Automatic arrival time detection for earthquakes based on fuzzy possibilistic C-Means clustering algorithm

Abstract

Earthquake Early Warning System (EEWS) has a great impact on reducing the harm effects resulting from earthquakes such as human death, nuclear leakage, contamination of water, and properties damage. In this paper, we proposed a new approach to detect the arrival time of the earthquakes which is the main module in the EEWS. The proposed algorithm based on Fuzzy Possibilistic C-Means (FPCM) clustering algorithm. FPCM divide the signal into two groups, seismic noise, and seismic signal. The degrees of membership computed, and a Dual-thresholds system applied as a basis for classification to detect the arrival time accurately. The proposed algorithm has high accuracy on picking the arrival time of the earthquake. It achieved arrival time picking accuracy of 90.7 % with a standard deviation of 0.105 seconds for 407 field seismic waveforms. Also, the results show that the proposed algorithm can detect the arrival time for micro-earthquakes accurately despite the existence of low Signal to Noise ratio (SNR). The proposed algorithm can deal with the seismic signal with SNR as low as −10 dB.