马骏, 吴开志, 李新民, 俞子荣. 时空域相关自适应小波包声发射信号降噪方法[J]. 南昌航空大学学报(自然科学版), 2018, 32(1): 90-96. DOI: 10.3969/j.issn.1001-4926.2018.01.015
引用本文: 马骏, 吴开志, 李新民, 俞子荣. 时空域相关自适应小波包声发射信号降噪方法[J]. 南昌航空大学学报(自然科学版), 2018, 32(1): 90-96. DOI: 10.3969/j.issn.1001-4926.2018.01.015
MA Jun, WU Kai-zhi, Li Xin-min, YU Zi-rong. Time-spatial Correlation Based Adaptive Wavelet Packet Method of Acoustic Emission (AE) Signal De-noising[J]. Journal of nanchang hangkong university(Natural science edition), 2018, 32(1): 90-96. DOI: 10.3969/j.issn.1001-4926.2018.01.015
Citation: MA Jun, WU Kai-zhi, Li Xin-min, YU Zi-rong. Time-spatial Correlation Based Adaptive Wavelet Packet Method of Acoustic Emission (AE) Signal De-noising[J]. Journal of nanchang hangkong university(Natural science edition), 2018, 32(1): 90-96. DOI: 10.3969/j.issn.1001-4926.2018.01.015

时空域相关自适应小波包声发射信号降噪方法

Time-spatial Correlation Based Adaptive Wavelet Packet Method of Acoustic Emission (AE) Signal De-noising

  • 摘要: 现有的小波变换方法在对受强噪声干扰的声发射信号降噪时,由于忽略了小波系数之间的相关性,容易造成信号失真。针对该问题,提出了一种基于时空域相关性的自适应小波包声发射信号降噪方法。算法采用自适应冗余小波变换,最大限度保留了信号的时域空域特征,并利用小波系数在时域空域上存在的相关性,提高对声发射信号及噪声的甄别能力,提升降噪效果。同时利用小波系数在空域上的相关性寻找最佳分解层数,进一步提升了算法的适应性。为了验证本文提出算法的有效性,分别在模拟声发射信号和断铅信号上添加不同程度的噪声,并进行降噪实验。实验结果表明,与其他算法相比,经过本文算法处理的信号信噪比大大提高,均方根误差也有一定程度的降低。

     

    Abstract: Existing wavelet transform method in the strong noise interference AE signal de-noising, due to ignore the correlation between the wavelet coefficients, easily lead to signal distortion. To solve the problem, a time-spatial correlation based adaptive wavelet packet method was proposed to Acoustic Emission (AE) signal de-noising. Adaptive redundant wavelet transform was used to maximize the time-spatial features in the algorithm. The correlation of the wavelet coefficients in time-spatial domain were used to improve the discrimination ability of AE signal and noise, It were improves the effect of noise reduction. Meanwhile, the correlation of wavelet coefficients in spatial domain was used to find the best decomposition level to further improve the adaptability of the algorithm. In order to validate the effectiveness of the proposed algorithm, different levels of noise are added to the simulated AE signal and the disconnected lead signal respectively, and the noise reduction experiment is carried out. Experimental results show that the SNR of the signal processed by this algorithm is greatly improved compared with that of the other algorithms, and the RMSE is also reduced to a certain extent.

     

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