QUALITY MONITORING IN MASS PRODUCTION OF MULTIAXIAL NON-CRIMP FABRICS BY USING A MULTISENSOR SYSTEM

Robert Schmitt, Tobias Fürtjes, Walter Kimmelmann, Philipp Kosse, Andrea Buratti

Abstract

Due to their excellent mechanical properties and light weight, fiber-reinforced plastic (FRP) has a huge potential as a way to reduce vehicle and airplane weight and is therefore a subject of interest for aerospace and automotive industries. To mass-produce FRP products, certain textile structures are commonly used as semifinished products, such as multiaxial non-crimp fabrics (NCF). Currently, there is no automated monitoring system capable of ensuring quality in NCF production. The purpose of this study is to develop tools and concepts that could lead to fully-automated quality control of non-crimp fabrics. Useful sensor concepts were developed based on a thorough requirement analysis. Sensor data fusion strategies were conceived and evaluated to combine image processing information and basis weight sensor information with the purpose of detecting relevant quality features in a textile sample. The developed algorithm was tested on a textile sample and a corresponding defect map was generated. Results showed that it is possible to identify common textile defect types by combining these two sensors.

Keywords

sensor data fusion, fiber-reinforced plastics, quality control, image processing, radiography

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IMEKO-WC-2015-TC21-384.pdf

DOI

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IMEKO TC

TC21 - Mathematical Tools for Measurements

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