测绘通报 ›› 2026, Vol. 0 ›› Issue (6): 107-111,163.doi: 10.13474/j.cnki.11-2246.2026.0616

• 学术研究 • 上一篇    

基于改进3σ-EMD的GNSS RTK桥梁变形监测信号粗差探测与降噪研究

于丽娜1,2, 张红3, 潘孝军4, 熊春宝1, 齐文聪1,5   

  1. 1. 天津大学建筑工程学院, 天津 300350;
    2. 天津理工大学海洋能源学院, 天津 300384;
    3. 上海同济工程咨询有限公司, 上海 200082;
    4. 三峡(青岛)海洋发展有限公司, 山东 青岛 266400;
    5. 中铁十八局集团, 天津 300000
  • 收稿日期:2025-10-15 发布日期:2026-07-09
  • 通讯作者: 齐文聪。E-mail:2015201078@tju.edu.cn
  • 作者简介:于丽娜(1991—),女,博士,副教授,主要研究方向为结构健康监测与数字孪生、GNSS结构动态变形监测应用。E-mail:yulina@tju.edu.cn
  • 基金资助:
    天津市自然科学基金(25JCQNJC00340);武汉大学测绘遥感信息工程全国重点试验室开放基金(24A05)

Improved 3σ-EMD-based gross error detection and noise reduction for GNSS RTK bridge deformation monitoring signals

YU Lina1,2, ZHANG Hong3, PAN Xiaojun4, XIONG Chunbao1, QI Wencong1,5   

  1. 1. School of Civil Engineering, Tianjin University, Tianjin 300350, China;
    2. School of Ocean Energy, Tianjin University of Technology, Tianjin 300384, China;
    3. Shanghai Tongji Engineering Consulting Co., Ltd., Shanghai 200082, China;
    4. China Three Gorges (Qingdao) Marine Development Co., Ltd., Qingdao 266400, China;
    5. China Railway 18th Bureau Group Co., Ltd., Tianjin 300000, China
  • Received:2025-10-15 Published:2026-07-09

摘要: [目的] 针对传统3σ方法在全球卫星导航系统实时动态定位 (GNSS RTK)监测信号中低幅粗差探测能力不足,以及 EMD 方法对区域态粗差敏感性低的问题,本文基于仿真数据,运用统计及信号处理方法,提出了一种改进3σ-EMD粗差探测与降噪方法,并将其应用于桥梁动态变形监测。[方法]首先,通过3σ法快速识别并修复显著粗差,利用EMD自适应分离高频随机噪声,并通过二次3σ探测优化残余粗差;然后,采用GNSS RTK监测了天津海河大桥的动态变形,并结合改进3σ-EMD方法进行信号降噪处理。[结果]结果表明:改进3σ-EMD方法的粗差探测率(66.7%)优于单一3σ(59.0%)和EMD(25.6%),信噪比(SNR)提升至10.44 dB,较含噪信号(5.74 dB)提高81.9%。降噪处理后GNSS RTK信号幅值由69.70 cm降至34.36 cm,标准差优化至6.78 cm,并准确提取了桥梁振动基频(0.37 Hz)。[结论]改进3σ-EMD方法可有效提升GNSS RTK信号的粗差探测能力与降噪效果,为桥梁结构动态变形监测提供可靠的技术支持。

关键词: GNSS RTK, 桥梁变形监测, 粗差探测, 经验模态分解(EMD), 信号降噪, 改进3σ-EMD

Abstract: [Purposes]To improve the detection of low-amplitude gross errors inglobal navigation satellite system real time kinematic (GNSS RTK) signals,which is limited by the traditional 3σ method,and to address the low sensitivity of empirical mode decomposition (EMD) to regional gross errors,an improved 3σ-EMD algorithm is proposed.[Methods]The algorithm combines experimental and simulated data,utilizing statistical and signal processing techniques to detect and reduce noise in GNSS RTK monitoring signals.It follows a multi-stage strategy: rapid identification and correction of significant gross errors using 3σ,adaptive separation of high-frequency noise via EMD,and residual error optimization through a secondary 3σ process.Applied to dynamic deformation monitoring of Tianjin Haihe Bridge,GNSS-RTK was adopted,and signal denoising was conducted by combining the improved 3σ-EMD method.[Findings]Results show that the improved method achieves a gross error detection rate of 66.7%,outperforming standalone 3σ (59.0%) and EMD (25.6%).The signal to noise ratio is increased to 10.44 dB,an 81.9% improvement over the noisy signal.The algorithm reduced the signal amplitude from 69.70 cm to 34.36 cm,optimized the standard deviation to 6.78 cm,and accurately extracted the bridge's fundamental vibration frequency (0.37 Hz).[Conclusions]The study confirms the robustness of the improved 3σ-EMD algorithm in complex environments,enhancing GNSS RTK signal quality for reliable dynamic deformation monitoring of bridges.

Key words: GNSS RTK, bridge deformation monitoring, gross error detection, empirical mode decomposition (EMD), noise reduction, improved 3σ-EMD

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