Ash fall-out following the explosive activity of volcanoes represents a factor of risk for people and a serious hazard for air traffic, especially if airports are close to the volcanic area. This is the case of the Fontanarossa airport located in Catania, in the south of Italy, close to the Etna volcano. Researchers at DIEEI are facing the challenge of developing a low-cost smart multisensor system to monitor the ash fall-out phenomenon by measuring the average granulometry of ash particles and the ash flow rate. Moreover, the system must be selective in respect to volcanic ash against others sediments such as dust, sand or soil. This paper is particularly focused on the methodology to be adopted for ash granulometry detection. The main idea is to use a piezoelectric transducer to convert ash impacts into electrical signals, which should provide information about the ash granulometry. Experimental results showing the suitability of the proposed approach are presented. Moreover, Receiver Operating Characteristic (ROC) analysis has been proposed as a theoretical support to properly implement the threshold mechanism aimed at ash granulometry classification. (C) 2013 Published by Elsevier B.V.
A smart multisensor system for volcanic ash fall-out monitoring
ANDO', Bruno;BAGLIO, Salvatore;
2013-01-01
Abstract
Ash fall-out following the explosive activity of volcanoes represents a factor of risk for people and a serious hazard for air traffic, especially if airports are close to the volcanic area. This is the case of the Fontanarossa airport located in Catania, in the south of Italy, close to the Etna volcano. Researchers at DIEEI are facing the challenge of developing a low-cost smart multisensor system to monitor the ash fall-out phenomenon by measuring the average granulometry of ash particles and the ash flow rate. Moreover, the system must be selective in respect to volcanic ash against others sediments such as dust, sand or soil. This paper is particularly focused on the methodology to be adopted for ash granulometry detection. The main idea is to use a piezoelectric transducer to convert ash impacts into electrical signals, which should provide information about the ash granulometry. Experimental results showing the suitability of the proposed approach are presented. Moreover, Receiver Operating Characteristic (ROC) analysis has been proposed as a theoretical support to properly implement the threshold mechanism aimed at ash granulometry classification. (C) 2013 Published by Elsevier B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
