Integrated Sensor System for Monitoring the Braiding Process as a Use Case for Digitalization in Composite Production Technology

Defects that occur during braiding of reinforcement fibers can lead to a deterioration in mechanical strength of the finished parts as well as to a significant machine downtime. In order to minimize the effects of defects, production errors need to be detected as early as possible. Current sensor systems for defect detection however come with drawbacks of either late response times or high installation effort and costs. The goal of the thesis at hand is to develop new types of sensor systems that are, on the one hand, cost-efficient while, on the other hand, able to detect defects early during their formation. Firstly, stationary Hall sensors that detect the orientation of the lever of the yarn tensioning unit of the bobbin carriers that pass by the sensors are introduced (discrete-time measurement). In contrast to commercially available systems, the Hall sensors are able to detect even early stages of forming braiding defects well before a yarn breaks. Secondly, sensor integrated braiding rings for estimating the resulting radial and axial forces acting onto the braiding ring are proposed as a methof of time continuous process monitoring. An artificlially intelligent algorithm is presented that allows a surveillance of the process without any false positive or false negative defect detections. Thirdly, a camera-based system including an image processing algorithm for measuring the distances between the braiding yarns in the braid formation zone and thereby the evenness of the formed braid is developed. Fourthly, a sensor integrated bobbin carrier including an energy harvesting module is proposed that generates electric energy from the movement of the carrier itself. By means of this approach, particularly fine process irregularities can be measured. It is demonstrated that the newly developed sensor systems can be retrofitted to existing braiding machines and thereby enhance machine productivity and improve quality assurance in existing production lines.