ST STM32Cube Manuel utilisateur

Quick Start Guide

STM32Cube function pack for STEVAL-

STWINKT1B evaluation kit for predictive

maintenance application based on artificial

intelligence (AI)

(FP-AI-PREDMNT2)

Version 1.0 (Oct 15, 2021)

Agenda

1Hardware and Software overview

3Documents & Related Resources

4STM32 Open Development Environment: Overview

2Setup & Demo Examples

1- Hardware and Software overview

STWIN development kit - STEVAL-STWINKT1B

Hardware Overview

STWIN - SensorTile Wireless Industrial Node

The STWIN (STEVAL-STWINKT1B) is a development kit and reference design that simplifies prototyping and testing

of advanced industrial IoT applications such as condition monitoring and predictive maintenance. The kit supports

BLE wireless connectivity through an on-board module and Wi-Fi connectivity through a special plugin expansion

board (STEVAL-STWINWFV1), wired RS485 and USB OTG connectivity.

Key Features

•Multi-sensing wireless platform implementing vibration monitoring and ultrasound detection

•Updated version of STEVAL-STWINKT1, now including STSAFE-A110 populated, BlueNRG-M2S module and

IMP23ABSU MEMS microphone

•Ultra-low-power ARM Cortex-M4 MCU at 120 MHz with FPU, 2048 kbytes Flash memory (STM32L4R9)

•Micro SD Card slot for standalone data logging applications

•Option to implement Authentication and Brand protection secure solution with STSAFE-A110

•Wide range of industrial IoT sensors: ultra-wide bandwidth (up to 6 kHz), low-noise, 3-axis digital vibration sensor

(IIS3DWB), 3D accelerometer + 3D Gyro iNEMO inertial measurement unit (ISM330DHCX) with machine learning core,

ultra-low-power high performance MEMS motion sensor (IIS2DH), ultra-low-power 3-axis magnetometer (IIS2MDC),

digital absolute pressure sensor (LPS22HH), relative humidity and temperature sensor (HTS221), low-voltage digital local

temperature sensor (STTS751), industrial grade digital MEMS microphone (IMP34DT05), analog MEMS microphone with

frequency response up to 80 kHz (IMP23ABSU)

•Modular architecture, expandable via on-board connectors: STMOD+ and 40-pin flex general purpose expansions, 12-pin

male plug for connectivity expansions, 12-pin female plug for sensing expansions

•Other kit components: Li-Po battery 480 mAh, STLINK-V3MINI debugger with programming cable, Plastic box

Latest info available at

www.st.com/stwin

STWIN development kit - STEVAL-STWINWFV1

Hardware Overview

Wi-Fi expansion for the SensorTile Wireless Industrial Node (STWIN) kit

The STEVAL-STWINWFV1 expansion board adds 2.4 GHz Wi-Fi connectivity to the STEVAL-STWINKT1B.

Application examples that take advantage of this expansion board can be found also in STSW-STWINKT01 firmware

package as well as in the FP-IND-PREDMNT1 and FP-AI-PREDMNT2 Predictive Maintenance Function Pack.

Key Features

•Wi-Fi adapter for STEVAL-STWINKT1B

•Plugs into STWIN core system board through dedicated 12-pin connector

•Single 3.3 V power supply input

•ISM43362-M3G-L44-E Wi-Fi module:

•802.11 b/g/n Compatible based on Broadcom MAC/Baseband/Radio device

•Fully contained TCP/IP stack

•Host interface: SPI up to 25 MHz

•Network features ICMP ( Ping), ARP, DHCP,TCP, UDP

•Low power operation (3.3 V supply) with built-in low power modes

•Secure Wi-Fi authentication WEP-128, WPA-PSK (TKIP), WPA2-PSK

•CE, FCC and IC certified

•RoHS and China RoHS compliant

•WEEE compliant Latest info available at www.st.com

STEVAL-STWINWFV1

FP-AI-PREDMNT2

Software Overview

FP-AI-PREDMNT2 Software Description

FP-AI-PREDMNT2 is an STM32Cube function pack that programs the STWIN as an

IoT Edge node, connected to the cloud, able to acquire sensor data, process them and

send the results to the DSH-PREDMNT cloud dashboard. It includes dedicated

algorithms for advanced time and frequency domain signal processing and analysis of

3D digital accelerometers with flat bandwidth up to 6 kHz.

Key features

•Compatible with NanoEdge™ AI Studio solution from Cartesiam, to enable AI-

based solution (NanoEdge™ AI library generation is out of the scope of this

function pack and must be generated using NanoEdge™ AI Studio)

•Generic FFT library middleware to enable frequency domain analysis for any kind

of sensor through Fast Fourier Transform (with programmable size, overlapping

and windowing)

•Motion TD library middleware for vibration analysis in time domain (speed RMS

and acceleration peak)

•Configurable alarm and warning thresholds for key parameters

•Compatible with STBLESensor application forAndroid/iOS, to perform Wi-Fi

configuration and secure certificate provisioning

•Compatible with DSH-PREDMNT web-based predictive maintenance dashboard

for monitoring sensor data and device status

•Easy portability across different MCU families, thanks to STM32Cube

•Firmware modular example based on eLooM (embedded Light object-oriented

fraMework for STM32) to enable code re-usability at application level

•Free, user-friendly license terms

Overall Software Architecture

Latest info available at www.st.com

FP-AI-PREDMNT2

2- Setup & Demo Examples

•1x STEVAL-STWINKT1B development board

•1x STEVAL-STWINWFV1

•Laptop/PC with Windows 7, 8 or 10

•2x microUSB cables

•1 smartphone with ST BLESensor App

•Wi-Fi Router or access to a Wi-Fi network

MicroUSB Cable

Setup & Demo Examples

HW prerequisites

STEVAL-STWINKT1B

STEVAL-STWINWFV1

ST BLESensor App

Setup & Demo Examples

HW prerequisites

•How to re-program/debug the STWIN

Assembled Kit

Programming cable

STLINK-V3MINI

Setup & Demo Examples

Software and Other prerequisites

•STM32CubeProgrammer Software

•Download and install STM32CubeProgrammer

•FP-AI-PREDMNT2

•Copy the .zip file content into a folder on your PC. The package will contain source code example (Keil, IAR,

STM32CubeIDE) based on STEVAL-STWINKT1B

•ST BLE Sensor Application for Android/iOS to download from Google Store / iTunes

•ST DSH-PREDMNT Account

FP-AI-PREDMNT2 is not the default firmware on STEVAL-STWINKT1B.

To update the firmware, please follow the instructions available in slide 11

Autres manuels pour STM32Cube

Table des matières

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