Automatic defect recognition for pulsed terahertz inspection of basalt fiber reinforced composites

Abstract

Purpose

The purpose of this paper is to present a system for automatic recognition of defects detected in non-conductive polymer composites using pulsed terahertz imaging.

Design/methodology/approach

On the beginning, non-destructive evaluation of composites using electromagnetic waves in terahertz frequency is shortly introduced. Next automatic defects recognition (ADR) algorithm is proposed, focussing on new features calculation. Dimensionality of features space is reduced by using principal component analysis. Finally, results of basalt fiber reinforced composite materials inspection and identification using artificial neural networks is presented and discussed.

Findings

It is possible to develop ADR system for non-destructive evaluation of dielectric materials using pulsed terahertz technique. New set of features in time and frequency domains is proposed and verified.

Originality/value

ADR in non-destructive testing is utilized in case of digital radiography and ultrasonic testing. Terahertz inspection with pulsed excitation is reported as a source of many useful information about the internal structure of the dielectric material. Up to now ADR based on terahertz non-destructive evaluation systems was not utilized.

Citation

Lopato, P. (2016), "Automatic defect recognition for pulsed terahertz inspection of basalt fiber reinforced composites", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 35 No. 4, pp. 1346-1359. https://doi.org/10.1108/COMPEL-09-2015-0351