A probabilistic detectability-based structural sensor network design methodology for prognostics and health management

Pingfeng Wang, Byeng D. Youn, Chao Hu

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

Abstract

Significant technological advances in sensing and communication promote the use of large sensor networks to monitor structural systems, identify damages, and quantify damage levels. Prognostics and health management (PHM) technique has been developed and applied for a variety of safety-critical engineering structures, given the critical needs of the structure health state awareness. The PHM performance highly relies on real-time sensory signals which convey the structural health relevant information. Designing an optimal structural sensor network (SN) with high detectability is thus of great importance to the PHM performance. This paper proposes a generic SN design framework using a detectability measure while accounting for uncertainties in material properties and geometric tolerances. Detectability is defined to quantify the performance of a given SN. Then, detectability analysis will be developed based on structural simulations and health state classification. Finally, the generic SN design framework can be formulated as a mixed integer nonlinear programming (MINLP) using the detectability measure and genetic algorithms (GAs) will be employed to solve the SN design optimization problem. A power transformer study will be used to demonstrate the feasibility of the proposed generic SN design methodology.

Original languageEnglish (US)
Title of host publicationAnnual Conference of the Prognostics and Health Management Society, PHM 2010
PublisherPrognostics and Health Management Society
ISBN (Electronic)9781936263011
StatePublished - Jan 1 2010
Externally publishedYes
EventAnnual Conference of the Prognostics and Health Management Society, PHM 2010 - Portland, United States
Duration: Oct 13 2010Oct 16 2010

Publication series

NameAnnual Conference of the Prognostics and Health Management Society, PHM 2010

Other

OtherAnnual Conference of the Prognostics and Health Management Society, PHM 2010
CountryUnited States
CityPortland
Period10/13/1010/16/10

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Health Information Management
  • Computer Science Applications
  • Software

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  • Cite this

    Wang, P., Youn, B. D., & Hu, C. (2010). A probabilistic detectability-based structural sensor network design methodology for prognostics and health management. In Annual Conference of the Prognostics and Health Management Society, PHM 2010 (Annual Conference of the Prognostics and Health Management Society, PHM 2010). Prognostics and Health Management Society.