High precision slope deformation monitoring by UAV with industrial photogrammetry

Li, Mingpeng; Cheng, Dehu; Yang, X. B.; Luo, Guangguang; Liu, Ningyao; Meng, Chunyu; Pan, Qi

doi:10.1088/1755-1315/636/1/012015

Cited by 5 publications

(6 citation statements)

References 22 publications

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“…"Image for-mat(Image type): ([]="r"="ras", "b" = "bmp", "t" = "tif", "p" = "pgm", "j" = "jpg","g" = "jpeg", "m" = "ppm")," the type of the input image, for example, in jpg format, enter j (4) Click "Read picture," and the program will read all pictures with "20180520" prefix and display the read picture and progress in the command window (5) Click "to extract the corner [automatic]"; the program first identifies the four corner points of each calibration board and then through detectChecker-boardPoints. M functions all corners of the calibration board for automatic extraction [13]. During the process, the checkerboard number of the length and width of the calibration board and the size of the checkerboard can be input according to the prompts.…”

Section: H ð9þmentioning

confidence: 99%

The Key Technology of Oblique Photogrammetry of Assembled Buildings by UAV

Yao

et al. 2022

Advances in Multimedia

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In order to ensure the disaster control during infrastructure construction and operation, a method of tilt photogrammetry of prefabricated buildings using UAV is proposed. A comparative study of the key steps in the 3D construction process of building (structure) was carried out, and a set of 3D morphology construction method based on UAV tilt photogrammetry was proposed, and the key steps were optimized to realize automation and visualization in the process of model construction. The experimental results show that in the application case of a school district, the error of the three directions is distributed between -4 cm and 4 cm, accounting for 74%, and that between -2 cm and 2 cm, accounting for 37%; the root mean square error of the three directions was calculated to be 4.0 cm, 3.8 cm, and 2.8 cm, respectively. In an engineering application case, the error size of the three directions distributed between -4 cm and 4 cm accounted for 74%, and that between -2 cm and 2 cm accounted for 50%; the root mean square error of the three directions was calculated as 2.3 cm, 2.5 cm, and 3.3 cm, respectively. Conclusion. This method can not only obtain high-precision 3D models of urban complex and single buildings, but also meet the requirements of digital city construction for 3D model construction and obtain clear and high-precision digital land surface model.

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Section: H ð9þmentioning

confidence: 99%

The Key Technology of Oblique Photogrammetry of Assembled Buildings by UAV

Yao

et al. 2022

Advances in Multimedia

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“…The measured horizontal accuracy was 7 cm, and the vertical accuracy was 6 cm. Li et al [73] monitored the deformation of the slope section of large water conservancy projects using UAV aerial photography and achieved a measurement error of less than 3 mm, which was significantly higher than traditional aerial photography methods. Han et al [74] proposed a method of using UAVs to monitor road construction, which was applied to an extended road construction site and accurately identified changed ground areas with an accuracy of 84.5∼85%.…”

Section: Change Detectionmentioning

confidence: 99%

A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications

Zhang

Zhu

2023

Drones

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In recent years, UAV remote sensing has gradually attracted the attention of scientific researchers and industry, due to its broad application prospects. It has been widely used in agriculture, forestry, mining, and other industries. UAVs can be flexibly equipped with various sensors, such as optical, infrared, and LIDAR, and become an essential remote sensing observation platform. Based on UAV remote sensing, researchers can obtain many high-resolution images, with each pixel being a centimeter or millimeter. The purpose of this paper is to investigate the current applications of UAV remote sensing, as well as the aircraft platforms, data types, and elements used in each application category; the data processing methods, etc.; and to study the advantages of the current application of UAV remote sensing technology, the limitations, and promising directions that still lack applications. By reviewing the papers published in this field in recent years, we found that the current application research of UAV remote sensing research can be classified into four categories according to the application field: (1) Precision agriculture, including crop disease observation, crop yield estimation, and crop environmental observation; (2) Forestry remote sensing, including forest disease identification, forest disaster observation, etc.; (3) Remote sensing of power systems; (4) Artificial facilities and the natural environment. We found that in the papers published in recent years, image data (RGB, multi-spectral, hyper-spectral) processing mainly used neural network methods; in crop disease monitoring, multi-spectral data are the most studied type of data; for LIDAR data, current applications still lack an end-to-end neural network processing method; this review examines UAV platforms, sensors, and data processing methods, and according to the development process of certain application fields and current implementation limitations, some predictions are made about possible future development directions.

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“…Te advent of unmanned aerial vehicles (UAVs) has presented a novel solution. UAVs, capable of swiftly capturing video footage of sizable structures, fnd myriad applications in civil engineering, including 3D reconstruction of buildings, dams, and bridges [17][18][19], assessment of seismic damage in buildings [20], long-term monitoring of slope displacements [21], and detection of structural cracks [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Complex Background Removal Method for Video of an Inclined Cable Based on UAV Detection of Structural Vibration Frequencies

Li,

Cao,

et al. 2024

Structural Control and Health Monitoring

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The safety of inclined cables is fundamental to the integrity of cable-stayed bridges. The vibrational frequencies of these cables form the foundation for assessing the cable force. Traditional contact measurement methods necessitate the installation of sensors on each cable, incurring substantial costs. In scenarios where camera placement adjacent to an inclined cable is impractical, noncontact approaches such as video capture via unmanned aerial vehicles prove effective. However, unmanned aerial vehicle-captured videos present a challenge due to their complex background, impeding cable feature recognition. In our study, we initially utilized the Region Growing algorithm for background subtraction. To enhance this method, we integrated it with the unique structural characteristics of cables, leading to the creation of the RGv2 algorithm. This novel algorithm offers increased processing speed and improved accuracy. Furthermore, we combined our method with empirical mode decomposition for effective detection of cable frequency characteristics. We also implemented a hybrid method, combining the K-Means and line segment detector algorithms with empirical mode decomposition. Compared to deep learning techniques for background subtraction, our proposed method demonstrates superior computational efficiency and promising potential for measuring vibrational frequencies of inclined cables.

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High precision slope deformation monitoring by UAV with industrial photogrammetry

Cited by 5 publications

References 22 publications

The Key Technology of Oblique Photogrammetry of Assembled Buildings by UAV

The Key Technology of Oblique Photogrammetry of Assembled Buildings by UAV

A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications

Complex Background Removal Method for Video of an Inclined Cable Based on UAV Detection of Structural Vibration Frequencies

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