Automated acoustic identification of beetle larvae in imported goods using time domain analysis

The detection of insect pests in imported goods is of considerable economic importance and the automation of this process is becoming more viable both technologically and financially. As a result, the Department for Environment, Food and Rural Affairs in the UK has funded a research project to devel...

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Veröffentlicht in:The Journal of the Acoustical Society of America 2008-05, Vol.123 (5_Supplement), p.3778-3778
Hauptverfasser: Schofield, James, Chesmore, David
Format: Artikel
Sprache:eng
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Zusammenfassung:The detection of insect pests in imported goods is of considerable economic importance and the automation of this process is becoming more viable both technologically and financially. As a result, the Department for Environment, Food and Rural Affairs in the UK has funded a research project to develop instrumentation facilitating real-time acoustic detection of the feeding activity of insect larvae inside imported goods, such as timber. The instrumentation will also be capable of species-level identification. Previous work at York has shown that detection of beetle larvae in wood is possible using low cost piezoelectric sensors. The project described here extends this work by investigating a number of signal analysis methods for robust detection of biting events, including fractal dimension analysis. Identification is currently being carried out using time domain signal coding and artificial neural networks. This paper will concentrate on the results of various algorithms for the estimation of fractal dimension and their relative suitability for bite detection. The effects of varying sampling rates, threshold levels and signal-to-noise ratio on the detection rate will be demonstrated.
ISSN:0001-4966
1520-8524
DOI:10.1121/1.2935411