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基于监测关键数据的综合智能处理技术研究及应用OA

Research and Application of Integrated Intelligent Processing Technology Based on Key Monitoring Data

中文摘要英文摘要

[目的]为解决滑坡监测数据处理与分析中的准确性和效率问题,提出一种综合智能处理技术以监测关键勘察数据,并开发相应的云平台系统.[方法]该系统通过联合多个数据库,实现了各类监测数据的高效存储与管理.具体而言,采用改进的切线角算法来识别滑坡滑面深度,并基于此构建滑坡三维模型.与传统切线角识别算法的识别正确率 5/12 相比,改进后的算法达到 12/12,识别准确性显著提高.在滑坡模型构建方面,相较于点云模型数小时的构建时间,使用 Three.js 与 Delaunay 生成的方法仅需几秒即可准确构建三维滑坡模型.此外,系统利用 Web-GIS 技术实现了监测数据的可视化管理和预警功能,使用户能够直观地观察滑坡的动态变化和潜在风险.[结果]研究结果表明:该系统能够高效处理和分析多类型监测数据,成功实现滑坡滑带位置、滑体空间尺寸和形态的智能分析与动态监测;实现了滑坡变形数据的连续监测和记录,可全面、持续地追踪滑坡变形的演化过程,从而提高预警的及时性和准确性;提出的综合智能处理技术和云平台为边坡滑坡防治提供了一种通用化、智能化的工具,对滑坡的预防和治理具有重要意义.[结论]所提方法不仅实现了滑坡变形数据的连续监测与记录,还能帮助相关部门及时采取防范措施,保障人民生命和财产安全.

[Objective]To address the accuracy and efficiency problems in landslide monitoring data processing and analysis,an integrated intelligent processing technology for monitoring key survey data is proposed,and a corresponding cloud platform system is developed.[Methods]By integrating multiple databases,the system realized efficient storage and management of various types of monitoring data.Specifically,an improved tangent-angle algorithm was adopted to identify the depth of the landslide slip surface,and a three-dimensional landslide model was constructed on this basis.Compared with the recognition accuracy of 5/12 of the traditional tangent-angle algorithm,the improved algorithm achieved 12/12,significantly improving the recognition accuracy.In terms of landslide model construction,compared with the several hours required for point cloud model construction,the method using Three.js and Delaunay generation could accurately construct a three-dimensional landslide model within only a few seconds.In addition,the system used Web-GIS technology to realize visualized management and early warning of monitoring data,enabling users to intuitively observe dynamic changes and potential landslide risks.[Results]The results showed that the system efficiently processed and analyzed multiple types of monitoring data and successfully realized intelligent analysis and dynamic monitoring of landslide slip-zone position,landslide spatial dimensions,and morphology.It also enabled continuous monitoring and recording of landslide deformation data and could comprehensively and continuously track the evolution of landslide deformation,thereby improving the timeliness and accuracy of early warning.The proposed integrated intelligent processing technology and cloud platform provided a generalized and intelligent tool for slope landslide prevention and control,which was of great significance for landslide prevention and treatment.[Conclusion]The proposed method not only realizes continuous monitoring and recording of landslide deformation data,but also helps relevant departments take timely preventive measures to safeguard people's lives and property.

王亚飞;周根郯;曾长贤;李富年

中铁第四勘察设计院集团有限公司,武汉 430063中铁第四勘察设计院集团有限公司,武汉 430063中铁第四勘察设计院集团有限公司,武汉 430063武汉科技大学信息科学与工程学院,武汉 433081

交通工程

滑坡监测综合智能处理技术云平台Web-GIS,切线角算法

landslide monitoringintegrated intelligent processing technologycloud platformWeb-GIStangent-angle algorithm

《铁道标准设计》 2026 (7)

33-40,8

国家重点研发计划项目(2021YFB2600400)

10.13238/j.issn.1004-2954.202408140002

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