Met4FoF use case of agent based condition monitoring

This is supported by European Metrology Programme for Innovation and Research (EMPIR) under the project Metrology for the Factory of the Future (Met4FoF), project number 17IND12.

Purpose

This is an implementation of the agent-based approach for the ZEMA dataset on condition monitoring of a hydraulic system.

Getting started

In case you are using PyCharm, you will already find proper run configurations at the appropriate place in the IDE. If not you can either proceed executing the Jupyter Notebooks or by running some of the script files.

If you have any questions please get in touch with the author.

Jupyter Notebooks

Run Code 01-03 to prepare the ML models, and run Code 04 to start and run the agents. While Code 04 is running, run Code 05 in separate terminal to visualize them.

Scripts

The interesting parts you find in the files

• main_bnn_agents.py
• cuda_agent.py
• confusion_matrix_dev.py

Orphaned processes

In the event of agents not terminating cleanly, you can end all Python processes running on your system (caution: the following commands affect all running Python processes, not just those that emerged from the agents).

Killing all Python processes in Windows

In your Windows command prompt execute the following to terminate all python processes.

> taskkill /f /im python.exe /t
>

Killing all Python processes on Mac and Linux

In your terminal execute the following to terminate all python processes.

$ pkill python
$

References

For details about the agents refer to the upstream repository agentMET4FOF

Screenshot of web visualization