Wind Turbine Vibration Analysis: Which approach?
One technique that I've seen used in determining bearing faults is using the kurtosis of the vibration signal.

You can track as a function of time what Wikipedia calls the sample excess kurtosis. This is the kurtosis that is different from the kurtosis you would see if the signal was Gaussian distributed.

The sample excess kurtosis is defined as:

$$
\frac{m_4}{m_2^2} - 3 = \frac{\frac{1}{N} \displaystyle \sum_{n=0}^{N=1} (x_n - \bar{x})^4}{\left(\frac{1}{N} \displaystyle \sum_{n=0}^{N=1} (x_n - \bar{x})^2\right)^2} - 3
$$

where $\bar{x}$ is the sample mean, $m_2$ is the sample second order moment, and $m_4$ is the sample fourth order moment.

Brüel &amp; Kjær have a nice writeup about using kurtosis, though they use the actual kurtosis rather than the excess kurtosis.

Why?

Bearing faults tend to show up when grit or dirt or broken bearing pieces get into the rotating elements.  When that happens, the vibration signals tend to be more "spiky" as the fault-inducing material gets ground against the rolling elements and bearing races.

Other approaches

You can also look at removing what you know about the harmonic content of the signals and then looking at the remainder.  There's some stuff about that here.  However, try something simple like kurtosis first.