University of Twente Student Theses
Pump diagnostics using machine learning
Ekris, C.J. van (2020) Pump diagnostics using machine learning.
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| 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 |
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