The SL-PREDMNT-E2C1 solution combines STMicroelectronics motion and environmental sensors, STM32F4 microcontrollers (MCUs), and STM32MP157 microprocessing units (MPUs) in a condition monitoring and predictive maintenance framework. That is, connecting smart sensor nodes to cloud services such as data lakes and monitoring dashboards.

The smart sensor nodes include selected environmental and individual vibration sensors, an STM32 MCU, and multiple connectivity interfaces. These nodes are placed on top of or around industrial machinery to collect temperature, pressure, and humidity data from LPS22HB and HTS221 sensors, as well as vibration data from IIS3DWB triaxial accelerometers. The STM32 MCU of the same sensor node initiates edge processing to convert vibration signals into frequency and time domain data.

After merging the data from up to four sensor nodes, it is routed through a concentrator to a gateway equipped with an STM32MP157 MPU for further edge processing. Data from the node is cleansed and consolidated before all data is sent to a server-based or cloud-based system for further analysis.

STMicroelectronics provides a predictive maintenance dashboard application to demonstrate how cloud capabilities make this solution complete. The dashboard configures an edge gateway node running AWS IoT Greengrass service and AWS IoT Core. With the solution, you can monitor data curves like status on the dashboard and configure warning thresholds as part of a global predictive maintenance solution.

The solution consists of the following templates

STEVAL-BFA001V2B

● 32-bit ARM® Cortex®-M4 core for signal processing and analysis (STM32F469AI)

● Ultra-wide bandwidth (up to 6kHz), low-noise, three-axis digital vibration sensor (IIS3DWB)

● Optimized package: 50mm × 9mm × 9mm

● Includes IO-Link device stack v1.1 protocol and IO-Link device bus (IODD) for all measurements (provided by TEConcept GmbH)

STEVAL-IDP004V2

● Master IO-Link stack with built-in friction protection

● Fully compatible with all IO-Link devices

● Master supply voltage: up to 32V

● 4 L6360 IO-Link master transceiver ICs

STM32MP157F-DK2

● STM32MP157 Arm® based dual Cortex®-A7 800 MHz 32-bit + Cortex®-M4 32-bit MPU in TFBGA361 package

● 4-Gb DDR3L, 16-bit, 533 MHz

● 1-Gbps isolation (RGMII) compliant with IEEE-802.3ab standard

● USB OTG HS

● Board with USB re-enumeration function ST-LINK/V2-1 debugger/programmer: virtual COM port and debug port

● STM32CubeMP1 and complete mainstream open source Linux® STM32 MPU OpenSTLinux distribution (such as STM32MP1Starter) software and examples

● TFT 480×800 pixels with LED lighting, MIPI DSISM interface and capacitive touch panel

Tools and software

STSW-BFA001V2 - Software package for STEVAL-BFA001V2B multi-sensor development kit for condition monitoring and predictive maintenance - STMicroelectronics

▶Application scenario diagram

▶Demonstration board photo

▶Block diagram

Core technology

IIS3DWB vibration sensor

IIS3DWB is a system-in-package with a three-axis digital vibration sensor with low noise, ultra-wide and low frequency range. The device has high bandwidth, low noise, very stable and repeatable performance, and the ability to operate over an extended temperature range, making it particularly suitable for vibration monitoring in industrial applications.

STM32F4 series microcontrollers

The STM32F4 series MCUs have the digital signal processing capabilities and clock speed to manage ultra-high-speed data streams from vibration and environmental sensors.

LPS22HB and HTS221 sensors

LPSSHB digital pressure and HTS221 relative humidity sensors and temperature sensors meet the data requirements of comprehensive condition monitoring scenarios.

STM32MP157 microprocessor

The dual-core STM32MP157 MPU deployed in the gateway node has the ability to store, process and queue data from multiple edge sensor nodes. The MPU also manages the connection handshake and transmission schedule with the centralized condition and monitoring predictive maintenance system.

Solution Specifications

● Edge processing of comprehensive vibration monitoring data such as velocity (RMS), peak acceleration, and FFT at sensor nodes.

● Temperature, humidity, and pressure data from ST environmental sensors.

● Condition monitoring software supports communication with cloud applications through a secure gateway to expose edge node processing capabilities.

● The ultimate communication framework supports upgrading the condition monitoring platform to a predictive maintenance solution.

● The cloud dashboard is used to register and configure devices, configure and assign gateways to device groups, analyze real-time and historical data, and set the same thresholds.