ST STM32Cube Bedienungsanleitung
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
2
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
6
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
8
•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
9
•How to re-program/debug the STWIN
Assembled Kit
Programming cable
STLINK-V3MINI
Setup & Demo Examples
Software and Other prerequisites
10
•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
Andere Handbücher für STM32Cube
6
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