问题

The research addresses the challenge of low signal-to-noise ratio in ultrasonic echo signals caused by interference waves and noise, which hinders accurate defect detection. The study aims to improve the clarity of ultrasound signals.

方法

The study proposes a joint wavelet threshold function denoising method based on WOA-optimized ICEEMDAN. This method optimizes ICEEMDAN parameters using WOA, decomposes the ultrasound signal, separates useful and noise components, and reconstructs the denoised signal.

关键发现

The proposed method was verified by simulation and real experiments. Compared with hard and soft threshold methods, the signal-to-noise ratio improved by 44.8% and 24.9%, while the root-mean-square error declined by 52.3% and 38%, respectively.

3个要点

• The WOA algorithm effectively optimizes ICEEMDAN parameters, enhancing the accuracy of signal decomposition and adaptive parameter setting.
• The joint WOA-ICEEMDAN wavelet thresholding algorithm improves signal performance and denoising effect by addressing valuable information loss.
• Experimental results confirm the algorithm's effectiveness in removing noise and maintaining useful signal information, validated through measured signals.