• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

使用混合惯性视觉系统测量三维结构位移。

Measurement of Three-Dimensional Structural Displacement Using a Hybrid Inertial Vision-Based System.

机构信息

Department of Electrical and Computer Engineering, Southern Methodist University, Dallas, TX 75205, USA.

Department of Civil and Environmental Engineering, Southern Methodist University, Dallas, TX 75205, USA.

出版信息

Sensors (Basel). 2019 Sep 21;19(19):4083. doi: 10.3390/s19194083.

DOI:10.3390/s19194083
PMID:31546595
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6806297/
Abstract

Accurate three-dimensional displacement measurements of bridges and other structures have received significant attention in recent years. The main challenges of such measurements include the cost and the need for a scalable array of instrumentation. This paper presents a novel Hybrid Inertial Vision-Based Displacement Measurement (HIVBDM) system that can measure three-dimensional structural displacements by using a monocular charge-coupled device (CCD) camera, a stationary calibration target, and an attached tilt sensor. The HIVBDM system does not require the camera to be stationary during the measurements, while the camera movements, i.e., rotations and translations, during the measurement process are compensated by using a stationary calibration target in the field of view (FOV) of the camera. An attached tilt sensor is further used to refine the camera movement compensation, and better infers the global three-dimensional structural displacements. This HIVBDM system is evaluated on both short-term and long-term synthetic static structural displacements, which are conducted in an indoor simulated experimental environment. In the experiments, at a 9.75 m operating distance between the monitoring camera and the structure that is being monitored, the proposed HIVBDM system achieves an average of 1.440 mm Root Mean Square Error (RMSE) on the in-plane structural translations and an average of 2.904 mm RMSE on the out-of-plane structural translations.

摘要

近年来,桥梁和其他结构的精确三维位移测量受到了广泛关注。这种测量的主要挑战包括成本和对可扩展仪器阵列的需求。本文提出了一种新颖的基于混合惯性视觉的位移测量(HIVBDM)系统,该系统可以通过使用单目电荷耦合器件(CCD)相机、一个固定的校准目标和一个附加的倾斜传感器来测量三维结构位移。HIVBDM 系统在测量过程中不需要相机保持静止,而相机在测量过程中的运动,即旋转和平移,可以通过在相机视场(FOV)内使用固定的校准目标来补偿。进一步使用附加的倾斜传感器来完善相机运动补偿,并更好地推断全局三维结构位移。在室内模拟实验环境中进行的短期和长期综合静态结构位移实验中对该 HIVBDM 系统进行了评估。在实验中,在监测相机与被监测结构之间的 9.75 米工作距离处,所提出的 HIVBDM 系统在平面内结构平移方面的平均均方根误差(RMSE)为 1.440 毫米,在平面外结构平移方面的平均 RMSE 为 2.904 毫米。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/452ff01bd24a/sensors-19-04083-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/909c50cdc908/sensors-19-04083-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/c90153adc3e9/sensors-19-04083-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/e13a5796c0fc/sensors-19-04083-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/af39a611e281/sensors-19-04083-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/452ff01bd24a/sensors-19-04083-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/909c50cdc908/sensors-19-04083-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/c90153adc3e9/sensors-19-04083-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/e13a5796c0fc/sensors-19-04083-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/af39a611e281/sensors-19-04083-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b57/6806297/452ff01bd24a/sensors-19-04083-g005.jpg

相似文献

1
Measurement of Three-Dimensional Structural Displacement Using a Hybrid Inertial Vision-Based System.使用混合惯性视觉系统测量三维结构位移。
Sensors (Basel). 2019 Sep 21;19(19):4083. doi: 10.3390/s19194083.
2
PTZ Camera-Based Displacement Sensor System with Perspective Distortion Correction Unit for Early Detection of Building Destruction.基于云台摄像机的位移传感器系统,带有用于早期检测建筑物破坏的透视失真校正单元。
Sensors (Basel). 2017 Feb 23;17(3):430. doi: 10.3390/s17030430.
3
Scheimpflug Camera-Based Technique for Multi-Point Displacement Monitoring of Bridges.基于谢伊姆普flug相机的桥梁多点位移监测技术
Sensors (Basel). 2022 May 27;22(11):4093. doi: 10.3390/s22114093.
4
SLAM-based dense surface reconstruction in monocular Minimally Invasive Surgery and its application to Augmented Reality.基于 SLAM 的单目微创手术中密集表面重建及其在增强现实中的应用。
Comput Methods Programs Biomed. 2018 May;158:135-146. doi: 10.1016/j.cmpb.2018.02.006. Epub 2018 Feb 8.
5
Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly Detection.基于标记的结构位移测量模型,使用图像匹配和异常检测进行相机运动误差校正。
Sensors (Basel). 2020 Oct 5;20(19):5676. doi: 10.3390/s20195676.
6
A Vision-Based Sensor for Noncontact Structural Displacement Measurement.一种用于非接触式结构位移测量的基于视觉的传感器。
Sensors (Basel). 2015 Jul 9;15(7):16557-75. doi: 10.3390/s150716557.
7
3D Vision by Using Calibration Pattern with Inertial Sensor and RBF Neural Networks.利用带有惯性传感器和 RBF 神经网络的校准图案进行 3D 视觉
Sensors (Basel). 2009;9(6):4572-85. doi: 10.3390/s90604572. Epub 2009 Jun 11.
8
Continuous Structural Displacement Monitoring Using Accelerometer, Vision, and Infrared (IR) Cameras.使用加速度计、视觉和红外(IR)相机进行连续结构位移监测。
Sensors (Basel). 2023 May 31;23(11):5241. doi: 10.3390/s23115241.
9
Accurate Calibration of a Large Field of View Camera with Coplanar Constraint for Large-Scale Specular Three-Dimensional Profile Measurement.具有共面约束的大视场相机的精确标定及其在大规模镜面三维轮廓测量中的应用。
Sensors (Basel). 2023 Mar 25;23(7):3464. doi: 10.3390/s23073464.
10
A Novel Laser and Video-Based Displacement Transducer to Monitor Bridge Deflections.一种用于监测桥梁挠度的新型激光和视频位移传感器。
Sensors (Basel). 2018 Mar 25;18(4):970. doi: 10.3390/s18040970.

