I'm analysing vibration data from 4 wind turbines (WTs). 8 different sensors are sampled at 25.6 kHz for 10 seconds once a day. I have data from around 400 days (intervals). The plot underneath is for one of the four WT in the time domain.
The frequency domain from FFT of the four turbines (Gearbox HSS) in the the range 0-12kHz:
Current plan and questions:
I want to look for faults in the gearbox, and I am suspecting that WT 4 (bottom right plot above) is most degraded. I want to apply some kind of high frequency technique for looking for early stage bearing damages in the higher frequency range, since these are not captured by FFT.
- What approaches should can I consider here? (I have looked a bit at Hilbert transform, but I'm not exactly sure how that would help me.) I am also considering performing some kind of enveloping/wavelet transform.
- Should I be looking at lower frequencies as well?
This is not my main study field, and I want to try building a machine learning classifier with variables obtained from the signal processing.
Plots of the lower frequency (0-2000Hz) development over the 400 intervals for all 4 turbines: