June 2020

Condition Monitoring with RMG/941 and AWS

SSV has published a comprehensive example of machine learning-based condition monitoring using the RMG/941 remote maintenance gateway, the MLS/160A soft sensor, and the Amazon cloud on GitHub.

In this example, an MLS/160A is attached as a triaxial vibration sensor to a rotating machine (in this case, a fan). The sensor transmits a continuous data stream to an RMG/941. In the gateway, a CSV file is generated from the vibration data of the sensor for training a so-called supervised machine learning algorithm.

Using this CSV data and AWS (Amazon Web Services), a machine learning model is thus created, which can then be used to classify the operating states of the machine based on the current vibrations.

The complete condition monitoring example with RMG/941, MLS/160A and AWS including all code and CSV files as well as a detailed description can now be found on GitHub:

Condition Monitoring with RMG/941 and AWS on GitHub.

On-demand AWS IoT Integration Webinar

We now offer the on-demand AWS IoT integration webinar for the RMG/941 if needed. We show there, among other things, how an RMG/941 is registered in the Amazon cloud and how the resulting access authorization or key files are downloaded and used for the RMG/941 configuration.

Please contact us for more information about the on-demand AWS IoT integration webinar.

 

 

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