Click board for ML models for vibration analysis
MikroE has launched a Click board that helps the development and training of AI models for vibration analysis for machine health monitoring..
The MikroE ML Vibro Sens Click uses the FXLS8974CF 3-axis low-g accelerometer from NXP Semiconductors which has ultra-low-power operation alongside high-performance modes, ensuring efficient use in a wide range of scenarios.
The Click board incorporates two DC motors to simulate vibration stimuli for machine learning. The BALANCED motor generates steady ‘nominal’ vibrations, serving as a baseline signal for training ML models in a ‘healthy’ state. The UNBALANCED motor is designed to provide customizable vibration signals, ranging from low-intensity to specific frequency-based vibrations.
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The FXLS8974CF accelerometer captures detailed data from the balanced and unbalanced motors, enabling the differentiation between healthy baseline states and anomalous conditions. It communicates with the host MCU via a standard 2-wire I2C interface and the extended temperature range enhances reliability in demanding applications, including industrial diagnostics, wearable technology, and environmental monitoring.
“A new member of our company’s 1750-strong mikroBUS-enabled Click board family of compact add-on boards, ML Vibro Sens Click can be used to collect data for training ML models to recognize different types of vibrations, and to monitor the health of machines and industrial equipment based on vibration patterns. It can also be used to track motion and activity in wearable devices, and to detect vibrations caused by earthquakes or other seismic events.”
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