Settlement observation method and system based on aerial photography measurement

Abstract

The invention discloses a settlement observation method based on aerial photography measurement, and relates to the technical field of engineering surveying, and the observation steps are as follows: S1, establishing a reference point on a building to be observed as a reference data point, marking and sorting the reference point, and establishing a proportional scale value of an image and an actual height; and S2, performing aerial photography on the to-be-observed building at a preset height position by using the unmanned aerial vehicle to obtain an aerial photography image. The invention further discloses a settlement observation system based on aerial photography measurement. According to the invention, a large-area and high-resolution building image to be observed can be obtained through aerial photography of the unmanned aerial vehicle, photographing is carried out from different angles and heights, and compared with a traditional ground measurement means, the limitation of terrains is avoided, the data acquisition efficiency is improved, the settlement rate is obtained, whether the building has potential safety hazards or not is found in time, and adjustment measures are taken.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering surveying, and in particular to a settlement observation method and a system thereof based on aerial photography surveying. Background Art

[0002] Settlement observation is to observe according to the observation points set up in the building and the fixed detection points, and express the degree of settlement with data. For buildings and structures with more than one floor, if the design requires the setting of observation points, settlement observations should be set up for artificial and land foundations. During construction, observations and records should be made on schedule or by layer until completion. Settlement observation is an important part of ensuring project quality and safe operation. Traditional settlement observation methods mainly use level and total station ground measuring instruments for manual measurement. Although these methods have high measurement accuracy, they have low measurement efficiency, high labor intensity, and are greatly restricted by terrain and environment. When measuring in large areas, complex terrain or areas that are difficult for people to reach, traditional methods are often difficult to implement and cannot reflect the dynamic changes of project settlement in a timely manner. In this regard, we proposed a settlement observation method and system based on aerial photography. Summary of the invention

[0003] In order to solve the above technical problems, a settlement observation method and system based on aerial photography measurement are provided. This technical solution solves the above problems of large terrain restrictions and low measurement efficiency.

[0004] In order to achieve the above purpose, the technical solution adopted by the present invention is: a settlement observation method based on aerial photography measurement, and the observation steps are:

[0005] S1. Establish reference points on the building to be observed as reference data points, mark and organize the reference points, and establish the scale value of the image and the actual height;

[0006] S2. Use a drone to take aerial photos of the building to be observed at a preset height to obtain aerial images;

[0007] S3, uploading the acquired aerial image to the image analysis module, analyzing the image based on the image analysis module, preprocessing the image, extracting the reference points of the building to be observed in the image based on the SIFT algorithm, and calculating the height position of the reference points in the image;

[0008] S4. In different time periods, use a drone to take aerial photos of the building to be observed again at the same height, obtain images of the building to be observed at the same position, analyze them again, obtain height position data of several reference points, and mark them;

[0009] S5, comparing and calculating the first recorded reference point data with the last recorded reference point data in the two-dimensional image to obtain a height difference, and converting the difference to a specific value according to a scale, which is the settlement amount;

[0010] S6. Analyze the settlement rate to obtain a threshold value of the safe settlement rate. If the rate is greater than the threshold, there is a safety hazard in the building, and further adjustment measures are taken for the building.

[0011] Preferably, in step S1, the reference point position is selected as a reference point with a stable structure, not easily affected by external interference and a representative building, and is marked for observation by the drone; the scale is established by selecting a reference object with a known precise height on the ground at the bottom of the building, including a standard height benchmark and a measured vertical wall, using a drone to photograph the building and the reference object according to predetermined aerial photography parameters, and obtaining a clear aerial image containing the building and the reference object, based on image processing, identifying and measuring the pixel height value of the reference object in the image, and combining the actual height of the reference object, the scale value between the image and the actual height is calculated according to the proportional relationship; the calculation formula is: k=h1 / h2, where k is the calculated scale value, h1 is the actual height of the known reference object, and h2 is the height of its pixel measured in the image.

[0012] Preferably, in step S2, before performing the aerial photography operation, the flight route is planned. After the flight route is determined, the shooting parameters are adjusted to ensure that the entire building can be captured completely and clear image details can be obtained. The optimal aerial photography altitude is determined through multiple flight experiments, and the image quality is optimized by turning on the camera's noise reduction function. The flight shooting is performed and the reference points on the building are photographed by flying to a predetermined altitude. After the aerial photography mission is completed, the drone is controlled to land safely and the aerial image data captured is transmitted to the image analysis module.

[0013] Preferably, the image preprocessing in step S3 includes denoising and grayscale processing. The denoising adopts the median filtering algorithm, and the median of the pixel grayscale value in the field of each pixel in the image is selected to replace the original grayscale value of the pixel to achieve the purpose of denoising. The grayscale is processed by the averaging method, and the pixel values ​​of the three channels R, G, and B of each pixel in the color image are added, and then the average value is taken as the grayscale value of the pixel. The processing formula is: Gray = (R+G+B) / 3, where R, G and B are the pixel values ​​of the three channels of the pixel.

[0014] Preferably, the SIFT algorithm formula in step S3 is:

[0015]

[0016] Where (x, y) is the coordinate of the feature point of the reference point on the image, (x0, y0) is the coordinate of the principal point, f is the focal length of the camera, (Xs, Ys, Zs) is the coordinate position of the camera, (a1, b1, c1), (a2, b2, c2) and (a3, b3, c3) are the elements of the camera posture rotation matrix, (X, Y, Z) is the coordinate of the reference point in the set ground coordinate system associated with the actual position of the building, and the height position of the reference point in the image is determined by the above calculation.

[0017] Preferably, in step S4, the drone is kept at the same height during multiple shootings, and aerial monitoring is performed every few months. When a predetermined time period is reached, the drone is controlled at the same height to conduct a comprehensive and detailed aerial photography operation on the building to be observed again along a pre-planned and optimized flight route, and multiple image data are obtained and marked and organized.

[0018] Preferably, the comparison calculation formula in step S5 is: △h3=h4-h5, wherein △h3 is the calculated difference value, h4 is the height coordinate value of the first recorded reference point in the image, and h5 is the height value of the last recorded reference point in the image.

[0019] Preferably, the formula for calculating the settlement amount based on scale conversion is: D=△h3*k, where D is the calculated settlement amount value.

[0020] Preferably, the sedimentation rate calculation formula in step S6 is:

[0021]

[0022] Where v is the settlement rate, D2 is the second observed settlement, D1 is the first observed settlement, t2 is the time of the second observation, and t1 is the time of the first observation. The calculated settlement rate v is compared with the safe settlement rate threshold. If the actual settlement rate is greater than the safe settlement rate threshold, it indicates that there is a safety hazard in the building. The foundation reinforcement technology is used to reinforce the soft foundation, improve the bearing capacity and stability of the foundation, and slow down or prevent the continued development of settlement.

[0023] The settlement observation system based on aerial photography measurement includes: aerial photography module, image analysis module, ratio conversion module, settlement amount calculation module and settlement rate analysis module;

[0024] The aerial photography module includes a drone unit and a camera unit, which are used to take aerial photos of buildings and obtain image data;

[0025] The image analysis module is used to pre-process the image and analyze the location of the building's reference point in the image;

[0026] The scale conversion module is used to establish the scale value between the image and the actual height;

[0027] The settlement calculation module is used to calculate the height difference and the settlement of the building based on the scale value;

[0028] The settlement rate analysis module is used to analyze the settlement rate and further adjust the buildings that have safety hazards.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention proposes that large-area, high-resolution images of the buildings to be observed can be obtained through drone aerial photography, and shooting can be performed from different angles and heights. Compared with traditional ground measurement methods, it avoids terrain limitations, improves data collection efficiency, obtains settlement rate, and promptly discovers whether there are safety hazards in the buildings and makes adjustment measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart of the observation steps of the present invention;

[0032] Figure 2 This is a framework diagram of the observation system of the present invention. DETAILED DESCRIPTION

[0033] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0034] Reference Figure 1 As shown in the figure, the settlement observation method based on aerial photography measurement has the following observation steps:

[0035] S1. Establish reference points on the building to be observed as reference data points, mark and organize the reference points, and establish the scale value of the image and the actual height;

[0036] S2. Use a drone to take aerial photos of the building to be observed at a preset height to obtain aerial images;

[0037] S3, uploading the acquired aerial image to the image analysis module, analyzing the image based on the image analysis module, preprocessing the image, extracting the reference points of the building to be observed in the image based on the SIFT algorithm, and calculating the height position of the reference points in the image;

[0038] S4. In different time periods, use a drone to take aerial photos of the building to be observed again at the same height, obtain images of the building to be observed at the same position, analyze them again, obtain height position data of several reference points, and mark them;

[0039] S5, comparing and calculating the first recorded reference point data with the last recorded reference point data in the two-dimensional image to obtain a height difference, and converting the difference to a specific value according to a scale, which is the settlement amount;

[0040] S6. Analyze the settlement rate to obtain a threshold value of the safe settlement rate. If the rate is greater than the threshold, there is a safety hazard in the building, and further adjustment measures are taken for the building.

[0041] This application uses drones for aerial photography, and there is no need to install complex contact measurement equipment on the building, which avoids causing additional load or potential damage to the building structure. This is especially important for some historical buildings, ancient buildings or modern buildings with high requirements for appearance. It can conduct settlement observation without affecting its normal use and appearance integrity. Whether it is a building located in a mountainous area or a waterside area with complex terrain, or a building in a city with tall buildings and narrow space, the drone can easily reach the predetermined observation position for aerial photography;

[0042] The reference points extracted by the SIFT algorithm have good scale invariance and rotation invariance characteristics, and can accurately match the same feature points in images taken at different times. Even if the building has certain appearance changes or the shooting angle is slightly different, it will not affect the recognition and positioning of the reference points.

[0043] The analysis of the settlement rate and the comparison with the safety threshold can promptly detect whether the building settlement is abnormal. Once the settlement rate exceeds the threshold, an early warning signal can be quickly issued, allowing relevant personnel to take corresponding adjustment measures before serious safety problems occur in the building. This early warning mechanism can effectively reduce the risk of safety accidents and ensure the safety of life and property of people in the building and the stability of the surrounding environment.

[0044] In step S1, the reference point position is selected as a reference point with a stable structure, not easily affected by external interference and a representative building, and is marked for drone observation; the scale is established by selecting a reference object with a known precise height on the ground at the bottom of the building, including a standard height benchmark and a measured vertical wall, using a drone to shoot the building and the reference object according to predetermined aerial photography parameters, and obtaining a clear aerial image containing the building and the reference object. Based on image processing, the pixel height value of the reference object in the image is identified and measured, and at the same time, combined with the actual height of the reference object, the scale value between the image and the actual height is calculated based on the proportional relationship; the calculation formula is: k=h1 / h2, where k is the calculated scale value, h1 is the actual height of the known reference object, and h2 is the height of its pixel measured in the image.

[0045] This application selects a location with a stable structure and not easily affected by external interference as a reference point, which can minimize the displacement or deformation of the reference point itself due to environmental factors, thereby ensuring the stability and reliability of its coordinate data; by selecting a reference object with a known precise height on the ground at the bottom of the building and combining it with drone aerial photography to establish a scale value, a reliable quantitative basis is provided for accurately converting the two-dimensional data in the image into actual three-dimensional height information.

[0046] In step S2, before the aerial photography operation, the flight route is planned. After the flight route is determined, the shooting parameters are adjusted to ensure that the entire building can be captured and clear image details can be obtained. The best aerial photography altitude is determined through multiple flight experiments. The image quality is optimized by turning on the camera's noise reduction function. The flight shooting is carried out to the predetermined altitude to shoot the reference points on the building. After the aerial photography mission is completed, the drone is controlled to land safely and the aerial image data captured is transmitted to the image analysis module.

[0047] This application plans the flight route in advance and determines the flight route, which can ensure that the drone systematically and comprehensively covers the buildings to be observed, avoids missing important areas, and thus obtains complete building image information. Reasonable route planning can also optimize the flight path, reduce unnecessary flight time and energy consumption, and improve data collection efficiency. Especially when observing large buildings or building complexes, efficient flight planning can significantly shorten the overall operation time; after the aerial photography mission is completed, the image data will be transmitted to the image analysis module in a timely manner, realizing the rapid flow and centralized processing of data.

[0048] Image preprocessing in step S3 includes denoising and grayscale processing. Denoising uses the median filtering algorithm, and the median of the pixel grayscale values ​​within the area of ​​each pixel in the image is selected to replace the original grayscale value of the pixel to achieve the purpose of denoising. Grayscale is processed using the averaging method, and the pixel values ​​of the three channels R, G, and B of each pixel in the color image are added, and then the average value is taken as the grayscale value of the pixel. The processing formula is: Gray = (R+G+B) / 3, where R, G, and B are the pixel values ​​of the three channels of the pixel.

[0049] The median filtering algorithm of this application has unique advantages in removing noise. Compared with other filtering methods, it does not simply perform weighted averaging on pixels, but replaces the grayscale value of the current pixel by selecting the median grayscale value of the pixel in the neighborhood. This method is particularly effective in removing salt and pepper noise and impulse noise. The image denoised by median filtering has more stable and reliable data. In the subsequent feature extraction and analysis process, stable data helps to improve the accuracy and robustness of the algorithm.

[0050] Converting color images to grayscale images can greatly reduce the complexity of data. In the image analysis of settlement observation, color information is not a key factor in extracting the benchmark points of buildings and calculating the height position. Instead, it will increase the amount of data and calculation. Through grayscale processing, the values ​​of the three RGB channels of each pixel are converted into a grayscale value, which reduces the data dimension and makes subsequent image processing and analysis more efficient. The SIFT algorithm formula in step S3 is:

[0051]

[0052] Where (x, y) is the coordinate of the feature point of the reference point on the image, (x0, y0) is the coordinate of the principal point, f is the focal length of the camera, (Xs, Ys, Zs) is the coordinate position of the camera, (a1, b1, c1), (a2, b2, c2) and (a3, b3, c3) are the elements of the camera posture rotation matrix, (X, Y, Z) is the coordinate of the reference point in the set ground coordinate system associated with the actual position of the building, and the height position of the reference point in the image is determined by the above calculation.

[0053] The SIFT algorithm in this application is an algorithm for detecting and describing local features of an image. Its core is to find representative feature points in different scale spaces and describe these feature points so that these feature points can still be accurately matched and identified when the image is translated, rotated, scaled, and has a certain degree of lighting changes.

[0054] In step S4, the drone is kept at the same altitude during multiple shots, and aerial monitoring is performed every few months. When the predetermined time period is reached, the drone is controlled at the same altitude to conduct a comprehensive and detailed aerial photography operation of the building to be observed again along a pre-planned and optimized flight route, and multiple image data are obtained and marked and organized.

[0055] This application conducts aerial monitoring every few months, which can construct time series data of building settlement changes over time. By collecting data over a long period of time and regularly, the development trend of settlement can be clearly observed, such as whether it is uniform settlement, accelerated settlement or gradually stabilizing.

[0056] The comparison calculation formula in step S5 is: △h3=h4-h5, where △h3 is the calculated difference value, h4 is the height coordinate value of the first recorded reference point in the image, and h5 is the height value of the last recorded reference point in the image.

[0057] When processing a large amount of image data for settlement analysis, this application can easily integrate such a formula into the automated data processing process. Since its calculation method is concise and clear and does not require complicated intermediate steps or additional parameter estimation, the computer program can quickly calculate each set of corresponding benchmark point height data, thereby efficiently generating a series of height difference values.

[0058] The formula for calculating the settlement based on scale conversion is: D = △h3*k, where D is the calculated settlement value.

[0059] This application uses a unified formula to calculate the settlement amount, so that the settlement observation data of different buildings or different parts of the same building have a unified measurement standard. When monitoring the settlement of multiple buildings or comparing and analyzing different areas of a building, a fair and accurate comparison can be made based on this standard. The settlement rate calculation formula in step S6 is:

[0060]

[0061] Where v is the settlement rate, D2 is the second observed settlement, D1 is the first observed settlement, t2 is the time of the second observation, and t1 is the time of the first observation. The calculated settlement rate v is compared with the safe settlement rate threshold. If the actual settlement rate is greater than the safe settlement rate threshold, it indicates that there is a safety hazard in the building. The foundation reinforcement technology is used to reinforce the soft foundation, improve the bearing capacity and stability of the foundation, and slow down or prevent the continued development of settlement.

[0062] This application compares the calculated settlement rate with the safe settlement rate threshold, providing a clear boundary for the safety assessment of the building. The safe settlement rate threshold is determined based on a combination of factors such as the type of building, design standards, and geological conditions. It represents the maximum safe settlement rate that the building can withstand.

[0063] Reference Figure 2 As shown, the settlement observation system based on aerial photography measurement includes: an aerial photography module, an image analysis module, a ratio conversion module, a settlement amount calculation module and a settlement rate analysis module;

[0064] The aerial photography module includes a drone unit and a camera unit, which are used to take aerial photos of buildings and obtain image data;

[0065] The image analysis module is used to pre-process the image and analyze the location of the building's reference point in the image;

[0066] The scale conversion module is used to establish the scale value between the image and the actual height;

[0067] The settlement calculation module is used to calculate the height difference and the settlement of the building based on the scale value;

[0068] The settlement rate analysis module is used to analyze the settlement rate and further adjust the buildings if there are safety hazards.

[0069] This application utilizes a combination of drones and camera units to collect building image data in an all-round, large-area, convenient and efficient manner. It is not restricted by terrain, has strong timeliness, and has high image resolution, which is conducive to subsequent analysis. Image interference can be removed through preprocessing to improve the accuracy of benchmark point extraction. At the same time, it realizes automated and standardized analysis processes, reduces errors, ensures data comparability, analyzes settlement rates to assess risks in real time, promptly warns of safety hazards, assists in the formulation of targeted adjustment measures, and supports the full life cycle management of buildings.

[0070] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention, and these changes and improvements fall within the scope of the present invention claimed.

Claims

1. The settlement observation method based on aerial photography is characterized by: The observation steps are: S1. Establish reference points on the building to be observed as reference data points, mark and organize the reference points, and establish the scale value of the image and the actual height; S2. Use a drone to take aerial photos of the building to be observed at a preset height to obtain aerial images; S3, uploading the acquired aerial image to the image analysis module, analyzing the image based on the image analysis module, preprocessing the image, extracting the reference points of the building to be observed in the image based on the SIFT algorithm, and calculating the height position of the reference points in the image; S4. In different time periods, use a drone to take aerial photos of the building to be observed again at the same height, obtain images of the building to be observed at the same position, analyze them again, obtain height position data of several reference points, and mark them; S5, comparing and calculating the first recorded reference point data with the last recorded reference point data in the two-dimensional image to obtain a height difference, and converting the difference to a specific value according to a scale, which is the settlement amount; S6. Analyze the settlement rate and obtain the threshold of the safe settlement rate. If the settlement rate is greater than the threshold, there is a safety hazard in the building, and further adjustment measures should be taken on the building.

2. The settlement observation method based on aerial photography measurement according to claim 1 is characterized in that: In step S1, the reference point position is selected as a reference point with a stable structure, not easily affected by external interference and a representative building, and is marked for observation by the drone; the scale is established by selecting a reference object with a known precise height on the ground at the bottom of the building, including a standard height benchmark and a measured vertical wall, using a drone to shoot the building and the reference object according to predetermined aerial photography parameters, and obtaining a clear aerial image containing the building and the reference object. Based on image processing, the pixel height value of the reference object in the image is identified and measured, and at the same time, combined with the actual height of the reference object, the scale value between the image and the actual height is calculated based on the proportional relationship; the calculation formula is: k=h1 / h2, where k is the calculated scale value, h1 is the actual height of the known reference object, and h2 is the height of its pixel measured in the image.

