Detection of small-scale rockfall incidents using their seismic signature

Achilleas Tripolitsiotis; Antonis Daskalakis; Stelios Mertikas; Dionysios Hristopulos; Zach Agioutantis; Panagiotis Partsinevelos

doi:10.1117/12.2192591

19 June 2015 Detection of small-scale rockfall incidents using their seismic signature

Achilleas Tripolitsiotis, Antonis Daskalakis, Stelios Mertikas, Dionysios Hristopulos, Zach Agioutantis, Panagiotis Partsinevelos

Author Affiliations +

Proceedings Volume 9535, Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015); 953519 (2015) https://doi.org/10.1117/12.2192591
Event: Third International Conference on Remote Sensing and Geoinformation of the Environment, 2015, Paphos, Cyprus

Abstract

Several algorithms have been effectively used to identify the seismic signature of rockfall incidents, which constitute a significant threat for human lives and infrastructure especially when occurring along transportation networks. These algorithms have been mostly evaluated using data from large scale rockfall events that release a large amount of energy. However, low-energy rockfall events (< 100 Joules) triggered by small-sized individual rocks falling from small heights can be severely destructive. In this study, a three-parameter algorithm has been developed to identify low-energy rockfall events. An experimental setup was implemented to 1) validate the results obtained by this algorithm against visual inspection of seismic signals records, 2) define the optimal algorithm parameterization to minimize false alarms, and 3) investigate whether tri-axial vibration monitoring can be replaced by a uniaxial device in order to reduce the installation cost of a real-time rockfall monitoring system. It was found that the success rate of the proposed algorithm exceeds 80%independently of the parameters used, while event identification at a maximum distance with minimal false alarms was achieved when using mean± 3σ as the threshold criterion and 6 ms and 4 ms as the trigger and event window parameters respectively. Finally, it was found that for the specific experimental setup, a uniaxial device could be used for rockfall event identification.

Citation Download Citation

Achilleas Tripolitsiotis, Antonis Daskalakis, Stelios Mertikas, Dionysios Hristopulos, Zach Agioutantis, and Panagiotis Partsinevelos "Detection of small-scale rockfall incidents using their seismic signature", Proc. SPIE 9535, Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015), 953519 (19 June 2015); https://doi.org/10.1117/12.2192591

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