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Título
Acoustic detection and localisation system for Hylotrupes bajulus L. larvae using a MEMS microphone array
Año del Documento
2023
Editorial
Elsevier
Documento Fuente
Roberto D. Martínez, Alberto Izquierdo, Juan José Villacorta, Lara del Val, Luis-Alfonso Basterra, Acoustic detection and localisation system for Hylotrupes bajulus L. larvae using a MEMS microphone array, Applied Acoustics, Volume 213, 2023, 109618, ISSN 0003-682X,
Resumen
A novel system for acoustic detection of the presence of xylophagous insect larvae inside structural timber beams is presented. It is based on an extensive array of MEMS microphones that allows the acoustic detection and localisation of the larvae when they are active. In a first phase, the activity of the larvae is continuously detected by means of frequency filtering and a sliding energy estimator, and after that, a set of short-duration segmented signals is generated, which obtains the spatial localisation of the larvae, by means of a shaping algorithm based on delay-sum beamforming techniques. The tests carried out demonstrate that it is possible to detect and locate multiple larvae of Hylotrupes bajulus L. inside structural-sized pieces of wood of Pinus syilvestris L., as well as their internal trajectory. In the future, the system could address the identification of the specific type of xylophage responsible for the deterioration by using machine learning or equivalent techniques, based on the temporal and frequency information of the detected sound events. The aim of this work is to control unintentional infestions in the international timber trade, in the assembly and the use of infested timber and, in all cases, to be able to carry out selective, targeted and localised treatments and to verify their success.
Palabras Clave
Wood-boring larvae identification; Beamforming; MEMS microphone array; Timber trade safeguard; Targeted treatment methods
ISSN
0003-682X
Revisión por pares
SI
Idioma
spa
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
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Tamaño:
10.66Mb
Formato:
Adobe PDF
La licencia del ítem se describe como Attribution-NonCommercial-NoDerivs 3.0 Unported