3. The settlement observation method based on aerial photography measurement according to claim 1 is characterized in that: In step S2, before the aerial photography operation, the flight route is planned. After the flight route is determined, the shooting parameters are adjusted to ensure that the entire building can be captured and clear image details can be obtained. The best aerial photography altitude is determined through multiple flight experiments. The image quality is optimized by turning on the camera's noise reduction function. The flight shooting is carried out to the predetermined altitude to shoot the reference points on the building. After the aerial photography mission is completed, the drone is controlled to land safely and the aerial image data captured is transmitted to the image analysis module.

4. The settlement observation method based on aerial photography measurement according to claim 1 is characterized in that: Image preprocessing in step S3 includes denoising and grayscale processing. Denoising uses the median filtering algorithm, and the median of the pixel grayscale values ​​within the area of ​​each pixel in the image is selected to replace the original grayscale value of the pixel to achieve the purpose of denoising. Grayscale is processed using the averaging method, and the pixel values ​​of the three channels R, G, and B of each pixel in the color image are added, and then the average value is taken as the grayscale value of the pixel. The processing formula is: Gray = (R+G+B) / 3, where R, G, and B are the pixel values ​​of the three channels of the pixel.

5. The settlement observation method based on aerial photography measurement according to claim 1 is characterized in that: The SIFT algorithm formula in step S3 is: Where (x, y) is the coordinate of the feature point of the reference point on the image, (x0, y0) is the coordinate of the principal point, f is the focal length of the camera, (Xs, Ys, Zs) is the coordinate position of the camera, (a1, b1, c1), (a2, b2, c2) and (a3, b3, c3) are the elements of the camera posture rotation matrix, (X, Y, Z) is the coordinate of the reference point in the set ground coordinate system associated with the actual position of the building, and the height position of the reference point in the image is determined by the above calculation.

6. The settlement observation method based on aerial photography measurement according to claim 1 is characterized in that: In step S4, the drone is kept at the same altitude during multiple shots, and aerial monitoring is performed every few months. When the predetermined time period is reached, the drone is controlled at the same altitude to conduct a comprehensive and detailed aerial photography operation of the building to be observed again along a pre-planned and optimized flight route, and multiple image data are obtained and marked and organized.

7. The settlement observation method based on aerial photography measurement according to claim 1 is characterized in that: The comparison calculation formula in step S5 is: △h3=h4-h5, where △h3 is the calculated difference value, h4 is the height coordinate value of the first recorded reference point in the image, and h5 is the height value of the last recorded reference point in the image.

8. The settlement observation method based on aerial photography measurement according to claim 7 is characterized in that: The formula for settlement calculated based on scale conversion is: D = △h3*k, where D is the calculated settlement value.

9. The settlement observation method based on aerial photography measurement according to claim 1, characterized in that: The sedimentation rate calculation formula in step S6 is: Where v is the settlement rate, D2 is the second observed settlement, D1 is the first observed settlement, t2 is the time of the second observation, and t1 is the time of the first observation. The calculated settlement rate v is compared with the safe settlement rate threshold. If the actual settlement rate is greater than the safe settlement rate threshold, it indicates that there is a safety hazard in the building. The foundation reinforcement technology is used to reinforce the soft foundation, improve the bearing capacity and stability of the foundation, and slow down or prevent the continued development of settlement.

10. The settlement observation system based on aerial photography measurement is characterized by: The observation system includes: aerial photography module, image analysis module, ratio conversion module, sedimentation calculation module and sedimentation rate analysis module; The aerial photography module includes a drone unit and a camera unit, which are used to take aerial photos of buildings and obtain image data; The image analysis module is used to pre-process the image and analyze the location of the building's reference point in the image; The scale conversion module is used to establish the scale value between the image and the actual height; The settlement calculation module is used to calculate the height difference and the settlement of the building based on the scale value; The settlement rate analysis module is used to analyze the settlement rate and further adjust the buildings if there are safety hazards.

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