Detection of Locally Stationary Segments in Time Series
Uwe Ligges, Claus Weihs, Petra Hasse-Becker · COMPSTAT · 2002
In many applications it is required to segment a time series into its locally stationary parts. Two applications are presented: As a first example consider online monitoring of a BTA Deep-Hole-Drilling process. Here chattering and spiralling of the drilling tool should be avoided by process control. A second example is the analysis of vocal sound signals. It may be required to analyse only specific tones instead of a whole song. Three new algorithms are introduced in this paper, all based on the theory of ( Dahlhaus(1997) and the analysis of the spectrum of time series, but with different methods to distinguish locally stationary parts of the signals.