MULTI-SENSOR PREDICTIVE MAINTENANCE KIT WITH IO-LINK STACK V.1.1

Are you on the market for a kit ready to kickstart your predictive maintenance projects? Probably you may want to hear about the IO-Link stack v.1.1 from ST microelectronics, as they just released this very complete and interesting kit, in a very compact form factor. There is just about everything you need, including sensors, processing capabilities, and communication. Overall, we are looking at a very solid package.

The STEVAL-BFA001V2B is an industrial reference kit for condition monitoring predictive maintenance, ready to be deployed in industrial environments, by obeying the IEC61000-4-2/4 and EN60947 requirements for these environments. This board was specifically designed for industrial applications, housing industrial sensors, along with the necessary debugging tools, cables, adapters, and plugs for applications that need industrial communication. This module connects through a standard multipolar cable, where one wire is being used for IO-Link data.

But regarding the specifications, what are we looking at? Let us see:

  • Kit: sensor node (STEVAL-IDP005V2, not available separately), communication board (STEVAL-UKI001V2, not available separately) and STLINK-V3MINI programming and debugging interface
  • Supply voltage range from 18 to 32 V
  • Sensor node:
    • ARM Cortex-M4 microcontroller for signal processing and analysis (STM32F469AI)
    • IIS3DWB: ultra-wide bandwidth (up to 6 kHz), low-noise 3-axis digital vibration sensor
    • LPS22HB: absolute digital pressure sensor
    • HTS221: relative humidity and temperature sensors
    • IMP34DT05: digital microphone sensors
    • L6362A: IO-Link PHY device
    • EEPROM for data storage
    • Step-down switching (L6984) and LDO (LDK220) regulators
    • ESD protection
  • M12 standard industrial connector
  • SWD connector for programming and debugging purposes
  • Reset button and expansion connector with GPIO, ADC, I2C bus and timers
  • Designed to comply with the IEC industrial standard requirements

Read more: MULTI-SENSOR PREDICTIVE MAINTENANCE KIT WITH IO-LINK STACK V.1.1


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Muhammad Bilal

I am highly skilled and motivated individual with a Master's degree in Computer Science. I have extensive experience in technical writing and a deep understanding of SEO practices.

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