Research on noise reduction method for acoustic emission signals based on Kalman filtering

Panlong Sheng; Pengju He; Yimei Xu

doi:10.1117/12.3033645

13 June 2024 Research on noise reduction method for acoustic emission signals based on Kalman filtering

Panlong Sheng, Pengju He, Yimei Xu

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131802R (2024) https://doi.org/10.1117/12.3033645
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

Based on the Cloud-Edge system architecture proposed by the research team, this article investigates the method of Kalman filtering in acoustic emission signal denoising processing. Acoustic emission (AE) signals are small sounds generated when a material is subjected to stress or deformation, often disturbed by environmental noise, which reduces the clarity and usability of the signal. In order to effectively reduce the impact of noise on AE signals, this paper adopts the Kalman filtering algorithm. By dynamically modeling and estimating the signal, noise suppression and signal recovery are achieved. Through comparative experiments and analysis, it has been proven that the proposed method has significant advantages in noise reduction and signal fidelity of acoustic emission signals, and has good application prospects.

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

Citation Download Citation

Panlong Sheng, Pengju He, and Yimei Xu "Research on noise reduction method for acoustic emission signals based on Kalman filtering", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131802R (13 June 2024); https://doi.org/10.1117/12.3033645

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