引用本文的文献

1
Drone-based displacement measurement of infrastructures utilizing phase information.利用相位信息的基于无人机的基础设施位移测量。
Nat Commun. 2024 Jan 9;15(1):395. doi: 10.1038/s41467-023-44649-2.
2
A Review of Vision-Laser-Based Civil Infrastructure Inspection and Monitoring.基于视觉激光的民用基础设施检测与监测综述。
Sensors (Basel). 2022 Aug 6;22(15):5882. doi: 10.3390/s22155882.
3
Probabilistic Modeling of Motion Blur for Time-of-Flight Sensors.运动模糊的概率建模在飞行时间传感器中的应用。

本文引用的文献

1
Non-Target Structural Displacement Measurement Using Reference Frame-Based Deepflow.基于参考框架的深度流非目标结构位移测量
Sensors (Basel). 2019 Jul 7;19(13):2992. doi: 10.3390/s19132992.
2
Scour Damage Detection and Structural Health Monitoring of a Laboratory-Scaled Bridge Using a Vibration Energy Harvesting Device.利用振动能量采集装置对实验室规模桥梁的冲刷损伤检测与结构健康监测
Sensors (Basel). 2019 Jun 6;19(11):2572. doi: 10.3390/s19112572.
3
Recent Advances in Piezoelectric Wafer Active Sensors for Structural Health Monitoring Applications.
Sensors (Basel). 2022 Feb 4;22(3):1182. doi: 10.3390/s22031182.
4
CFNet: LiDAR-Camera Registration Using Calibration Flow Network.CFNet:基于标定流网络的激光雷达-相机标定
Sensors (Basel). 2021 Dec 4;21(23):8112. doi: 10.3390/s21238112.
压电晶圆主动传感器在结构健康监测应用中的最新进展。
Sensors (Basel). 2019 Jan 18;19(2):383. doi: 10.3390/s19020383.
4
Drive-By Bridge Frequency Identification under Operational Roadway Speeds Employing Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR).在运行道路速度下采用频率独立欠阻尼钉扎随机共振(FI-UPSR)的驾车过桥频率识别。
Sensors (Basel). 2018 Nov 30;18(12):4207. doi: 10.3390/s18124207.
5
Non-Contact Measurement of the Surface Displacement of a Slope Based on a Smart Binocular Vision System.基于智能双目视觉系统的边坡表面位移非接触测量。
Sensors (Basel). 2018 Aug 31;18(9):2890. doi: 10.3390/s18092890.
6
Structural Health Monitoring in Composite Structures by Fiber-Optic Sensors.基于光纤传感器的复合材料结构健康监测
Sensors (Basel). 2018 Apr 4;18(4):1094. doi: 10.3390/s18041094.
7
Monitoring Bridge Dynamic Responses Using Fiber Bragg Grating Tiltmeters.使用光纤布拉格光栅倾斜仪监测桥梁动态响应
Sensors (Basel). 2017 Oct 20;17(10):2390. doi: 10.3390/s17102390.
8
Computer Vision-Based Structural Displacement Measurement Robust to Light-Induced Image Degradation for In-Service Bridges.基于计算机视觉的在用桥梁结构位移测量,对光致图像退化具有鲁棒性
Sensors (Basel). 2017 Oct 11;17(10):2317. doi: 10.3390/s17102317.
9
Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles.基于互相关的无人机结构系统识别
Sensors (Basel). 2017 Sep 11;17(9):2075. doi: 10.3390/s17092075.
10
Structural Health Monitoring Using Textile Reinforcement Structures with Integrated Optical Fiber Sensors.使用带有集成光纤传感器的纺织增强结构进行结构健康监测。
Sensors (Basel). 2017 Feb 10;17(2):345. doi: 10.3390/s17020345.