Two Novel Approaches to Reduce False Alarm Due to Non-Earthquake Events for On-Site Earthquake Early Warning System

An on-site earthquake early warning system (EEWS) can provide more lead-time at regions that are close to the epicenter of an earthquake because only seismic information of a 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. It then predicts the intensity of the forthcoming earthquake at the same station according to these features. However, the system may be triggered by some vibration signals that are not caused by an earthquake or by interference from electronic signals, which may consequently result in a false alarm at the station. Thus, this study proposes two approaches to distinguish the vibration signals caused by non-earthquake events from those caused by earthquake events based on support vector classification (SVC) and singular spectrum analysis (SSA). In the first approach (Approach I), the fast Fourier transform algorithm and the established SVC model are employed to classify the vibration signals. In the second approach (Approach II), a SSA criterion is added to Approach I for the purpose of identifying earthquake events that are classified as non-earthquake events by the SVC model with increased accuracy. Both approaches are verified by using data collected from the Taiwan Strong Motion Instrumentation Program and EEW stations of the National Center for Research on Earthquake Engineering. The results indicate that both of the proposed approaches effectively reduce the possibility of false alarms caused by an unknown vibration event.