Pattern recognition for earthquake detection

Abstract

The detector algorithms in use at date rely on negative decision logic: based on a model of the ambient noise process they detect all deviations, but many of them are false alarms. The principal alternative to this approach is pattern recognition, which tests on positive correlation with some known signal patterns. The Sonogram-detector realizes this scheme for single seismogram traces. Sonograms display spectral energy versus time. Suitably scaled, these images display only information which is significant to the detection process. Patterns of known earthquakes and noise signals are defined by means of these images. Event detection is performed by recognizing one of the patterns in the actual sonogram. The overall processing scheme is similar to the visual inspection of seismograms by the human observer. An off-line test installation for detecting local earthquakes proves the expected low false alarm rate, high timing accuracy and good detection probability of the Sonogram-detector.