Signal Processing on Precursory “Fingerprint” Image Pattern Feature of Yushu Earthquake

Abstract

Precursory earthquake data are linked closely to the earthquake processes. Taking the Tibetan Autonomous Region’s Yushu County earthquake as an example, we analyzed three types of earthquake signals and studied a modeling method for self-adaptative matching warning data on precursory data’s fingerprint features. We calculated different timescale features of precursory fingerprint pattern images based on statistical physics and image matching. We also developed corresponding fuzzy discriminant rules and established a database of warning-image fingerprint pattern features for the Yushu County region and studied evolutionary laws for the data feature patterns under different time scales during abnormal development in front of and behind of abnormal development. Result were similar to the general “fingerprint” pattern feature among precursory earthquake data for different signal channels, but the details of these characteristics are completely different. This special “fingerprint” image pattern feature is useful as on early warning of possible geological follow-up activity. Our method could improve the limitations on and low efficiency of manual handling and could also heighten observational accuracy and work efficiency.