噪声频谱混叠干扰下超声检测信号高质量提取方法  

High quality extraction method of ultrasonic detection signals under noise spectrum aliasing interference

作　　者：王辰辰 杨梦冉 姚贞建 Wang Chenchen;Yang Mengran;Yao Zhenjian(Changcheng Institute of Metrology&Measurement,Aviation Industry Corporation of China,Beijing 100095,China;School of Electrical and Information Engineering,Wuhan Institute of Technology,Wuhan 430205,China)

机构地区：[1]中国航空工业集团公司北京长城计量测试技术研究所,北京100095 [2]武汉工程大学电气信息学院,武汉430205

出　　处：《仪器仪表学报》2024年第10期244-252,共9页Chinese Journal of Scientific Instrument

摘　　要：为解决超声检测中噪声频谱混叠导致检测精度低的问题,提出一种数据-模型联合驱动的超声检测信号高质量提取方法。结合经验模态分解和分量聚类指标实现超声检测信号预处理,减小噪声对检测信号提取的影响;基于高斯回波模型,结合时频变换、频谱高斯拟合和人工蜂群算法对预处理信号的模型参数进行准确估计;根据模型参数对信号进行重构,实现超声检测信号高质量提取。仿真结果表明,本文方法可高质量提取信噪比(SNR)低至4.56 dB的超声检测信号,提取信号信噪比均值提升至28.71 dB,提取效果显著优于现有常用方法,如经验模态分解(SNR=9.82 dB)和变分模态分解(SNR=11.07 dB)。此外,超声检测实验证明了本文方法可实现噪声频谱混叠下超声检测信号的高质量提取。To address the issue of low testing accuracy caused by noise spectrum aliasing in ultrasonic testing,a data-model-driven method for high-quality extraction of ultrasonic detection signals is proposed.This approach combines empirical mode decomposition(EMD)with a component clustering index to pre-process the ultrasonic signal,reducing the impact of noise on signal extraction.Using the Gaussian echo model,time-frequency transformation,spectral Gaussian fitting,and the artificial bee swarm algorithm,the model parameters of the pre-processed signals are accurately estimated.The Gaussian echo model is then reconstructed to achieve high-quality signal extraction.Simulation results demonstrate that this method can extract ultrasonic signals with an SNR as low as 4.56 dB,improving the mean SNR of the extracted signals to 28.71 dB—significantly outperforming common methods such as EMD(SNR=9.82 dB)and variational mode decomposition(SNR=11.07 dB).Furthermore,ultrasonic testing experiments confirm the method′s ability to extract high-quality signals even under noise spectrum aliasing interference.

关 键 词：超声检测 频谱混叠 噪声消除 时频变换 模型辨识 

分 类 号：TB52[理学—物理] TH89[理学—声学]