FP-IND-DATALOGMC

Description

The FP-IND-DATALOGMC function pack for STEVAL-STWINBX1 and EVLSPIN32G4-ACT is a powerful integrated toolkit for the next generation of smart actuators.

This toolkit is derived from a FP-SNS-DATALOG2 function pack and it allows the collection of heterogeneous data, combining STWIN.box sensor information with STSPIN32G4 motor control data and it provides a comprehensive view of the system’s operational conditions. This enables both real-time monitoring and accurate performance assessment.

The v1.1.0 introduces a further firmware example called DATALOGMC_AI that implements a motor fault classification based on a machine learning solution developed through NanoEdgeAIStudio. The machine learning model allows an accurate classification of motor behavior into two states: good and faulty.

Users can also customize the model by adding their own classes, which can be achieved by incorporating additional data and modifying the training process.

The package also includes a portable mechanical setup that can be replicated with a 3D printer.

EVLSPIN32G4-ACT is designed to drive a variety of three-phase brushless DC motors (not included in the kit) and ready for FOC control algorithms. The list of supported motors is provided in the motor control SDK documentation (X-CUBE-MCSDK-6) and installation details are available in the Quick Start guide.

The FP-IND-DATALOGMC, thanks to its data-centric design and user-friendly Python SDK, may run with hardware boards that supply real-time data streams and motor telemetries, empowering users with full control of the data acquisition process.

The included firmware is compatible with the STBLESensor app, which lets you manage: the board, motor, and sensor configurations; start/stop data acquisition on SD card, and control data labeling. Sensor data and motor telemetries can also be stored onto a microSD™ card.

The software is also available on GitHub, where the users can signal bugs and propose new ideas through [Issues] and [Pull requests] tabs.