Neural network representation of fatigue damage dynamics

Chen Jung Li, A. Ray

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Recently, a model of fatigue damage dynamics has been reported (Ray et al., 1994), which allows the damage information on critical plant components to be integrated with the plant dynamics for both online life prediction and offline control synthesis. This paper proposes a neural network implementation of the fatigue damage model in order to alleviate the problem of slow computation via conventional numerical methods. The results of simulation experiments reveal that a neural network algorithm could be used as an intelligent instrument for online monitoring of fatigue damage and also as a tool for failure prognostics and service life prediction.

Original languageEnglish (US)
Article number009
Pages (from-to)126-133
Number of pages8
JournalSmart Materials and Structures
Volume4
Issue number2
DOIs
StatePublished - 1995

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Civil and Structural Engineering
  • Atomic and Molecular Physics, and Optics
  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanics of Materials
  • Electrical and Electronic Engineering

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