Probabilistic fatigue life prediction of composite laminates using Bayesian updating

Tishun Peng, Yongming Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


In this paper, the general framework for composite fatigue life prediction is proposed that can incorporate the detected stiffness from structural health monitoring system. First, an in-situ composite fatigue testing with pre-installed piezoelectric sensors is designed and performed to collected sensor signal and overall stiffness measurement. Signal processing techniques are implemented to extract damage identification features. Following this, power law is introduced to express the stiffness degradation mechanism and a general prognosis framework is proposed. Next, the detected overall stiffness degradation is integrated with a Bayesian inference framework for remaining useful life (RUL) prediction. The prognosis performance is validated using prognostics metric. Finally, some conclusions based this work are presented and directions for future work are drawn.

Original languageEnglish (US)
Title of host publication17th AIAA Non-Deterministic Approaches Conference
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
ISBN (Electronic)9781624103476
StatePublished - 2015
Event17th AIAA Non-Deterministic Approaches Conference 2015 - Kissimmee, United States
Duration: Jan 5 2015Jan 9 2015

Publication series

Name17th AIAA Non-Deterministic Approaches Conference


Other17th AIAA Non-Deterministic Approaches Conference 2015
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Architecture
  • Civil and Structural Engineering
  • Mechanics of Materials
  • Building and Construction


Dive into the research topics of 'Probabilistic fatigue life prediction of composite laminates using Bayesian updating'. Together they form a unique fingerprint.

Cite this