Lamb Wave-Based Damage Localization Feature Enhancement and Extraction Method for Stator Insulation of Large Generators Using VMD and Wavelet Transform
Lamb Wave-Based Damage Localization Feature Enhancement and Extraction Method for Stator Insulation of Large Generators Using VMD and Wavelet Transform
复制标题
基于兰姆波的大型发电机定子绝缘损伤定位特征增强与提取方法
DOI：
10.3390/s20154205
复制
发表时间：
2020-08-01
期刊：
影响因子：
3.9
通讯作者：
Hu, Bo
中科院分区：
文献类型：
--
作者：
Li, Ruihua;Luo, Jing;Hu, Bo
兰姆波用于定位大型发电机定子绝缘结构中的任何损坏。然而，在强背景噪声环境下，兰姆波信号的特征提取比较困难，从而大大降低了损伤定位的精度。提出了一种基于变分模式分解(VMD)和小波变换的大型电机定子绝缘损伤信号增强和定位特征提取方法。首先考虑到VMD的特性对噪声敏感，对兰姆波检测信号进行分解、去噪和重构，然后对重构后的信号进行小波变换，提取损伤散射波的飞行时间(TOF)作为损伤定位特征，最后利用TOF特征确定损伤位置。在各种噪声环境下对该方法进行了实验测试和验证。结果表明，VMD和小波变换方法能显著提高兰姆波检测信号的信噪比和强背景噪声下损伤定位的精度。本研究扩展了基于兰姆波的定子绝缘损伤无损检测在复杂环境中的适用性。
Lamb waves are used to locate any damage in the stator insulation structure of large generators. However, it is difficult to extract the features of Lamb wave signals in a strong background noise environment, thus significantly reducing the accuracy with which the damage is located. This paper proposes a method based on variational mode decomposition (VMD) and wavelet transform to enhance and extract the location features of stator insulation damage signals of large motors. First, considering that the characteristics of VMD are sensitive to noise, the Lamb wave detection signal is decomposed, denoised, and reconstructed; the reconstructed signal is then wavelet-transformed to extract the time of flight (TOF) of the damage-scattered wave as the damage location feature; finally, the damage location is determined using the TOF features. The proposed method is experimentally tested and verified under various noise environments. The results show that the VMD and wavelet transform methods can significantly improve the signal-to-noise ratio of Lamb wave detection signals and the accuracy with which the damage is located under strong background noise. This study extends the applicability of Lamb wave-based non-destructive detection of stator insulation damage in complex environments.