A SENSOR DESIGN AND DATA ANALYSIS FOR AUTOMATIC DRUM BEATER WINDING
Editor: Christian Weber, Stephan Husung, Gaetano Cascini, Marco Cantamessa, Dorian Marjanovic, Monica Bordegoni
Author: Zhao, Yuchen; Johson, Teegan; Goh, Yee Mey
Institution: 1: Loughborough University, United Kingdom; 2: Cranfield University, United Kingdom
Section: Human Behaviour in Design, Design Education
In the percussion music industry, drum beater manufacturing requires a skilled operator to manually wind the beater with acrylic yarn. Tacit skill is used to control and adapt tension during the winding process of beater construction, which cannot be easily articulated. Consequently the operator has been unable to successfully pass the skill on. In order to overcome this problem, an investigation into automating the drum beater winding process has been initiated. An in-depth human task analysis was performed to identify the skill-, rule-, and knowledge-based tasks during the winding process. In this paper, the two key parameters, yarn tension and patting force reported by the human task analysis during the manual process are further studied. The patting force has been measured and analysed for the low-level control unit. A tension measurement sensor has been designed and substrate has been simulated. This sensor will be used to measure yarn tension during the manual winding process and further work will be carried out to analyse the results for tension control mechanism.