We are proud to report that the first master thesis conducted at ai-omatic is now completed!
The aim of the master thesis was to simplify the acquisition of maintenance relevant data. For this purpose, our master student Florian recorded machine vibrations by means of small radio sensors, which were connected to the ai-omatic cloud via a modified measuring case with an integrated mobile phone connection. The system developed in this way makes it possible to transmit the required data from the sensors to our algorithm in real time.
For ai-omatic, the results of the master thesis show known and also new ideas:
It is confirmed that vibrations and oscillations of a machine or an engine can tell a lot about damage that has occurred.
Indications could be given as to which measurement parameters and frequency ranges are particularly suitable for determining the condition of a machine and possible faults. Suitable radio sensors could be further identified for this purpose.
In addition, various pre-processing possibilities of measurement data were shown, which allow a data reduction.
Finally, it can be stated: Florian succeeded in integrating wireless sensors with a high measurement resolution and a long battery life into our system. For our predictive maintenance solution, this offers the possibility of easy acquisition of maintenance-relevant measured variables and fast installation of sensors without interfering cables - within a few minutes.
And there is another good news to report: because following his master's degree, we were able to recruit Florian as a full-time automation engineer. We are happy about the great results and about welcoming Florian as a long-term team member.
