Denoising low SNR percussion acoustic signal in the marine environment based on the LMS algorithm

Percussion-based inspection of structures has attracted widespread attention in recent years. However, the percussion acoustic signals collected in the marine environment usually have a low signal-to-noise ratio (SNR) and are difficult to use directly due to the interference by a multitude of marine noises. The frequency contents of the ambient noises usually overlap with those of the percussion acoustic signals, thus limiting the denoising using traditional methods. This paper proposes a denoising method using the least mean square (LMS) algorithm to obtain the approximate percussion signal. The noisy percussion signals and marine noise are recorded syn-chronously by two hydrophones. Then the LMS algorithm processes the collected signals and provides the fre-quency peaks that cannot be extracted with conventional methods. The proposed method is validated by experiments conducted in a noiseless laboratory environment and a noisy, naturally occurring marine envi-ronment. The results reveal that the proposed method is excellent in denoising the raw signal, and the error is about 3% in terms of differences in the estimated value of the primary peak frequency. This study demonstrates the broad potential for the method to be applied toward damage detection for underwater structures.

Automated summary

This paper proposes a denoising method using the least mean square (LMS) algorithm for percussion acoustic signals collected in the marine environment. The method is validated by experiments and shows excellent performance in denoising the raw signals with a small error in the estimated primary peak frequency. This study demonstrates the broad potential for the method to be applied towards damage detection for underwater structures.