The monitoring of the acoustic emissions (AEs) due to rock fracturing allows the detection of the rockfall precursor signals, leading to a strong improvement of the real time assessment of the induced risk. A network of piezoelectric sensors (PZTs) provides reliable AE data, as testified by a series of applications in non-destructive testing, but PZTs are strongly affected by lightings and electromagnetic interference. In order to avoid such PZT drawbacks and limitations and therefore to allow the rock fracturing monitoring in unstable slopes, two FOS architectures (referred to as fibre coil sensor and ferrule top cantilever) have been recently proposed in previous works from the same authors. In this paper, the two sensors are tested in a more realistic scenario, by monitoring AE in a rock block in which crack is induced by highly expansive mortar; complementary activities, mainly aimed at the recognition of the type of expected signals and optimisation of the sensor array in the framework of the monitoring system, are also described here.
Rockfall precursor detection based on rock fracturing monitoring by means of optical fibre sensors
L. Schenato;PALMIERI, LUCA;AUTIZI, ENRICO;TEZA, GIORDANO;SASSI, RAFFAELE;GALGARO, ANTONIO;GALTAROSSA, ANDREA
2013
Abstract
The monitoring of the acoustic emissions (AEs) due to rock fracturing allows the detection of the rockfall precursor signals, leading to a strong improvement of the real time assessment of the induced risk. A network of piezoelectric sensors (PZTs) provides reliable AE data, as testified by a series of applications in non-destructive testing, but PZTs are strongly affected by lightings and electromagnetic interference. In order to avoid such PZT drawbacks and limitations and therefore to allow the rock fracturing monitoring in unstable slopes, two FOS architectures (referred to as fibre coil sensor and ferrule top cantilever) have been recently proposed in previous works from the same authors. In this paper, the two sensors are tested in a more realistic scenario, by monitoring AE in a rock block in which crack is induced by highly expansive mortar; complementary activities, mainly aimed at the recognition of the type of expected signals and optimisation of the sensor array in the framework of the monitoring system, are also described here.Pubblicazioni consigliate
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