Predictive maintenance - STEVAL-STWINCSV1

[buelaraj]

I am using the FP-IND-PREDMNT1 STM32Cube function pack for predictive maintenance in STEVAL-STWINCSV1 board, which performs vibration analysis using a 3-axis accelerometer (3 DoF). My use case involves motor vibration analysis. Would it be beneficial to use 6 DoF or 9 DoF data for more effective monitoring?

[SimonePradolini]

Hello @buelaraj 

FP-IND-PREDMNT1 is a complete demo, but it is enabling only some specific sensors and it is not meant to be customize. If you would change the sensor used or add some others, important modifications are needed.

Could you be interested in other ST software solutions? Have a look here, where I'm discussing on a similar topic with another user.

In the post, I'm suggesting a new approach by using newer ST tools available through ST Edge AI Suite.

The idea behind Edge AI Suite is to provide a comprehensive solution to help developers accelerate their product transformation. Here, developers can find the tools to optimize and deploy machine learning algorithms, from data collection to final deployment on hardware. 

This presentation can guide you to select the tool you need.

Notice that the STWIN board you are using is still supported by ST Edge AI Suite tools (i.e.: High Speed Datalog, NanoEdge AI Studio, MEMS Studio, ST AIoT Craft)

Best regards

Simone