| 宋旸辰,宓超,刘熠,沈阳.一种边坡位移视觉测量装置与方法研究[J].电子测量与仪器学报,2025,39(2):113-122 |
| 一种边坡位移视觉测量装置与方法研究 |
| Research on a visual measurement device and method for slope displacement |
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| DOI： |
| 中文关键词: 高速公路边坡 位移视觉测量 YOLOv8-Pose 关键点识别 亚像素提取 |
| 英文关键词:highway slopes visual measurement of displacement YOLOv8-Pose key point identification sub-pixel extraction |
| 基金项目:上海市科学技术委员会上海市自然科学基金（22ZR1427700）、上海市教育科学研究项目（B2023003）资助 |
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| Author | Institution |
| Song Yangchen | School of Logistics Engineering, Shanghai Maritime University, Shanghai 201306, China |
| Mi Chao | 1.School of Logistics Engineering, Shanghai Maritime University, Shanghai 201306, China; 2.Shanghai SMU Vision Co. Ltd.,
Shanghai 201306, China |
| Liu Yi | School of Logistics Engineering, Shanghai Maritime University, Shanghai 201306, China |
| Shen Yang | 2.Shanghai SMU Vision Co. Ltd.,
Shanghai 201306, China; 3.Higher Institute of Technology, Shanghai Maritime University, Shanghai 201306, China |
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| 摘要点击次数: 25 |
| 全文下载次数: 57 |
| 中文摘要: |
| 针对传统边坡位移监测方法成本高昂，对环境要求高等问题，提出了一种低成本、高精度的边坡位移视觉测量装置及其方法。首先，在监测场景中部署高精度摄像机和特制标志物，利用改进的YOLOv8-Pose算法实现对标志物关键点的初步识别。随后，采用亚像素提取技术对标志物关键点进行处理，以获得其亚像素级别的精确坐标。接着，通过比较不同时刻关键点的坐标偏移量，计算标志物的像素位移变化。最后，结合已知标志物的几何尺寸，通过尺度转换方法计算实际位移变化，从而实现对边坡位移的精确监测。为验证该方法的实际应用效果，选取贵州省某高速公路的边坡进行了现场监测实验。实验结果表明，该视觉测量方法在边坡位移监测中具有良好的精度表现。与全站仪监测结果比较，水平位移的准确率达到了90.43%，竖直位移的准确率为91.58%，均超过90%，充分验证了该方法在实际工程应用中的可行性和有效性。 |
| 英文摘要: |
| Aiming at the problems of high cost and high environmental requirements of traditional slope displacement monitoring methods, a low-cost and high-precision slope displacement visual measurement device and its method are proposed. First, a high-precision camera and a special marker are deployed in the monitoring scene, and the improved YOLOv8-Pose algorithm is utilized to realize the initial recognition of the key points of the marker. Subsequently, a sub-pixel extraction technique is used to process the key point of the marker to obtain its precise coordinates at the sub-pixel level. Next, the pixel displacement change of the marker is calculated by comparing the coordinate offsets of the keypoints at different moments. Finally, the actual displacement change is calculated by the scale conversion method in combination with the known geometric dimensions of the markers, so as to realize the accurate monitoring of slope displacement. In order to verify the practical application effect of the method, this paper selects the slope of a highway in Guizhou Province for on-site monitoring experiments. The experimental results show that the visual measurement method has good accuracy performance in slope displacement monitoring. Compared with the monitoring results of total station, the accuracy of horizontal displacement reaches 90.43%, and the accuracy of vertical displacement is 91.58%, which are more than 90%, fully verifying the feasibility and effectiveness of the method in practical engineering applications. |
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