Stochastic modeling and analysis of multiple nonlinear accelerated degradation processes through information fusion

Fuqiang Sun, Le Liu, Xiaoyang Li, Haitao Liao

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

Accelerated degradation testing (ADT) is an efficient technique for evaluating the lifetime of a highly reliable product whose underlying failure process may be traced by the degradation of the product’s performance parameters with time. However, most research on ADT mainly focuses on a single performance parameter. In reality, the performance of a modern product is usually characterized by multiple parameters, and the degradation paths are usually nonlinear. To address such problems, this paper develops a new s-dependent nonlinear ADT model for products with multiple performance parameters using a general Wiener process and copulas. The generalWiener process models the nonlinear ADT data, and the dependency among different degradation measures is analyzed using the copula method. An engineering case study on a tuner’s ADT data is conducted to demonstrate the effectiveness of the proposed method. The results illustrate that the proposed method is quite effective in estimating the lifetime of a product with s-dependent performance parameters.

Original languageEnglish (US)
Article number1242
JournalSensors (Switzerland)
Volume16
Issue number8
DOIs
StatePublished - Aug 6 2016
Externally publishedYes

Keywords

  • Accelerated degradation testing
  • Copulas
  • General wiener process
  • Multiple performance parameters
  • Nonlinearity
  • S-dependency

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Electrical and Electronic Engineering

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