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Predictive-Maintenance-PYNQ

MakarenaLabs s.r.l.

This repo is the open-source implementation for the Predictive Maintenance of Xilinx made with MakarenaLabs. For more information about the other projects involved as dependencies please visit:

Setup

The project currently works with the Motor Control Kit provided by Trenz Electronic and supports the Ultra96-V2 board. To connect to the power stage board of the motor is needed the Adapter provided by Trenz Electronic.

Instructions for Installation

To build the project you need to:

  • Flash in a SD-Card the Pynq image V2.6 for Ultra96-V2 from the ones available and follow the steps to setup the board.
  • After having created a working PYNQ image, connect to the board and clone the repo.
  • cd into the folder cloned and tap chmod 755 init.sh && ./init.sh. It will ask you the password, which is xilinx (same name as the account).
  • Once the installation has completed you can try the Jupyter Notebooks provided as an example under pynq-dpu installed in the jupyter folder.

To run the flask server you need to tap sudo python3 main.py in the folder pynq-foc-dpu-python-code. Currently it is supported just the FOC interfacing. The server will run in local (w.r.t. the Ultra96-V2) on the port 5000. For example, if your board has 192.168.2.5 IP address, the server is accessible through this address: 192.168.2.5:5000

Note that the python process is not detached, so you need to keep your SSH terminal active.

The documentation of Flask API server is here: https://github.com/MakarenaLabs/Predictive-Maintenance-PYNQ/tree/main/pynq-foc-dpu-python-code

Notes for Installation

The script init.sh will download and install the project DPU-PYNQ needed to interface the DPU.

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Predictive Maintenance project on PYNQ framework by Xilinx

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