This chapter illustrates the concept of passive seismics as a method for monitoring the propagation of cracks within a rock mass as a result of load stress or water freezing in view of the use of this technique for rockfall early warning. The methodology is still far from being a standard and consolidated technique. The research is making progress, but just a few real case studies are documented. They are shortly overviewed in the introduction. Then, an interesting field test where crack propagation was artificially triggered up to full rock detachment, while a small sensor network was active, is discussed to show the existence and the characteristics of precursory signals. It follows the illustration of the microseismic monitoring methodology through the description of the Mt. San Martino (Lecco, Italy) sensor network and the discussion of the preliminary results obtained during the initial months of activity. Apparently, the preliminary results show some correlation with rainfalls, but not with temperature. Microseismic spectra are mainly concentrated in the first 100 Hz. This probably means that the hypocentre distances from the sensors are quite longer than 10 m. Electromagnetic interferences are also observed as mentioned by other authors who have analyzed data sets from other microseismic networks installed in mountain regions. They are automatically discriminated from significant signals by a classification software which works on the time/ frequency properties of these events. Hypocenter localization and clustering analysis of the significant events are the planned near- future activities.
|Data di pubblicazione:||2015|
|Titolo:||Analysis of Microseismic Activity Within Unstable Rock Slopes|
|Autori:||Arosio, Diego; Longoni, Laura; Papini, Monica; Zanzi, Luigi|
|Digital Object Identifier (DOI):||10.1007/978-3-662-45931-7_7|
|Titolo del libro:||Modern technologies for landslide monitoring and prediction|
|Tutti i curatori:||Scaioni, M.|
|Appare nelle tipologie:||Capitolo/Saggio|
I documenti presenti in Iris Unimore sono rilasciati con licenza Creative Commons Attribuzione - Non commerciale - Non opere derivate 3.0 Italia, salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris