国防科技大学学报2018，Vol.40Issue(3)：61-68,8.DOI:10.11887/j.cn.201803010
希尔伯特-黄变换在脉冲涡流信号消噪与识别中的应用
Application of Hilbert-Huang transform inde-noising and recognition of pulse eddy current testing
摘要
Abstract
A de-noising and recognition method based on HHT ( Hilbert-Huang transform ) was proposed to solve the problem that the traditional methods cannot effectively identify the pulse eddy current signals produced by small defects with different sizes.Firstly, the pulse eddy current signal was decomposed by EEMD (ensemble empirical mode decomposition), and the IMFs (intrinsic mode functions) of much noise were selected according to normalized autocorrelation function and its variance.Secondly, the selected IMFs of much noise were removed by the wavelet threshold de-noising, and then the noiseless signal was reconstructed by adding to the non-processed IMFs.Then, the HMS ( Hilbert marginal spectrum) was obtained by using HHT.Finally, according to the difference of HMS, the surface and subsurface defects with different sizes were identified.Experimental results show the effectiveness of the proposed method: the noise of pulsed eddy current signal is eliminated by noise elimination through EEMD, and the method based on HHT can effectively identify cracks of different sizes.关键词
细小裂纹/脉冲涡流信号/希尔伯特-黄变换/集成经验模态分解/希尔伯特边际谱Key words
small defects/pulse eddy current signal/Hilbert-Huang transform/ensemble empirical mode decomposition/Hilbert marginal spectrum分类
信息技术与安全科学引用本文复制引用
张智军,杨博楠,杜金强..希尔伯特-黄变换在脉冲涡流信号消噪与识别中的应用[J].国防科技大学学报,2018,40(3):61-68,8.基金项目
国家自然科学基金资助项目(51507186) （51507186）
陕西省自然科学基金资助项目(2016JQ5004) （2016JQ5004）
