Nebojsa Matic, Managing Director of MIKROE, comments: “ML Vibro Sens Click, a new member of our company’s family of compact mikroBUS™ —enabled for mikroBUS™ 1750—can be used to collect data for training ML models that recognize different types of vibrations, and to monitor the health of industrial machinery and equipment based on vibration patterns. It can also be used to track movement and activity in wearable devices, and to detect vibrations caused by earthquakes or other seismic events.”
The FXLS8974CF offers the versatility of ultra-low power operation combined with high-performance modes, ensuring efficient use in diverse environments. Its integrated digital functions simplify data collection and reduce system power consumption, while its robust performance across wide temperature ranges enhances reliability in demanding applications such as industrial diagnostics, wearable technology, and environmental monitoring.
This Click board™ incorporates two DC motors to simulate vibration stimuli for machine learning. The BALANCED motor generates stable "nominal" vibrations, which serve as a reference signal for training ML models in a "healthy" state. The UNBALANCED motor is designed to provide customizable vibration signals, from low-intensity vibrations to vibrations based on specific frequencies.
The FXLS8974CF accelerometer captures detailed data from both the balanced and unbalanced motors, allowing differentiation between healthy reference states and abnormal conditions. It communicates with the host MCU via a standard 2-wire I2C interface.
