i intend to extract features from time-domain measurement data. I feed the features to machine learning algorithms to detect anomalies.
In the time-domain, i extract mean, RMS, skew and standard deviation. I also want to execute a fourier transform and extract the features from the fourier transform. Intuitively, i would pick the mean frequency and the peak frequency for different frequency bands.
Unfortunately, i cant find any literature on the topic or other people who extracted features from fourier transform (and wavelet, cepstrum, Hilbert, ...) who are smarter than me. can anybody help?