辨別地震與非地震訊號之現地即時強震預警系統研發
Other Title
Research on Distinguishing between Earthquake Signal and Non-Earthquake Signal for On-Site Earthquake Early Warning System
Date Issued
2014
Abstract
The regional earthquake early warning system (EEWS) is not suitable for Taiwan due to the fact that most of the destructive seismic hazard comes from in-land earthquakes, which makes the lead-time before destructive earthquake wave arrives provided by the regional warning system can be null. On the other hand, on-site warning system can provide more lead-time at the region close to an epicenter since only the seismic information on the target site is required. Instead of leveraging the information of several stations, the on-site system extracts some P-wave features from the first few seconds of vertical ground acceleration of a single station and performs the prediction of the coming earthquake intensity at the same station according to these features. However, the system may be triggered due to some vibration signals that are not caused by an earthquake event or interference from electronic signals, which may result in false alarm at the station. Therefore, this research performs a study on the classification between true earthquake and non-earthquake events by means of Support Vector Classification (SVC) and Singular Spectrum Analysis (SSA).
Support Vector Classification is a machine learning technique that has been widely used in automatic data identification in the past decades. Singular Spectrum Analysis is a signal processing algorithm which is popular for classical time series analysis, multivariate statistics, and dynamical systems. This research proposes two methods to distinguish the vibration signals caused by non-earthquake events from the one caused by earthquake events based on the above two algorithms. The feasibility of the proposed method will be verified by using data collected from Taiwan Strong Motion Instrumentation Program (TSMIP) and earthquake early warning stations of National Center for Research on Earthquake Engineering (NCREE).
Subjects
地震預警系統
支持向量分類法
資料識別
奇異譜分析
Type
thesis
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