Degradation reliability modeling based on an independent increment process with quadratic variance

Zhihua Wang, Yongbo Zhang*, Qiong Wu, Huimin Fu, Chengrui Liu, Sridhar Krishnaswamy

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Degradation testing is an important technique for assessing life time information of complex systems and highly reliable products. Motivated by fatigue crack growth (FCG) data and our previous study, this paper develops a novel degradation modeling approach, in which degradation is represented by an independent increment process with linear mean and general quadratic variance functions of test time or transformed test time if necessary. Based on the constructed degradation model, closed-form expressions of failure time distribution (FTD) and its percentiles can be straightforwardly derived and calculated. A one-stage method is developed to estimate model parameters and FTD. Simulation studies are conducted to validate the proposed approach, and the results illustrate that the approach can provide reasonable estimates even for small sample size situations. Finally, the method is verified by the FCG data set given as the motivating example, and the results show that it can be considered as an effective degradation modeling approach compared with the multivariate normal model and graphic approach.

Original languageEnglish (US)
Pages (from-to)467-483
Number of pages17
JournalMechanical Systems and Signal Processing
Volume70-71
DOIs
StatePublished - Mar 1 2016

Keywords

  • Degradation test
  • Failure time distribution
  • Independent increment process
  • One-stage parameter estimation
  • Quadratic variance function
  • Reliability analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Degradation reliability modeling based on an independent increment process with quadratic variance'. Together they form a unique fingerprint.

Cite this