Frequency-Dependent Peak-Over-Threshold algorithm for fault detection in the spectral domain

An original novelty detection algorithm in the Fourier domain, using extreme value theory (EVT) is considered in this article. Periodograms may be considered as frequency-dependent random variables, and this can be taken into account when designing statistical tests. Frequency-Dependent Peak-Over-Threshold (FDPOT) puts special emphasis on the frequency dependence of extreme value statistics, thanks to Vector Generalized Additive Models (VGAM) estimation. An application is discussed in the field of mechanical vibrations. It is first shown that performance increases compared to POT detection. Then FDPOT is compared to state-of-the-art algorithms such as KPCA.