University of Twente Student Theses

Login

Pump diagnostics using machine learning

Ekris, C.J. van (2020) Pump diagnostics using machine learning.

This is the latest version of this item.

Full text not available from this repository.

Full Text Status:Access to this publication is restricted
Abstract:The master thesis shows how transfer learning can be used to train machine-learning models to automatically recognize faults in a UHPLC pump. With the developed machine-learning models it is possible to recognize faults in real-time, estimate the seriousness of a fault and to differentiate between several faults. With the help of the 20-Sim model the UHPLC pump, all kind of faults can be replayed and log data can be generated. With this generated log data, machine-learning models can be trained. Using the trained machine-learning models it should be possible for untrained users of the pump to recognize several faults and to solve them.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:30 exact sciences in general
Programme:Electrical Engineering MSc (60353)
Link to this item:http://purl.utwente.nl/essays/81327
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page