A multisensor data fusion approach for the volcanic ash granulometry classification

Abstract

In this paper a methodology to be adopted for volcanic ash average granulometry estimation is presented. The main idea is to count the number of ash particles in a known volume. To this purpose a piezoelectric transducer was used to convert ash particles impacts into electrical signals, which provide information about the number of ash particles. Moroever, a couple of infrared (IR) diode-phototransistors allows for the monitoring of the ash level in the instrumented tank. Information from this sensor should be used in a multisensor data fusion approach with information on the ash granulometry gained by the methodology proposed by authors in a previous work. Experimental results showing the suitability of the proposed approach are presented.