Paper Info
Title
An Adaptive Prognostic Approach for Newly Developed System With Three-Source Variability
Abstract
Remaining useful life (RUL) estimation is the key of prognostics and health management (PHM) technology and is an effective way to ensure the safe and reliable operation of equipment. Aiming at the lack of historical data and prior information for the newly developed small-sample systems, an adaptive RUL estimation method based on the expectation maximization (EM) algorithm is proposed with three-source variability. First, a degradation model based on a Wiener process is established to incorporate three-source variability and dynamic sampling interval, and the analytical solution of RUL distribution is derived in the sense of the first hitting time. Second, an adaptive parameter estimation method based on the EM algorithm is proposed to update the model parameters by using the condition monitoring (CM) data from one working system running up to the current moment. Finally, a practical example of a gyroscope in an inertial navigation system is provided to substantiate the effectiveness and superiority of the proposed method. The results indicate that the proposed method can efficiently improve the accuracy of the RUL estimation.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2911307
IEEE ACCESS
Keywords
Field
DocType
Remaining useful life,three-source variability,expectation maximization,dynamic sampling interval
Wiener process,Inertial navigation system,Gyroscope,Prognostics,Expectation–maximization algorithm,Computer science,Real-time computing,Condition monitoring,Estimation theory,Hitting time,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Xi Wang14712.80
C. H. Chang242836.69
Xiao-Sheng Si362346.17
Jian-Fei Zheng493.18
Hong Pei512.05
Yong Yu6393.86
Ziqiang Ren700.34