Pipeline excavation slope safety evaluation method based on three-dimensional reconstruction

Abstract

The invention discloses a pipeline excavation side slope safety evaluation method based on three-dimensional reconstruction, and belongs to the field of side slope landslide safety protection, and the method comprises the following steps: S1, arranging an image scanning system in a pipeline excavation side slope area, and collecting a side slope image; s2, performing feature extraction and stereo matching on the acquired slope image; s3, performing three-dimensional reconstruction on the landslide falling objects on the side slope according to the extracted features and the stereo matching result; s4, according to a three-dimensional reconstruction result, identifying the type, size, number and position features of the landslide falling objects; and S5, analyzing and evaluating the excavation safety condition of the pipeline slope according to the feature information identified in the step S4, so that the real-time monitoring of the slope landslide can be realized, the change condition of the slope can be found in time, timely and accurate information can be provided for early warning and response, the stability state of the slope can be automatically judged, and an early warning signal can be sent out in time when an abnormality is found.

Description

Technical Field

[0001] The invention relates to the field of slope landslide safety protection, and in particular to a pipeline excavation slope safety evaluation method based on three-dimensional reconstruction. Background Art

[0002] Pipeline projects often pass through different geological environments, including soft soil layers, rock layers and mixed soil layers. Changes in these geological conditions will lead to large differences in slope stability, especially in soft soil and weathered rock layers, where the risk of landslides is higher. Natural factors such as rainfall, earthquakes, weathering and groundwater changes will have a significant impact on slope stability. In addition, the pipeline itself will also disturb the slope during the excavation and construction process, causing landslides. Any damage caused by landslides will have serious consequences, including economic losses, environmental pollution and threats to personal safety. Therefore, it is crucial to ensure slope stability. Currently, there is no relevant technology for safety evaluation of pipeline excavation slopes. Summary of the invention

[0003] In response to the above problems, the present invention provides a pipeline excavation slope safety assessment method based on three-dimensional reconstruction. By using three-dimensional reconstruction technology, real-time monitoring of the slope can be achieved, and changes in the slope can be discovered in time, providing timely and accurate information for early warning and response, thereby ensuring the safety of slope operations.

[0004] The technical solution of the present invention is:

[0005] A pipeline excavation slope safety assessment method based on three-dimensional reconstruction includes the following steps:

[0006] S1. Deploy an image scanning system in the pipeline excavation slope area to collect slope images;

[0007] S2, performing feature extraction and stereo matching on the collected slope images;

[0008] S3, based on the extracted features and stereo matching results, three-dimensional reconstruction of the landslide debris on the slope;

[0009] S4. Identify the type, size, quantity and location characteristics of landslide debris based on the 3D reconstruction results;

[0010] S5. Analyze and evaluate the safety of pipeline slope excavation based on the characteristic information identified in step S4.

[0011] In the step S1, the image scanning system is a plurality of laser scanners that fully cover the pipeline excavation slope area.

[0012] In step S1, the slope image is collected and accurately positioned and identified using a hand-eye calibration method, and the specific method is as follows:

[0013] 1) Define an arbitrary world coordinate system on the target to be measured, and convert from the world coordinate system to the scanning system coordinate system. The conversion formula is as follows:

[0014]

[0015] Among them, (Wx, Wy, Wz, 1) T is the homogeneous coordinates of the target point in the world coordinate system; (Cx, Cy, Cz, 1) T is the homogeneous coordinate of the target point in the camera coordinate system; E is the 3x3 orthogonal unit matrix; S is the 3x1 translation vector; 0 is the 3x1 zero vector;

[0016] 3) Convert from the scanning system coordinate system to the imaging plane coordinate system. The conversion formula is as follows:

[0017]

[0018] Among them, (X, Y) T is the homogeneous coordinate in the imaging plane coordinate system, and f is the focal length.

[0019] In step S2, the stereo matching formula is as follows:

[0020]

[0021] Census(x,y,z)=ming(Census l (x,y),Census r (xd,y))

[0022]

[0023] C(x,y,z)=αmin(T c ,Census(x,y,z))+(1-α)min(T g ,g(x,y,z))

[0024] S(p,z)=∑ r L r (p,z)

[0025] Where: I(p), I(q) are the grayscale values ​​of the image, I(p) is the average grayscale value of the pixels in the window, ξ is the limit of grayscale binarization, Census(x, y, z) is the color difference between the corresponding pixels in the left and right images, G(x, y, z) is the matching cost of (x, y) in the image, and the disparity value is z at this time, IL(x, y) is the grayscale value of the pixel in the left image, IR(x, y, z) is the grayscale value of the pixel with the same name in the right image, α is the weight factor, balancing the weight of the Census algorithm and the gradient, Tc, Tg are the cutoff values, and Lr (p,z) is the path cost of a certain path.

