Beginner's book in signal processing with practical examples on fault detection in electrical motors I'm an electrical engineering graduate and I'm working on condition monitoring for electrical motors and generators. My goal is to improve reliability of electric rotary machines in such way, that any ongoing faults are discovered before they progress in major failures. Main role in this domain has signal processing (and also statistical analysis along with machine learning), which I would use to develop condition monitoring algorithms. Unfortunately signal processing wasn't included in my education program, so I have to learn this on my own.

So what I think that I need, are some sources which outline  basic concepts, typical tools (FFT, STFT, wavelets, filters...) and problem-solving examples (noise removal, hidden pattern extraction, ripple reduction,...)  with only so much math involved that the main idea can be grasped, and that implementation is possible, which would be demonstrated in lots of MATLAB examples in the context of electrical rotary machines. I truly don't want a source for signal processing, which is aimed for mathematicians or information engineers, but rather sth applicable for electrical engineers.
When I had a look at rotating machinery, the best reference I could find is Bob Randall's Frequency Analysis.  This was generated in conjunction with Brüel &amp; Kjær as they sold lots of nice (and expensive) vibration measuring / monitoring equipment.  A short Google search shows that B&amp;K have made the PDF of this book available for free download from their website.

The book is targeted at mechanical engineers, who (back in the day) were never exposed to the Fourier transform.