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Evaluation of Seismic Events Detection Algorithms


Affiliations
1 Central Scientific Instruments Organisation, Chandigarh - 160 030, India
2 Kurukshetra University, Kurukshetra - 136 119, India
     

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Identification of seismic events from continuously recorded seismic data in real-time through a Digital Seismic Data Recording system is a difficult task. Despite the vast amount of research in this field, the signal processing and event parameters discrimination algorithms have not yet fully come of age. Presently, we have a wide spectrum of trigger algorithms, ranging from a very simple amplitude threshold type to the sophisticated ones based on pattern recognition approaches. Some of the other approaches use adaptive technique and neural network methods. Researchers are continuously making efforts for the development of algorithms using various techniques, which produce minimum false trigger. Some approaches have been reported which are accurate for detecting first phase of events and take minimum possible computational time. In this paper several approaches for detecting event signals in background noise are presented and their precision evaluation is discussed.

Keywords

Seismic Events, Detection, Algorithms.
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  • Evaluation of Seismic Events Detection Algorithms

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Authors

B. K. Sharma
Central Scientific Instruments Organisation, Chandigarh - 160 030, India
Amod Kumar
Central Scientific Instruments Organisation, Chandigarh - 160 030, India
V. M. Murthy
Kurukshetra University, Kurukshetra - 136 119, India

Abstract


Identification of seismic events from continuously recorded seismic data in real-time through a Digital Seismic Data Recording system is a difficult task. Despite the vast amount of research in this field, the signal processing and event parameters discrimination algorithms have not yet fully come of age. Presently, we have a wide spectrum of trigger algorithms, ranging from a very simple amplitude threshold type to the sophisticated ones based on pattern recognition approaches. Some of the other approaches use adaptive technique and neural network methods. Researchers are continuously making efforts for the development of algorithms using various techniques, which produce minimum false trigger. Some approaches have been reported which are accurate for detecting first phase of events and take minimum possible computational time. In this paper several approaches for detecting event signals in background noise are presented and their precision evaluation is discussed.

Keywords


Seismic Events, Detection, Algorithms.