测绘通报 ›› 2024, Vol. 0 ›› Issue (12): 95-100,105.doi: 10.13474/j.cnki.11-2246.2024.1215

• 工程测量分会年会优选论文 • 上一篇    下一篇

基于GNSS的索道支架长期监测应用分析

许钧涛1, 杨云涛2,3, 张松2,3, 秦双星4, 姚连璧1   

  1. 1. 同济大学测绘与地理信息学院, 上海 200092;
    2. 山东省第一地质矿产勘查院, 山东 济南 250014;
    3. 山东省地矿局索道智能变形监测重点实验室, 山东 济南 250014;
    4. 山东天蒙旅游开发有限公司, 山东 临沂 273402
  • 收稿日期:2024-07-29 发布日期:2024-12-27
  • 通讯作者: 杨云涛,E-mail:54152502@qq.com E-mail:54152502@qq.com
  • 作者简介:许钧涛(2000-),男,硕士,研究方向为工程测量。E-mail:294448068@qq.com
  • 基金资助:
    山东省第一地质矿产勘查院开放基金(2022DY04)

Application analysis of long-term GNSS monitoring for cableway towers

XU Juntao1, YANG Yuntao2,3, ZHANG Song2,3, QIN Shuangxing4, YAO Lianbi1   

  1. 1. College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China;
    2. No. 1 Geological Team of Shandong Provincial Bureau of Geology and Mineral Resources, Jinan 250014, China;
    3. Key Laboratory of Cableway Intelligent Deformation Monitoring of Shandong Provincial Bureau of Geology&Mineral Resources, Jinan 250014, China;
    4. Shandong Tianmeng Tourism Development Co., Ltd., Linyi 273402, China
  • Received:2024-07-29 Published:2024-12-27

摘要: 索道支架是索道的重要结构,在索道检测系统方面多以钢丝绳监测、轿厢监测为主。考虑索道支架的监测数据处理与分析仍存在空白,本文基于沂蒙山望海楼客运索道的实时监测平台,对索道支架进行长期监测。使用脚本工具实现对大量GNSS观测文件的静态解算,并通过K最近邻异常值检测算法对静态解算结果进行检测;综合考虑倾斜仪、气象仪等传感器监测数据及异常分数,对检测的异常日期进行排查,并将排查后的静态解算结果作为支架位移数据,结合倾斜仪的姿态数据对索道支架的长期变化进行分析。结果表明,索道支架日夜数据变化明显,且不同位置的支架变化程度不同,分析结果可为索道支架变形规律及安全监测提供有益的参考。

关键词: 索道支架, 长期监测, GNSS, 异常值检测

Abstract: The cableway towers is a critical component of cableway systems. In the realm of cableway inspection systems, monitoring focuses primarily on wire ropes and elevator cars. However, gaps persist in the processing and analysis of monitoring data specific to cableway towers. This paper presents findings from the real-time monitoring platform of the Wanghailou passenger cableway of Yimengshan, which continuously observes cableway towers. Script tools are employed for static calculations of extensive GNSS observation files. We apply the K-nearest neighbor anomaly detection algorithm to evaluate the static calculation results. By integrating data from sensors such as inclinometers and meteorological instruments, and considering anomaly scores, we validate the abnormal detection dates. The validated static results are then utilized as the displacement data for the bracket, which when combine with the inclinometer's attitude data, are allowed for an analysis of the bracket's long-term changes. The findings reveal significant diurnal variations in the data from the cableway towers, with varying degrees of change at different positions. These results offer valuable insights into the deformation patterns and safety monitoring of cableway towers.

Key words: cableway towers, long-term monitor, GNSS, anomaly detection

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