Pulsed eddy current signal denoising based on singular value decomposition

The noise as an undesired phenomenon often appears in the pulsed eddy current testing (PECT) signal, and it is difficult to recognize the character of the testing signal. One of the most common noises presented in the PECT signal is the Gaussian noise, since it is caused by the testing environment. A new denoising approach based on singular value decomposition (SVD) is proposed in this paper to reduce the Gaussian noise of PECT signal. The approach first discusses the relationship between signal to noise ratio (SNR) and negentropy of PECT signal. Then the Hankel matrix of PECT signal is constructed for noise reduction, and the matrix is divided into noise subspace and signal subspace by a singular valve threshold. Based on the theory of negentropy, the optimal matrix dimension and threshold are chosen to improve the performance of denoising. The denoised signal Hankel matrix is reconstructed by the singular values of signal subspace, and the denoised signal is finally extracted from this matrix. Experiment is performed to verify the feasibility of the proposed approach, and the results indicate that the proposed approach can reduce the Gaussian noise of PECT signal more effectively compared with other existing approaches.     

计入能量损失的气泡运动三维数值模拟

在前人研究的基础上,假设能量损失主要发生在气泡体积达到最小的瞬间,通过改变压力参数计及能量损失,结合势流理论,建立气泡三维动力学数值模型。采用边界积分法求解该数值模型,计算得到气泡的动态特性,计算值与实验值吻合良好,验证了数值模型和计算方法的有效性。基于此,分别对自由场中和边界附近的气泡动力学特性进行了模拟,包括水下爆炸气泡以及空化气泡,得到了一些规律性的曲线和结论,旨在为气泡的相关动态特性研究提供参考。