摘要
工程病害检测过程中,深部地质异常雷达信号易被环境噪声所湮灭,导致很难进一步识别与判断。为提高地质雷达信号信噪比,结合VMD算法在非线性、自适应及对于采样和噪声处理方面具有更好鲁棒性的特点,将VMD算法应用于富水区雷达降噪过程中,并通过粒子群算法优化VMD降噪过程中关键参数设置,避免因人为设定不当造成的结果偏差与有效数据损失。在考虑相关性系数与地质雷达信号频谱特征的情况下,提出一种模态分量有效性计算指标及其计算方法,将有效性指数极大值分量作为去噪结果,其余分量作为噪声数据,从而实现信噪分离。仿真实验结果表明,基于PSO-VMD的雷达信号去噪算法可实现10 dB以上的信噪比提升,降噪效果明显优于EMD、CEEMD、ICEEMD、ICEEMDAN、NGO-ICEEMDAN等算法,不仅可以较好地分离强环境噪声与异常信息,稳定提升信号信噪比,并且对原始信号异常特征有较好程度保留,为富水强噪声环境下地质雷达的应用提供有力支持。
In the process of engineering disease radar detection,deep geological anomaly radar signals are often annihilated by environmental noise due to signal attenuation,making it difficult to further identify and judge.In order to improve the signal-to-noise ratio of geological radar signals,this paper combined the nonlinear,adaptive,and better robustness of VMD algorithm for sampling and noise processing.VMD algorithm was applied to the noise reduction process of radar in rich water areas,and the key parameter settings in VMD noise reduction process were optimized through particle swarm optimization algorithm to avoid the result deviation and effective data loss caused by human parameter settings.Considering the correlation coefficient and spectral characteristics of geological radar signals,a modal component effectiveness calculation index and its calculation method were proposed.The maximum component of the effectiveness index was used as the denoising result,and the remaining components were used as noise data to achieve signal-to-noise separation.The simulation experiment results show that,the radar signal denoising algorithm based on PSO-VMD can achieve a signal-to-noise ratio improvement of more than 10dB for noisy signals,and the denoising effect is significantly better than EMD,CEEMD,ICEEMD,ICEEMDAN,NGO-ICEEMDAN and other algorithms.It can effectively separate strong environmental noise and abnormal information,stably improve the signal-to-noise ratio,and preserve the abnormal characteristics of the original signal to a good extent,providing strong support for the application of geological radar in water rich and strong noise environments.
作者
吴玄
WU Xuan(China Railway Siyuan Survey and Design Group Co.,Ltd.,Wuhan 430063,China)
出处
《铁道勘察》
2025年第4期83-89,共7页
Railway Investigation and Surveying
基金
中铁第四勘察设计院集团有限公司科技研发计划重点课题(KY2023116E)。
关键词
铁路隧道
信号降噪
仿真实验
地质雷达
粒子群优化
变分模态分解
railway tunnel
signal denoising
simulation experiment
geological radar
particle swarm optimization
variational mode decomposition
