基于可见-红外双光航探的堤坝渗漏智能温度感知

Integration of visible and infrared aerial imaging for intelligent thermal monitoring of dam leakage

  • 摘要: 渗漏是土石堤坝工程最典型的病害险情,及时发现渗漏隐患是保障堤坝安全的关键。本研究基于土石堤坝渗漏与温度的关联特性,系统阐释了红外热成像技术应用于堤坝渗漏非接触式探测的实现原理,提出了一种基于双回路PID控制的牛耕巡检方法,并结合自适应区域生长法及IHS(Intensity-Hue-Saturation Fusion)异源图像融合技术,构建一套基于热红外遥感图像的智能化渗漏识别方法,并以黑河市象山水库堤坝工程为研究实例。结果表明:热红外遥感图像能形象直观地呈现渗漏引起的温度异常,表现为内小外大的等温梯度分层变化;自适应区域生长法能够自动并准确地识别渗漏区域,能显著提升渗漏检测的效率和适应性;IHS异源图像融合能获得高对比度、多维度信息的土石堤坝渗漏险情红外与可见双光融合图像,为堤坝渗漏巡检与识别问题提供一种可行的技术方法。

     

    Abstract: Leakage represents one of the most critical failure modes in earth-rock dam engineering, and timely detection of leakage hazards is essential for ensuring dam safety. Based on the correlation between leakage and temperature distribution in earth-rock dams, this study systematically elucidates the principle of applying infrared thermal imaging technology for non-contact leakage detection. A boustrophedon scanning path model based on dual-loop PID control is proposed. Combined with an adaptive region-growing algorithm and IHS (Intensity-Hue-Saturation) image fusion technique, an intelligent leakage identification method is developed using thermal infrared remote sensing images, with the Xiangshan Reservoir dam project in Heihe City as a case study. The results demonstrate that thermal infrared imagery can effectively visualize temperature anomalies caused by leakage, characterized by a distinct temperature gradient that decreases inward and increases outward. The adaptive region-growing method achieves automatic and accurate identification of leakage areas, significantly improving detection efficiency and adaptability. Furthermore, the IHS-based multi-source image fusion generates high-contrast, multi-dimensional fused images integrating infrared and visible spectra, providing a technically viable solution for dam leakage inspection and identification.

     

/

返回文章
返回