FFT Analysis for Bearing Fault Detection: 2048-Point Setup

#fft #bearingdiagnostics #vibrationanalysis #predictivemaintenanc

A Low-Frequency Spike That Shouldn't Exist

You've mounted accelerometers on a motor bearing, set your sampling rate to 12.8 kHz, and started collecting vibration data. The motor's nameplate says 1800 RPM (30 Hz), so you're expecting peaks at the rotational frequency and maybe some harmonics. You run an FFT and see a clean peak at 30 Hz. Good.

Then you notice a second peak at 156 Hz that's 40% the amplitude of the main frequency. That's not a harmonic. It's not matching any gear mesh frequency either.

That's your bearing's outer race fault frequency.

This is what FFT analysis does for bearing diagnostics — it turns raw vibration time-series into a frequency spectrum where specific fault patterns show up as distinct peaks. But getting from "I see a spike" to "this is an outer race defect" requires understanding what you're looking for and why half the tutorials get the window function wrong.