Solution Description
In the framework of Predictive Maintenance, Condition Monitoring plays an important role towards a Smart Factory and Industry 4.0 strategy where vibration, ultrasound and environmental data are collected by smart sensor nodes and shared for analysis in a central data lake or cloud services via Wi-Fi or cellular network connectivity.
Critical vibration data is processed locally on a high-performance, ultra-low-power STM32L4+ microcontroller by combining 3-axis acceleration data from a 6 kHz IIS3DWB vibration sensor and ultrasound data up to 80 kHz from a IMP23ABS1 microphone sensor to generate frequency and time domain analyses such as fast Fourier transform (FFT), root mean square (RMS), and peak acceleration. Environmental pressure, temperature and humidity data is also collected by the LPS22HB and HTS221 sensors embedded on the node.
The very-low power requirements of the MCU and the sensors allow for compact, battery-operated nodes driven by the STBC02 battery charger.
The STM32L4+ microcontroller supports wireless data transmission through an additional Wi-Fi module such as the Inventek ISM43362.M3G-L44, or via a cellular modem such as the Quectel BG96, which supports LTE Cat M1 and NB-IoT connectivity with a plastic Micro-SIM (3FF).
Develop your own condition monitoring algorithms for edge processing and event visualization
To provision nodes, plot data, and configure triggers as part of an end-to-end solution, ST provides a highly functional and intuitive cloud platform (DSH-PREDMNT) tailored for the logging, visualization and analysis of condition monitoring data. You can use the dashboard to plot and graph real-time and historical data, monitor critical operating conditions such as running temperature, and set thresholds for automatic warnings when key parameters exceed acceptable limits. Once you collect and download the data, you can develop your own algorithms for edge processing and event visualization.
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Key Product Benefits
STM32L4R9ZI - Ultra-low power MCU plus high speed EEPROM
Ultra-low-power microcontroller based on ultra-low power Arm Cortex-M4 32-bit RISC core with single-precision floating-point unit (FPU), digital signal processing (DSP) and memory protection (MPU) unit. This MCU allows high speed sensor data streaming at the maximum ODR, and the 2MB Flash can host machine learning algorithms for anomaly detection
IIS3DWB - Ultra-wide band vibration sensor
Ultra-wide bandwidth (up to 6 kHz), low-noise, 3-axis digital vibration sensor is highly suited to applications involving vibration analysis up to 6kHz, both in terms of performance and cost.
LPS22HB and HTS221 - High accuracy environmental sensors
The LPSSHB digital pressure and HTS221 relative humidity and temperature sensors complete the data requirements for a comprehensive condition monitoring scenario.
MP23ABS1 - Wideband MEMS microphone
The wideband analog MEMS microphone up to 80kHz allows vibration data collection and analysis well into the ultrasound frequency range.
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All Features
- Condition monitoring data in the form of vibration speed (RMS), acceleration peak, and FFTs processed by the high-performance, ultra-low-power STM32L4+ microcontroller.
- Vibration detection using an industrial 3-axis MEMS vibration sensor with digital output (IIS3DWB) and ultrasound frequency analysis thanks to a compact MEMS analog audio sensor (IMP23ABS1).
- Precise environmental data measurements using an ultra-compact relative humidity and temperature sensor (HTS221) and MEMS nano pressure sensor (LPS22HB).
- SL-PREDMNT-S2C is an end-to-end communication framework that provides a condition monitoring platform able to grow into a predictive maintenance solution.
- Cloud-based web application (DSH-PREDMNT) available for the logging, visualization and analysis of condition monitoring data.
