Wavelets' filters and higher-order frequency analysis of acoustic emission signals from termite activity. (November 2016)

• Record Type: Journal Article
• Authors: González-de-la-Rosa, Juan-José; Agüera-Pérez, Agustín; Palomares-Salas, José-Carlos; Sierra-Fernández, José-María
• Is Part Of: Measurement. Volume 93(2016)
• Page Start: 315
• Page End: 318
• Publication Date: 2016-11
• Subjects: Acoustic Emission (AE) -- Bi-spectrum -- Discrete Wavelet Transform (DWT) -- Higher-Order Statistics (HOS) -- Spectral Kurtosis (SK) -- Termite detection; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2016.07.037
• Languages: English
• ISSNs: 0263-2241

Abstract

Abstract: A comparative analysis between two higher-order statistics in the frequency domain, combined with wavelets' filters, confirms the existence of three frequency sub-bands that characterize the species emission. De-noising via wavelet eliminates the symmetrical noise and reveals non-Gaussian features. Here, we show that the spectral kurtosis enhances the low and high-frequency components with high power variability, once the filter banks are applied, revealing new zones in the spectrum that are associated to high variability in the amplitudes. Despite de-noising via wavelets, the bi-spectrum is attenuated, but it confirms the frequency pattern of the emission, denoting at the same time the non-zero skewness of these components. Complementarily, it is observed that high bi-frequencies are attenuated more severely, suggesting the idea that certain frequencies content more information regarding symmetry than others. Results have been confirmed using three common wavelet families.