Building degradation index with variable selection for multivariate sensory data

Yueyao Wang, I-Chen Lee, Yili Hong and Xinwei Deng

Reliability Engineering and System Safety, 2022, vol. 227, issue C

Abstract: The modeling and analysis of degradation data have been an active research area in reliability engineering for reliability assessment and system health management. As the sensor technology advances, multivariate sensory data are commonly collected for the underlying degradation process. However, most existing research on degradation modeling requires a univariate degradation index to be provided. Thus, constructing a degradation index for multivariate sensory data is a fundamental step in degradation modeling. In this paper, we propose a novel degradation index building method for multivariate sensory data with censoring. Based on an additive nonlinear model with variable selection, the proposed method can handle censored data, and can automatically select the informative sensor signals to be used in the degradation index. The penalized likelihood method with adaptive group penalty is developed for parameter estimation. We demonstrate that the proposed method outperforms existing methods via both simulation studies and analyses of the NASA jet engine sensor data.

Keywords: Adaptive LASSO; General path model; Prognostics; Sensor selection; Splines; System health monitoring (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832022003295
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:227:y:2022:i:c:s0951832022003295

DOI: 10.1016/j.ress.2022.108704

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().