Degradation data analysis using wiener processes with measurement errors

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

  • Zhi-Sheng Ye
  • Yu Wang
  • Kwok-Leung Tsui
  • Michael Pecht

Detail(s)

Original languageEnglish
Article number6632957
Pages (from-to)772-780
Journal / PublicationIEEE Transactions on Reliability
Volume62
Issue number4
Online published17 Oct 2013
Publication statusPublished - Dec 2013

Abstract

Degradation signals that reflect a system's health state are important for diagnostics and health management of complex systems. However, degradation signals are often compounded and contaminated by measurement errors, making data analysis a difficult task. Motivated by the wear problem of magnetic heads used in hard disk drives (HDDs), this paper investigates Wiener processes with measurement errors. We explore the traditional Wiener process with positive drifts compounded with i.i.d. Gaussian noises, and improve its estimation efficiency compared with the existing inference procedure. Furthermore, to capture the possible heterogeneity in a population, we develop a mixed effects model with measurement errors. Statistical inferences of this model are discussed. The mixed effects model subsumes several existing Wiener processes as its limiting cases, and thus it is useful for suggesting an appropriate Wiener process model for a specific dataset. The developed methodologies are then applied to the wear problem of magnetic heads of HDDs, and a light intensity degradation problem of light-emitting diodes. © 1963-2012 IEEE.

Research Area(s)

  • Embedded model, Random effects, Wear data

Citation Format(s)

Degradation data analysis using wiener processes with measurement errors. / Ye, Zhi-Sheng; Wang, Yu; Tsui, Kwok-Leung et al.
In: IEEE Transactions on Reliability, Vol. 62, No. 4, 6632957, 12.2013, p. 772-780.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review