Abstract
A cumulant-based independent component analysis (Cum-ICA) is applied for blind source separation (BSS) in a synthetic, multi-sensor scenario, within a non-destructive pipeline test. Acoustic Emission (AE) sequences were acquired by a wide frequency range transducer (100-800 kHz) and digitalized by a 2.5 MHz, 8-bit ADC. Four common sources in AE testing are linearly mixed, involving real AE sequences, impulses and parasitic signals from human activity. A digital high-pass filter achieves a SNR up to -40 dB. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Puntonet, C. G., De-La-Rosa, J. J. G., Lloret, I., & Górriz, J. M. (2006). On the performance of a HOS-based ICA algorithm in BSS of acoustic emission signals. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3889 LNCS, pp. 400–405). https://doi.org/10.1007/11679363_50
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