[0026] In step S5, based on the feature recognition result, the threat level of the pipeline excavation slope to personnel is determined, and after a potential threat is found, an early warning message is issued to intervene in the construction personnel.

[0027] The beneficial effects of the present invention are:

[0028] By capturing images with a laser scanner, there is no need for direct contact with the object being measured, thus avoiding the physical damage or impact that may be caused by traditional contact measurement; by calculating the parallax information of the pixels in the image, the three-dimensional information of the object being measured can be accurately obtained, including shape, size and position, thereby achieving high-precision monitoring; real-time monitoring of slope landslides can be achieved, and through continuous shooting and analysis of images, changes in the slope can be discovered in a timely manner, providing timely and accurate information for early warning and response, automatically judging the stability of the slope, and issuing early warning signals in a timely manner when abnormalities are found. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a flow chart of a pipeline excavation slope safety assessment method based on three-dimensional reconstruction described in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0031] Example:

[0032] like Figure 1 As shown, a pipeline excavation slope safety evaluation method based on three-dimensional reconstruction includes the following steps:

[0033] S1. Deploy an image scanning system in the pipeline excavation slope area to collect slope images;

[0034] Specifically, a laser scanning system is deployed in key areas of the pipeline excavation slope. The laser scanner is fixedly installed on a movable bracket. The position and angle of the equipment are adjusted so that they can clearly capture changes in the slope. This ensures that the system can cover areas where landslides and falling objects may occur. If full coverage is not possible, the system is added to ensure full coverage of the working area. First, the laser scanner is calibrated by hand and eye to ensure that the data it obtains can be accurately mapped to the coordinate system of the early warning system equipment, thereby achieving accurate target positioning and identification. Secondly, the slope is scanned with a laser scanner to obtain image information.

[0035] The specific method of hand-eye calibration is as follows:

[0036] 1) Define an arbitrary world coordinate system on the target to be measured, and convert from the world coordinate system to the scanning system coordinate system. The conversion formula is as follows:

[0037]

[0038] Among them, (Wx, Wy, Wz, 1) T is the homogeneous coordinates of the target point in the world coordinate system; (Cx, Cy, Cz, 1) T is the homogeneous coordinate of the target point in the camera coordinate system; E is the 3x3 orthogonal unit matrix; S is the 3x1 translation vector; 0 is the 3x1 zero vector;

[0039] 4) Convert from the scanning system coordinate system to the imaging plane coordinate system. The conversion formula is as follows:

[0040]

[0041] Among them, (X, Y) T is the homogeneous coordinate in the imaging plane coordinate system, and f is the focal length.

[0042] Due to the accuracy of the camera, the origin of the imaging plane coordinate system is generally deviated from the origin of the image coordinate system. If the coordinates of the origin of the imaging plane coordinate system in the image coordinate system are known to be (u0, v0), then the conversion relationship can be expressed as:

[0043]

[0044] Among them, M1 is the camera intrinsic parameter matrix; M2 is the camera extrinsic parameter matrix, which is determined by the orientation of the camera relative to the world coordinate system.

[0045] S2, performing feature extraction and stereo matching on the collected slope images;

[0046] The Census algorithm is used in matching. The Census algorithm formula is as follows:

[0047]

[0048] Among them, I(p), I(q) are the grayscale values ​​of the image, I(p) is the average grayscale value of the pixels in the window, and ξ is the limit of grayscale binarization.

[0049] The corresponding pixels of the left and right images have similar grayscale values, so the degree of match between them can be determined by comparing the Census transform codes of the pixels of the left and right images:

[0050] Census(x,y,z)=ming(Census l (x,y),Censusr (xd,y))

[0051] Among them, Census (x, y, z) is the color difference between corresponding pixels in the left and right images.

[0052] By using the gradient transformation operator, the similarity between images can be calculated more accurately. The formula is as follows:

[0053]

[0054] Where G(x, y, z) is the matching cost of (x, y) in the image, the disparity value is z, IL(x, y) is the grayscale value of the pixel in the left image, and IR(x, y, z) is the grayscale value of the pixel with the same name in the right image.

