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基于小波-傅里叶变换的堤坝隐患三维雷达谱能比成像研究

Research on the three-dimensional radar spectral energy ratio imaging of dike hidden dangers based on wavelet-fourier transform

  • 摘要: 我国江河堤防普遍存在基础薄弱问题,洪水期堤防易出现渗漏、管涌、滑坡等险情,定期开展快速准确的堤防巡检是堤防安全运行必要环节。探地雷达作为一种有效的地下隐患探测技术,广泛应用于堤坝隐患探测,然而原始雷达信号包含大量高频噪声和背景干扰,在复杂背景中难以准确提取信号特征,常用的傅里叶变换提取雷达信号中频谱信息存在频谱模糊,主频不明显问题,在实际工程探测上具有很大的局限性。针对上述问题,本文提出一种基于小波-傅里叶变换的堤坝隐患三维雷达谱能比成像方法,该方法通过小波变换初步分析雷达信号中非稳定信号和瞬态信号,分层次解析信号不同频率段的特征,然后采用傅里叶变换计算每个时窗内信号和频率上的变化信息,识别信号在各个时刻的频率成分,获取信号中的主频率分量和能量分布,在此基础上基于谱能比信号提出了堤坝隐患类型分级标准,有效的分离出坝体中松散区域和富水区域,从而实现堤坝隐患高效无损检测。最后,依托江西省九江市永修县三角联圩堤坝开展了堤坝现场隐患探测试验,研究结果表明该方法能够有效的探明堤坝中松散区域和富水区域,为堤坝隐患排查提供有力的技术支撑。

     

    Abstract: In China, river embankments often suffer from weak foundation conditions, making them susceptible to seepage, piping, and slope failures during flood seasons. Regular, rapid, and accurate inspections are essential for ensuring the safe operation of embankments. As an effective non-destructive geophysical technique, Ground Penetrating Radar (GPR) has been widely applied in the detection of potential hazards in embankments. However, raw GPR signals often contain considerable high-frequency noise and background interference, making it difficult to extract reliable features under complex field conditions. Traditional spectral analysis methods, such as the Fourier Transform, typically suffer from spectral smearing and unclear dominant frequency components, limiting their practical effectiveness. To address these limitations, this study proposes a 3D spectral energy ratio imaging method based on combined wavelet–Fourier transforms for detecting hidden hazards in embankments. In this approach, wavelet transform is first applied to analyze non-stationary and transient components of the radar signal, allowing for multiscale decomposition of its frequency characteristics. Subsequently, a short-time Fourier transform is used to calculate the temporal evolution of frequency-domain information and extract dominant frequency components and energy distribution across time windows. Based on this, a classification criterion of hazard types is constructed using the spectral energy ratio, enabling the effective separation of loose zones and water-enriched zones within the embankment. This approach facilitates high-resolution, efficient, and non-destructive identification of internal embankment anomalies. Finally, a field investigation was carried out on the Sanjiang Lianwei embankment in Yongxiu County, Jiujiang City, Jiangxi Province. The results demonstrate that the proposed method successfully detects and delineates loose and water-rich areas within the embankment body, providing strong technical support for hazard assessment and routine inspection of earthen dams.

     

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