Fault classification using pseudomodal energies and probabilistic neural networks

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8 Citations (Scopus)

Abstract

This paper introduces a new fault identification method that uses pseudomodal energies to train probabilistic neural networks (PNNs). The proposed procedure is tested on a population of 20 cylindrical shells and its performance is compared to the procedure which uses modal properties to train probabilistic neural networks. The PNNs trained using pseudomodal energies provide better classification of faults than the PNNs trained using the conventional modal properties.

Original languageEnglish
Pages (from-to)1346-1355
Number of pages10
JournalJournal of Engineering Mechanics - ASCE
Volume130
Issue number11
DOIs
Publication statusPublished - Nov 2004
Externally publishedYes

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering

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