The Use of Phase Quadrature Information for the Automated Detection and Classification of Defects in the Presence of Deterministic Noise
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Begun in 1973, the Review of Progress in Quantitative Nondestructive Evaluation (QNDE) is the premier international NDE meeting designed to provide an interface between research and early engineering through the presentation of current ideas and results focused on facilitating a rapid transfer to engineering development.
This site provides free, public access to papers presented at the annual QNDE conference between 1983 and 1999, and abstracts for papers presented at the conference since 2001.
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Abstract
This paper describes the application of a neural network which was developed to perform a complex mapping [1]. The network utilizes phase quadrature information by, essentially, embedding the impedance plane representation in a network structure. The focus is on the implementation of the network in an automated inspection environment for the detection and classification of defects in the presence of severe deterministic noise arising from grain boundaries, machining grooves, and geometric discontinuities. We then go on to describe the possible use of chaotic oscillations for enhanced defect detection and the eventual marriage of chaotic oscillator phase plane data and the neural network for automated pattern recognition.