Probabilistic design of smart sensing functions for failure diagnostics and prognostics

Zequn Wang, Pingfeng Wang

Research output: Contribution to conferencePaper

Abstract

This paper presents a robust design framework to develop piezoelectric materials based structural sensing systems for failure diagnostics and prognostics. At first, a detectability measure is proposed to evaluate the performance of any given sensing system given varioaus uncertainties. Thus, the censoring system design problem can be formulated to maximize the detectability of the censoring system through optimally allocating piezoelectric materials into a target structural system. Secondly, the formulated problem can be conveniently solved using reliability-based robust design framework to ensure design robustness while considering the uncertainties. A rectangular plate is employed to demonstrate the effectiveness of the design framework in developing multifunctional material sensing systems.

Original languageEnglish (US)
StatePublished - Feb 28 2014
Externally publishedYes
Event16th AIAA Non-Deterministic Approaches Conference - SciTech Forum and Exposition 2014 - National Harbor, MD, United States
Duration: Jan 13 2014Jan 17 2014

Other

Other16th AIAA Non-Deterministic Approaches Conference - SciTech Forum and Exposition 2014
CountryUnited States
CityNational Harbor, MD
Period1/13/141/17/14

ASJC Scopus subject areas

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

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  • Cite this

    Wang, Z., & Wang, P. (2014). Probabilistic design of smart sensing functions for failure diagnostics and prognostics. Paper presented at 16th AIAA Non-Deterministic Approaches Conference - SciTech Forum and Exposition 2014, National Harbor, MD, United States.