Study of an underdetermined blind source separation method applied to acoustic inspection of rollers

Jianhao Liu; Hongtao Hao

doi:10.1117/12.3033921

13 June 2024 Study of an underdetermined blind source separation method applied to acoustic inspection of rollers

Jianhao Liu, Hongtao Hao

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 1318029 (2024) https://doi.org/10.1117/12.3033921
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

In the acoustic monitoring of belt conveyor rollers, multiple sound sources and strong noise often impede remote fault diagnosis based on acoustic signals. To address this issue, this study proposes an underdetermined blind source separation method that combines singular spectrum decomposition (SSD) and improved sparse component analysis (SCA), which is suitable for tackling noise interference in roller acoustic inspection systems. Field tests have validated the effectiveness of this method, which reduces reliance on extensive a prior knowledge and the need for numerous sensors, demonstrating outstanding performance in separating sound sources of faulty rollers from multiple noise sources.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jianhao Liu and Hongtao Hao "Study of an underdetermined blind source separation method applied to acoustic inspection of rollers", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 1318029 (13 June 2024); https://doi.org/10.1117/12.3033921

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