[0055] The Census transformation algorithm has excellent robustness and can effectively resist the grayscale changes caused by uneven illumination, while the gradient transformation can better preserve the details of the image edge. The two are combined and normalized using the matching cost. The formula is expressed as follows:

[0056] C(x,y,z)=αmin(T c ,Census(x,y,z))+(1-α)min(T g ,g(x,y,z))

[0057] Among them, α is the weight factor, balancing the weight of the Census algorithm and the gradient, and Tc and Tg are cutoff values.

[0058] Perform path aggregation on the matching cost of each pixel under different parallaxes to obtain the path value of each path, and then add up the cost values ​​of all possible matching points of the pixel in the left and right images to calculate the total matching cost. Total path cost value:

[0059] S(p,z)=∑ r L r (p,z)

[0060] Among them, L r (p,z) is the path cost of a certain path.

[0061] S3, based on the extracted features and stereo matching results, three-dimensional reconstruction of the landslide debris on the slope;

[0062] S4. Identify the type, size, quantity and location characteristics of landslide debris based on the 3D reconstruction results;

[0063] S5. Analyze and evaluate the safety of pipeline slope excavation based on the characteristic information identified in step S4.

[0064] Based on the identification results, determine whether the pipeline excavation slope poses a threat to personnel, determine whether the landslide debris poses a threat to the pipeline excavation slope, and determine the safe area on the slope. If workers enter an unsafe area, an early warning signal will be issued and the construction personnel will quickly leave the area. If potential threats are found, an early warning signal will be issued in time to remind the construction personnel to take corresponding measures.

[0065] The above-mentioned embodiments only express the specific implementation of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A pipeline excavation slope safety assessment method based on three-dimensional reconstruction, characterized in that: The steps include: S1. Deploy an image scanning system in the pipeline excavation slope area to collect slope images; S2, performing feature extraction and stereo matching on the collected slope images; S3, based on the extracted features and stereo matching results, three-dimensional reconstruction of the landslide debris on the slope; S4. Identify the type, size, quantity and location characteristics of landslide debris based on the 3D reconstruction results; S5. Analyze and evaluate the safety of pipeline slope excavation based on the characteristic information identified in step S4.

2. The pipeline excavation slope safety assessment method based on three-dimensional reconstruction according to claim 1 is characterized in that: In the step S1, the image scanning system is a plurality of laser scanners that fully cover the pipeline excavation slope area.

3. The pipeline excavation slope safety assessment method based on three-dimensional reconstruction according to claim 1 is characterized in that: In step S1, the slope image is collected and accurately positioned and identified using a hand-eye calibration method, and the specific method is as follows: 1) Define an arbitrary world coordinate system on the target to be measured, and convert from the world coordinate system to the scanning system coordinate system. The conversion formula is as follows: Among them, (Wx, Wy, Wz, 1) T is the homogeneous coordinates of the target point in the world coordinate system; (Cx, Cy, Cz, 1) T is the homogeneous coordinate of the target point in the camera coordinate system; E is the 3x3 orthogonal unit matrix; S is the 3x1 translation vector; 0 is the 3x1 zero vector; 2) Convert from the scanning system coordinate system to the imaging plane coordinate system. The conversion formula is as follows: Among them, (X, Y) T is the homogeneous coordinate in the imaging plane coordinate system, and f is the focal length.

4. The pipeline excavation slope safety assessment method based on three-dimensional reconstruction according to claim 1 is characterized in that: In step S2, the stereo matching formula is as follows: Census(x,y,z)=ming(Census l (x,y),Census r (xd,y)) C(x,y,z)=αmin(T c ,Census(x,y,z))+(1-α)min(T g ,g(x,y,z)) S(p,z)=∑ r L r (p,z) Where: I(p), I(q) are the grayscale values ​​of the image, I(p) is the average grayscale value of the pixels in the window, ξ is the limit of grayscale binarization, Census(x, y, z) is the color difference between the corresponding pixels in the left and right images, G(x, y, z) is the matching cost of (x, y) in the image, and the disparity value is z at this time, IL(x, y) is the grayscale value of the pixel in the left image, IR(x, y, z) is the grayscale value of the pixel with the same name in the right image, α is the weight factor, balancing the weight of the Census algorithm and the gradient, Tc, Tg are the cutoff values, and L r (p,z) is the path cost of a certain path.

5. The pipeline excavation slope safety assessment method based on three-dimensional reconstruction according to claim 1 is characterized in that: In step S5, based on the feature recognition result, the threat level of the pipeline excavation slope to personnel is determined, and after a potential threat is found, an early warning message is issued to intervene in the construction personnel.

Images