Modal Frequency Detection in Composite Beams Using Fiber Optic Sensors

Abstract

Extrinsic Fabry-Perot interferometric (EFPI) fiber optic sensors were used to determine the first five modal frequencies of laminated glass/epoxy composite beams. EFPI fiber optic sensors and piezoelectric (PZT) ceramic sensor both found identical modal frequencies of the composite beams, however, EFPI fiber optic sensors showed more sensitivity and better signal-to-noise ratios. The analytical classical beam theory and a finite element model validated the EFPI modal frequency measurements. Several 8-ply glass/epoxy composite beams, each 26.04 cm long and 2.33 cm wide were fabricated. Five damaged beams with specified delaminations as well as two different undamaged beams were tested for modal frequencies. Five different delaminations with sizes ranging from 1.27 cm to 6.35 cm long were incorporated in the midplane of the beams. Each modal frequency shifted with a change of delamination size and location. Classical beam theory was used to simulate modal frequency data sets for 1097 different prescribed delamination sizes and locations. These data sets were applied for training and testing a feedforward backpropagation neural network. Finally the neural network was tested against the EFPI fiber optic sensor modal frequency results. The delamination size and location predictions resulted from neural network's simulation had an average error of 5.9% and 4.7% respectively.

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Document Details

Document Type
Technical Report
Publication Date
Apr 18, 1997
Accession Number
ADA324039

Entities

People

  • Gilbert W. Sanders

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Analyzers
  • Ceramic Materials
  • Composite Material Fabrication
  • Composite Materials
  • Composite Structures
  • Detection
  • Detectors
  • Epoxy Composites
  • Failure Mode And Effect Analysis
  • Laminates
  • Material Degradation Processes
  • Materials
  • Materials Laboratories
  • Materials Processing
  • Materials Science
  • Signal Processing

Fields of Study

  • Physics

Readers

  • Computer Engineering
  • Optical Physics and Photonics.
  • Reinforced Composite Materials

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks