Turning Sensor Noise Into Signal: FFT and Power Spectrum Features

How we used Welch’s method and grouped Polars operations to extract frequency-domain features from 180+ sensors - and improved anomaly detection by 11% The Problem With Raw Sensor Data If you’ve ever worked with industrial sensor data, you know the feeling. You’re staring at a time-series plot - vacuum pressure oscillating, milk yield pulsing, hydraulic oil pressure fluctuating - and somewhere in that mess is a signal that says “this machine is about to break down.” Our project monitors milking robots at dairy farms. Each robot has over 180 sensors generating data at up to 300 Hz.