In-process fault detection for textile fabric production: onloom imaging

Florian Neumann; Timm Holtermann; Dorian Schneider; Ashley Kulczycki; Thomas Gries; Til Aach

doi:10.1117/12.889345

27 May 2011 In-process fault detection for textile fabric production: onloom imaging

Florian Neumann, Timm Holtermann, Dorian Schneider, Ashley Kulczycki, Thomas Gries, Til Aach

Proceedings Volume 8082, Optical Measurement Systems for Industrial Inspection VII; 808240 (2011) https://doi.org/10.1117/12.889345
Event: SPIE Optical Metrology, 2011, Munich, Germany

Abstract

Constant and traceable high fabric quality is of high importance both for technical and for high-quality conventional fabrics. Usually, quality inspection is carried out by trained personal, whose detection rate and maximum period of concentration are limited. Low resolution automated fabric inspection machines using texture analysis were developed. Since 2003, systems for the in-process inspection on weaving machines ("onloom") are commercially available. With these defects can be detected, but not measured quantitative precisely. Most systems are also prone to inevitable machine vibrations. Feedback loops for fault prevention are not established. Technology has evolved since 2003: Camera and computer prices dropped, resolutions were enhanced, recording speeds increased. These are the preconditions for real-time processing of high-resolution images. So far, these new technological achievements are not used in textile fabric production. For efficient use, a measurement system must be integrated into the weaving process; new algorithms for defect detection and measurement must be developed. The goal of the joint project is the development of a modern machine vision system for nondestructive onloom fabric inspection. The system consists of a vibration-resistant machine integration, a high-resolution machine vision system, and new, reliable, and robust algorithms with quality database for defect documentation. The system is meant to detect, measure, and classify at least 80 % of economically relevant defects. Concepts for feedback loops into the weaving process will be pointed out.

Citation Download Citation

Florian Neumann, Timm Holtermann, Dorian Schneider, Ashley Kulczycki, Thomas Gries, and Til Aach "In-process fault detection for textile fabric production: onloom imaging", Proc. SPIE 8082, Optical Measurement Systems for Industrial Inspection VII, 808240 (27 May 2011); https://doi.org/10.1117/12.889345

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