The ash fall-out following explosion activity of volcanoes represents a relevant factor of risk for people and facilities in the area near the volcano and a serious hazard for air traffic civil and otherwise [1] mainly when airports are close to active volcanoes. This is the case of the international Fontanarossa Airport in Catania close to Mount Etna. Researchers at DIEEI of the University of Catania are facing the challenge of developing a low-cost smart multisensor system for the monitoring of ash fall-out phenomena by measuring ash presence, average granulometry and ash flow rate. Moreover, the system must discriminate volcanic ash from others sediments such as dust, sand or soil. This paper is particularly focused on the methodology adopted for ash granulometry detection. The main idea is to use a piezoelectric transducer to convert ash impacts in electrical signals which should provide information about ash granulometry. Experimental investigations have been performed using volcanic ash with three different granulometries (big, medium and small) ranging from 2 mm to 0.2 mm. Experimental results are presented together with the methodology developed to classify ash granulometry. (C) 2012 Elsevier Ltd....Selection and/or peer-review under responsibility of the Symposium Cracoviense Sp. z.o.o.

A Smart Multisensor System for the Ash Fall-Out Monitoring

Ando B;Baglio S;Marletta V
2012-01-01

Abstract

The ash fall-out following explosion activity of volcanoes represents a relevant factor of risk for people and facilities in the area near the volcano and a serious hazard for air traffic civil and otherwise [1] mainly when airports are close to active volcanoes. This is the case of the international Fontanarossa Airport in Catania close to Mount Etna. Researchers at DIEEI of the University of Catania are facing the challenge of developing a low-cost smart multisensor system for the monitoring of ash fall-out phenomena by measuring ash presence, average granulometry and ash flow rate. Moreover, the system must discriminate volcanic ash from others sediments such as dust, sand or soil. This paper is particularly focused on the methodology adopted for ash granulometry detection. The main idea is to use a piezoelectric transducer to convert ash impacts in electrical signals which should provide information about ash granulometry. Experimental investigations have been performed using volcanic ash with three different granulometries (big, medium and small) ranging from 2 mm to 0.2 mm. Experimental results are presented together with the methodology developed to classify ash granulometry. (C) 2012 Elsevier Ltd....Selection and/or peer-review under responsibility of the Symposium Cracoviense Sp. z.o.o.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/46735
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