ADI Voyager4 EV-CBM-VOYAGER4-1Z Wireless Vibration Assessment Kit - Decision-Making Path

Embedded Development Boards, Kits, Programmers
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This article will discuss the decision-making path used by the ADI Voyager4 EV-CBM-VOYAGER4-1Z Wireless Vibration Assessment Kit

This kit is a complete low-power vibration monitoring platform that allows designers to quickly deploy wireless solutions to devices or test fixtures. It can detect abnormal motor behaviors through edge AI algorithms and trigger diagnostic and maintenance requests.

The decision-making path of Voyager4 reduces redundant data transmission through local edge AI processing. By combining the coordinated wake-up of dual sensors and intelligent power management, it achieves the core goals of “low power consumption, high precision, and real-time response” in industrial vibration monitoring. Its decision-making logic not only ensures the reliability of equipment health status detection but also significantly extends the device’s battery life.

ADI vibration detector EV-CBM-VOYAGER4-1Z decision-making path diagram
ADI vibration detector EV-CBM-VOYAGER4-1Z decision-making path diagram500×510 37.7 KB

Shown is the decision-making path at the core of the Voyager4 system. (Image source: Analog Devices)

The original vibration data is transmitted to the MAX32666GXMBL+ (integrated with BLE radio and Arm® Cortex®-M4F DARWIN MCU) through path (a) for training the edge AI algorithm, then sent to the user via the BLE or USB port.

After the training is completed, the vibration data can be used to predict the device’s status through the edge AI algorithm of the MAX78000EXG+ MCU via path (b). If the data is normal (path d), there is no need to activate the MAX32666 radio, and the sensor returns to sleep mode; if an anomaly is detected (path c), an alert is sent via BLE.

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ADI Voyager4 EV-CBM-VOYAGER4-1Z Wireless Vibration Assessment Kit

  • MEMS Accelerometers
    • ADXL382: A 16-bit, 8kHz bandwidth three-axis digital accelerometer for high-precision vibration data collection (such as bearing fault detection).
    • ADXL367: A 14-bit, 100Hz low-power three-axis accelerometer responsible for monitoring vibration events in low-power scenarios and waking up the system.
  • Microcontrollers and Edge AI Processing
    • MAX32666: A microcontroller integrated with BLE 5.3, responsible for wireless data transmission and system control.
    • MAX78000: An edge AI processor with a built-in hardware CNN accelerator, realizing local vibration anomaly detection and reducing the need for data upload.
  • Power Management Modules
    • MAX20335: A load switch to optimize system power consumption.
    • MAX17262: A battery charge monitoring chip that provides real-time feedback on battery health status.
    • MAX38642: A power management IC that supports flexible power supply schemes.