Accession Number : ADP010224

Title :   Classification of Composite Defects Using the Signature Classification Development System

Corporate Author : JOHNS HOPKINS UNIV LAUREL MD APPLIED PHYSICS LAB

Personal Author(s) : Lin, Jeffrey S. ; Brown, Lawrence M. ; Lebowitz, Carol A.

PDF Url : ADP010224

Report Date : APR 1996

Pagination or Media Count : 11

Abstract : The Johns Hopkins University Applied Physics Laboratory and the Carderock Division of the Naval Surface Warfare Center are developing a Signature Classification Development System (SCDS) to transfer classification technology to nondestructive evaluation (NDE) field equipment. SCDS is a personal computer-based software tool-kit for developing classification algorithms. It includes support for digital signal processing, gating of the signatures, generation of feature vectors, and classification of vectors using artificial neural networks. SCDS successfully classifies ultrasonic signatures from defects in thick section, graphite/epoxy composite test panels. Seven test panels were fabricated with programmed defects embedded one-eighth or halfway into the panel. Six of the panels contain defects representing delaminations, porosity, and contaminations, and one panel serves as a reference standard. Ultrasonic signatures were recorded from the test panels using an ultrasonic C-scan system. SCDS was used to process the signatures and generate feature vectors for input to the artificial neural networks. The classifier achieved a 94% accuracy for one defect, and perfect accuracy for two other defects.

Descriptors :   *SYMPOSIA, *GRAPHITE EPOXY COMPOSITES, *GRAPHICAL USER INTERFACE, SIGNAL PROCESSING, DIGITAL SYSTEMS, NEURAL NETS, NONDESTRUCTIVE TESTING, TECHNOLOGY TRANSFER, ULTRASONICS, ARTIFICIAL INTELLIGENCE.

Subject Categories : Laminates and Composite Materials
      Computer Programming and Software
      Test Facilities, Equipment and Methods

Distribution Statement : APPROVED FOR PUBLIC RELEASE