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.
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Puntonet, C.G., de-la-Rosa, JJ.G., Lloret, I., Górriz, JM. (2006). On the Performance of a HOS-Based ICA Algorithm in BSS of Acoustic Emission Signals. In: Rosca, J., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363_50
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DOI: https://doi.org/10.1007/11679363_50
Publisher Name: Springer, Berlin, Heidelberg
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