But I have also seen people trying to use deep networks to identify rotating machinery faults, like bearings, from raw accelerometer data collected a high frequencies like 40 kHz. Whereas the spectrum of the data from running FFT on the signal contains fault information much more obviously and clearly.

Throwing a deep network on a problem without some physical insight into the problem has also its disadvantages it seems.