Russia
来源：
JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS | 2019年 / 64卷 / 12期
基金：
俄罗斯基础研究基金会;
关键词：
monitoring system; anomaly detection; failure prediction; machine learning; predictive maintenance; signal processing;
D O I：
10.1134/S1064226919120027
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 problem of constructing predictive models for early warning systems for diagnostic maintenance in the aerospace industry is considered. A new approach to predicting rare failures based on a new methodology that takes into account the properties of technical systems and specific requirements imposed by applications is proposed.
引用
收藏
页码：1473 / 1484
页数：12
相关论文
共 44 条
[1]  
Alestra Stephane, 2014, Advanced Materials Research, V1016, P413, DOI 10.4028/www.scientific.net/AMR.1016.413
[2]  
Alestra S., 2014, P JOINT WCCM ECCM EC, P1
[3]  
[Anonymous], 2015, P SPIE
[4]  
[Anonymous], 2018, CONFORMAL PROBABILIS
[5]  
[Anonymous], 2015, MAINT OPT
[6]  
[Anonymous], 2015, P SPIE
[7]   OPTIMAL ESTIMATION OF A SIGNAL PERTURBED BY A FRACTIONAL BROWNIAN NOISE [J].
Artemov, A. V. ;
Burnaev, E. V. .
THEORY OF PROBABILITY AND ITS APPLICATIONS, 2016, 60 (01) :126-U239
[8]  
Artemov A, 2016, INT CONF DAT MIN WOR, P29, DOI [10.1109/ICDMW.2016.133, 10.1109/ICDMW.2016.0013]
[9]   Nonparametric Decomposition of Quasi-periodic Time Series for Change-point Detection [J].
Artemov, Alexey ;
Burnaev, Evgeny ;
Lokot, Andrey .
EIGHTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2015), 2015, 9875
[10]   Forecasting fault events for predictive maintenance using data-driven techniques and ARMA modeling [J].
Baptista, Marcia ;
Sankararaman, Shankar ;
de Medeiros, Ivo. P. ;
Nascimento, Cairo, Jr. ;
Prendinger, Helmut ;
Henriques, Elsa M. P. .
COMPUTERS & INDUSTRIAL ENGINEERING, 2018, 115 :41-53
12345