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Fast FMCW Terahertz Imaging for In-Process Defect Detection in Press Sleeves for the Paper Industry and Image Evaluation with a Machine Learning Approach

Authors :
Fabian Friederich
Raphael Hussung
Carsten Matheis
Joachim Jonuscheit
Maris Bauer
Uwe Matuschczyk
Peter Weichenberger
Jens Beck
Hermann Reichert
Publica
Source :
Sensors (Basel, Switzerland), Sensors, Volume 21, Issue 19, Sensors, Vol 21, Iss 6569, p 6569 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

We present a rotational terahertz imaging system for inline nondestructive testing (NDT) of press sleeves for the paper industry during fabrication. Press sleeves often consist of polyurethane (PU) which is deposited by rotational molding on metal barrels and its outer surface mechanically processed in several milling steps afterwards. Due to a stabilizing polyester fiber mesh inlay, small defects can form on the sleeveā€™s backside already during the initial molding, however, they cannot be visually inspected until the whole production processes is completed. We have developed a fast-scanning frequenc-modulated continuous wave (FMCW) terahertz imaging system, which can be integrated into the manufacturing process to yield high resolution images of the press sleeves and therefore can help to visualize hidden structural defects at an early stage of fabrication. This can save valuable time and resources during the production process. Our terahertz system can record images at 0.3 and 0.5 THz and we achieve data acquisition rates of at least 20 kHz, exploiting the fast rotational speed of the barrels during production to yield sub-millimeter image resolution. The potential of automated defect recognition by a simple machine learning approach for anomaly detection is also demonstrated and discussed.

Details

ISSN :
14248220
Volume :
21
Database :
OpenAIRE
Journal :
Sensors
Accession number :
edsair.doi.dedup.....b87e31c6cdd0d862b3f9bd8ffd855704