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  4. Development of a standardized data acquisition prototype for heterogeneous sensor environments as a basis for ML applications in pultrusion
 
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2024
Conference Paper
Title

Development of a standardized data acquisition prototype for heterogeneous sensor environments as a basis for ML applications in pultrusion

Abstract
Pultrusion of continuous fiber reinforced profiles has been state of the art for several decades. However, pultrusion in the production environment so far has no or only few sensor data in a heterogeneous sensor environment, has shortcomings in data quality (time synchronization, different formats, different sampling rates, sporadic disconnections and resulting data losses), and insufficient data processing methods are used for process control and optimization. Significant efficiency improvements would therefore still be possible in this respect. The question therefore arises as to how a data acquisition system can be designed that provides heterogeneous data in a standardized and reliable manner for data-based process development and optimization. The aim is therefore to develop a digitized and standardized data acquisition prototype for the continuous production of sustainable profile structures so flexible that the various components of the production line can be adaptively combined in a central data acquisition system. We have therefore screened and selected possible standardized transmission formats in combination with suitable low-cost data acquisition systems for a highly reliable and secure application area. The paper shows a profound concept for a data acquisition prototype based on different low cost control systems for the applicability and testability of the developed requirements regarding data acquisition, processing, and future storage.
Author(s)
Helfrich, Timo
Selfbits GmbH, Karlsruhe
Wilhelm, Michael Leander  orcid-logo
Fraunhofer-Institut für Chemische Technologie ICT  
Kuppler, Oliver
Selfbits GmbH, Karlsruhe
Rosenberg, Philipp  
Fraunhofer-Institut für Chemische Technologie ICT  
Henning, Frank  
Fraunhofer-Institut für Chemische Technologie ICT  
Mainwork
Machine Learning for Cyber-Physical Systems. Selected papers from the International Conference ML4CPS 2023  
Conference
International Conference Machine Learning for Cyber-Physical Systems 2023  
Open Access
DOI
10.1007/978-3-031-47062-2_10
Additional link
Full text
Language
English
Fraunhofer-Institut für Chemische Technologie ICT  
Keyword(s)
  • pultrusion

  • data acquisition

  • standardized data basis

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