Machine Learning Anomaly Detect Demo - FXLS8974

Highlights

• In this video, we will go over the important highlights of the Vibration Based - Machine Learning – Anomaly Detection Reference Design and Demonstration
• In this demo, we obtain acceleration data from the X, Y and Z axes of the FXLS8974, 3-Axis Low-G Accelerometer for Motion Wakeup. Designed for Industrial and Medical Application
• One-class, Support Vector Machine (SVM) is trained on "healthy" vibration of the device measuring 2 dimensional features Root Mean Square (RMS) and Max Fast Fourier Transform (FFT) on the vibration data detected by FXLS8974CF sensors
• The demo is based on the FRDM-MCXN947 evaluation board. This development tool hosts one of the latest MCU’s from NX
• This demo illustrates that FXLS8974 is the ideal choice for motor vibration anomaly detection and preventive maintenance use cases