Analiza degradacji z zastosowa niem nowego modelu procesu Wienera uwzględniającego błędy pomiarowe

Translated title of the contribution: A novel Wiener process model with measurement errors for degradation analysis

Zhihua Wang, Junxing Li, Yongbo Zhang, Huimin Fu, Chengrui Liu, Sridhar Krishnaswamy

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Degradation analysis can be used to assess reliability for complex systems and highly reliable products, because few or even no failures are expected in a reasonable life test span. In order to further our study on degradation analysis, an independent increment random process method with linear mean and standard deviation functions is presented to model practical degradation procedures. It is essentially a Wiener process method. Since measurement errors are often created by imperfect instruments, procedures and environments during degradation investigation, the measurement error is incorporated into the independent increment random process. Furthermore, statistical inferences of this model are discussed, and close forms of a product’s median life and percentile of the failure time distribution (FTD) are also derived. The proposed method is illustrated and verified in a comprehensive simulation study and two practice applications for storage disks and Infrared light-emitting diodes. Meanwhile, the time-transformed Wiener process model with measurement error is considered as a reference method. Comparisons show that the proposed model can provide reasonable results, even in considerably small sample size circumstance.

Translated title of the contributionA novel Wiener process model with measurement errors for degradation analysis
Original languagePolish
Pages (from-to)396-405
Number of pages10
JournalEksploatacja i Niezawodnosc
Issue number3
StatePublished - 2016


  • Independent increment process
  • Linear mean function
  • Linear standard deviation function
  • Measurement error
  • Performance degradation
  • Wiener process model

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering

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