Title :
Higher-order spectra and independent component analysis used for identification and SNR enhancement of acoustic emission signals
Author :
De la Rosa, J.G. ; Lloret, I. ; Moreno, A. ; Piotrkowski, R. ; Ruzzante, J. ; Puntonet, Carlos G. ; Górriz, J.M.
Author_Institution :
Electron.-Res. Group, Cadiz-Cordoba of Univ., Cadiz
Abstract :
Higher order statistics are used twofold: to characterize, and to enhance and to de-noise primary signals and their echoes in acoustic emission events occurring in samples of steel pipes under transversal strain. First, the characterization by diagonal bi-spectra is performed and it allows the spectral separation of the primary event from the secondary ones (echoes). Secondly, a cumulant-based independent component analysis is applied for blind sources separation in a low-SNR scenario. The method is first validated considering a synthetic of acoustic signals. Then, the developed algorithm is applied to a sequence of quartets of primary bursts and their first three echoes. The denoising capability of ICA is assessed by comparing the power spectra of the sources vs. the separated signals. Data were acquired by wide frequency-range transducers (100-800 kHz) and digitalized by a 2.5 MHz, 8-bit ADC
Keywords :
acoustic signal processing; blind source separation; higher order statistics; independent component analysis; signal denoising; 100 to 800 kHz; 2.5 MHz; ICA; SNR enhancement; acoustic emission signals; blind sources separation; cumulant-based independent component analysis; higher-order spectra; primary signal denoising; Acoustic emission; Acoustic reflection; Educational institutions; Higher order statistics; Independent component analysis; Noise measurement; Nondestructive testing; Signal analysis; Signal processing; Signal to noise ratio;
Conference_Titel :
Electrotechnical Conference, 2006. MELECON 2006. IEEE Mediterranean
Conference_Location :
Malaga
Print_ISBN :
1-4244-0087-2
DOI :
10.1109/MELCON.2006.1653145
