Defect Identification in Composite Structures Using Enhanced Signal Analysis

Abstract

This project developed a new approach with theoretical and experimental framework to automatically and rapidly quantify invisible defects in a composite structure through enhanced analysis of data from ultrasonic non-destructive inspection methods. The objectives of this project were to develop rapid automated techniques to: Interrogate output from ultrasonic NDI equipment to identify the presence of defects, Identify the type of defect, in particular delamination, disbanding, foreign body inclusions and porosity and Characterize the damage with respect to its location and size. Theoretical framework consisted of stochastic defect identification under sensor uncertainties and rapid field inspection by optimally guiding and controlling sensors. The system constructed from this project has the following capabilities: Automated techniques to characterize defects; Technique that stochastically estimates the states of defects; Technique that allows active sensing; and Technique that enhances current signal analysis.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 07, 2011
Accession Number
ADA534985

Entities

People

  • Shen H. Lim
  • Tomonari Furukawa

Organizations

  • Virginia Tech

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Composite Materials
  • Composite Structures
  • Data Analysis
  • Data Science
  • Engineering
  • Filters
  • Identification
  • Information Science
  • Inspection
  • Kalman Filters
  • Materials
  • Measurement
  • Quality Control
  • Stochastic Processes
  • Test And Evaluation
  • Uncertainty
  • Wounds And Injuries

Readers

  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.
  • Materials Science and Engineering.