Automated detection of yarn orientation in 3D-draped carbon fiber fabrics and preforms from eddy current data

Significance Statement

In the production of lightweight fiber-reinforced plastics, it is of highest importance to ensure the correct orientation of the reinforcement fibers, since only the fibers bear the load in the final composite. The state-of-the-art production of fiber-reinforced plastics usually consists of a preforming step, in which several layers of textile are bonded and draped to a 3D shape. The 3D-draped preform is then infused with a resin, a process called resin transfer molding (RTM). During both preforming and infusion, fiber reorientation and forming defects can occur, which makes a quality control of these steps of high importance.

To analyze the fiber orientation in 3D-draped preforms and 3D composites, researchers have used different techniques such as optical measurement, ultrasonic inspection or high-resolution thermography. However, these techniques are limited in resolution or can only detect fiber orientation in the uppermost layer. These limitations can be overcome by using electrical inspection techniques, which can be readily applied to preforms and composites made of conductive carbon fibers. It has been shown in previous research, that high-frequency eddy current testing with frequencies in the MHz-range can detect the orientation of yarns and local defects under six or more layers of carbon fiber fabrics. Combining this non-destructive testing process with an automated data evaluation technique and an industrial robot for guiding the sensor over 3D surfaces, this process has the potential to serve as a tool for the quality inspection of the critical 3D draping step.

To realize this potential, German researchers developed an automated process to reconstruct the fiber orientation in 3D-draped textiles and preforms with eddy current scanning. A high-resolution eddy current sensor was mounted to an industrial six-axis robot, which scans the 3D surface. The researchers then developed an automated algorithm which extracts local yarn angles from the three-dimensional eddy current scan data by using a local Fast Fourier transform image analysis algorithm. From these local yarn angles, the paths of the yarns that make up the fabric were reconstructed. The work was published in the peer-reviewed journal Composites Part B.

To prove the feasibility of the process, the authors conducted several experiments with bi-diagonal [+45/-45] carbon fiber non-crimp fabrics. The fabrics were draped to a hemisphere and scanned with an eddy current sensor. Yarn paths for both the upper and the lower of the fabric were extracted, which shows an improvement over optical methods, which cannot track the yarn orientation in lower layers. Finally, the authors showed how this technique can be used to better understand the influence of process factors like blank-holder forces on the draping process, by comparing the yarn orientation extracted from several experiment with different process settings.

The improved and fully automated eddy current analysis technique successfully integrates research in non-destructive testing, robotics and data evaluation. It can serve as a tool for the quality control of the preforming process and for the production of light-weight carbon-fiber reinforced plastics, where the assurance of correct fiber orientation may lead to further weight-loss in cars, airplanes and sports vehicles. Finally, the authors point to the option of using the yarn path reconstruction to better understand the complex textile draping process and serve as a validation tool for textile draping simulations.

Acknowledgement

The joint research group consisted of researchers from the Institute of Textile Machinery and High Performance Material Technology (ITM), TU Dresden, the Fraunhofer Institute for Ceramic Technology and Systems, Material Diagnostic (IKTS), Dresden, the Electronic Packaging Laboratory (IAVT), TU Dresden and the corporations HTS GmbH, Coswig and SURAGUS GmbH, Dresden.

Part of the research was done within the IGF project 18428 BG/1 of the joint research group Forschungskuratorium Textil e.V., which was funded via the AiF in the context of the Program for the Endorsement of Industrial Collective Research and Development (IGF) by the Federal Ministry of Economics and Technology, following a resolution of the German parliament.  

Automated detection of yarn orientation in 3D-draped carbon fiber fabrics and preforms from eddy current data. Advances in Engineering

Automated detection of yarn orientation in 3D-draped carbon fiber fabrics and preforms from eddy current data. Advances in Engineering

Automated detection of yarn orientation in 3D-draped carbon fiber fabrics and preforms from eddy current data. Advances in Engineering

Journal Reference

Georg Bardl1, Andreas Nocke1, Chokri Cherif1, Matthias Pooch2, Martin Schulze2, Henning Heuer2,3, Marko Schiller4, Richard Kupke5, Marcus Klein5. Automated detection of yarn orientation in 3D-draped carbon fiber fabrics and preforms from eddy current data,  Composites Part B: Engineering, Volume 96, 2016, Pages 312–324.

Show Affiliations
  1. Institute of Textile Machinery and High Performance Material Technology (ITM), TU Dresden, Dresden, Germany.
  2. Fraunhofer Institute for Ceramic Technology and Systems, Material Diagnostic (IKTS-MD), Dresden, Germany.
  3. Electronic Packaging Laboratory, Chair of Sensor Systems for Non-Destructive Testing, TU Dresden, Dresden, Germany.
  4. HTS GmbH, Coswig, Germany.
  5. SURAGUS GmbH, Dresden, Germany.

 

 

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