A highway geological disaster monitoring method based on remote sensing and BIM

Abstract

The present invention belongs to the field of geological disaster monitoring, and relates to a highway geological disaster monitoring method based on remote sensing and BIM. The present invention obtains the geological disaster influence coefficient of the road surface to be monitored in each region by analyzing the crack influence coefficient, deformation influence coefficient, settlement influence coefficient and obstacle influence coefficient of the road surface to be monitored in each region, and obtains the geological disaster influence coefficient on the slope corresponding to the road to be monitored in each region by analyzing the displacement offset coefficient, displacement offset change rate and center of gravity position offset coefficient of the characteristic points on the slope corresponding to the road to be monitored in each region. The present invention realizes continuous and real-time monitoring of the highway and its surrounding areas by using remote sensing and BIM technology, provides real-time and accurate data support for monitoring and early warning of geological disasters, and does not require manual intervention, thereby reducing the overall workload and cost, and is objective, not affected by human factors, and improves the reliability of monitoring results.

Description

Technical Field

[0001] The invention belongs to the field of geological disaster monitoring and relates to a highway geological disaster monitoring method based on remote sensing and BIM. Background Art

[0002] With the continuous development and extension of highway networks, the risk of highway geological disasters is gradually increasing. Geological disasters such as landslides, mudslides, and earthquakes will not only cause huge economic losses, but also endanger people's lives. Therefore, the development of efficient and accurate highway geological disaster monitoring methods is crucial to ensure highway safety.

[0003] The traditional highway geological disaster monitoring method has the following problems: First, the traditional highway geological disaster monitoring method relies on manual monitoring to obtain highway geological disaster data. The data obtained is subjective and may lead to low reliability of monitoring results.

[0004] Second, traditional highway geological disaster monitoring methods usually only analyze cracks and deformations on the highway surface, and cannot perform real-time analysis of obstacles that slide on the road surface, resulting in relevant personnel being unable to deal with obstacles on the road surface in a timely manner, thereby increasing the risk of highway safety hazards.

[0005] Third, the traditional highway geological disaster monitoring method does not analyze the slopes beside the highway, and cannot predict the falling of trees, rocks, etc. on the slopes, which may lead to the failure to timely discover and take measures when geological disasters occur, increasing the risk of disaster losses and affecting the accuracy of monitoring results. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a highway geological disaster monitoring method based on remote sensing and BIM is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a highway geological disaster monitoring method based on remote sensing and BIM, comprising the following steps: Step 1, using remote sensing technology to monitor the highway to be monitored, dividing the highway to be monitored into regions according to preset lengths, and obtaining BIM model images of the highway to be monitored in each region through BIM technology.

[0008] Step 2: Based on the acquired BIM model images of the roads to be monitored in each area, the defect data and obstacle data of the road surface of each area to be monitored are obtained, thereby analyzing the geological disaster impact coefficient of the road surface of each area to be monitored and issuing an early warning.

[0009] Step 3: Obtain the road surface defect data of the roads to be monitored in each area in each historical monitoring, analyze the change degree of the road surface defect impact of the roads to be monitored in each area, and issue an early warning.

[0010] Step 4: Obtain the BIM model image of the slope corresponding to the roads to be monitored in each area, obtain the coordinates and center of gravity position of each feature point on the slope corresponding to the roads to be monitored in each area, and analyze the displacement offset coefficient, displacement offset change rate and center of gravity position offset coefficient of the feature points on the slope corresponding to the roads to be monitored in each area.

[0011] Step 5: Based on the displacement offset coefficient, displacement offset change rate and center of gravity position offset coefficient of the characteristic points on the slopes corresponding to the monitored roads in each area, the geological disaster impact coefficient on the slopes corresponding to the monitored roads in each area is obtained, and an early warning is issued.

[0012] On the basis of the above embodiment, the geological disaster impact coefficient of the road pavement to be monitored in each area is analyzed as follows: the crack area, contour line length, longest width of the road, shortest width of the road, area and deepest depth of the settlement area in the defect data of the road pavement to be monitored in each area are extracted, and the crack impact coefficient of the road pavement to be monitored in each area is obtained according to the crack area of ​​the road pavement to be monitored in each area, which is recorded as β a , a represents the number of the ath region, a=1,2,...,b, according to the contour line length, the longest width and the shortest width of the road surface to be monitored in each region, the deformation influence coefficient of the road surface to be monitored in each region is obtained, which is recorded as δ a According to the area and the deepest depth of the settlement area of ​​the road surface to be monitored in each area, the settlement influence coefficient of the road surface to be monitored in each area is obtained, which is recorded as ε a According to the obstacle data of the road surface to be monitored in each area, the obstacle influence coefficient of the road surface to be monitored in each area is obtained, which is recorded as φ a .

[0013] By formula Obtain the geological disaster impact coefficient of the road surface to be monitored in each area

[0014] The geological disaster impact coefficient of the road surface to be monitored in each area is compared with the preset geological disaster impact reference coefficient of the road surface to be monitored. If the geological disaster impact coefficient of the road surface to be monitored in a certain area is greater than the preset geological disaster impact reference coefficient of the road surface to be monitored, the corresponding number of the road to be monitored in the area will be sent to relevant personnel and an early warning will be issued.

[0015] On the basis of the above-mentioned embodiment, the deformation influence coefficient of the road surface to be monitored in each area is analyzed as follows: the contour line length, the longest width of the road and the shortest width of the road to be monitored in each area are respectively denoted as x a , and

[0016] By formula Obtain the deformation influence coefficient δ of the road surface to be monitored in each area a , x0 represents the preset standard contour line length of the road surface to be monitored, e represents a natural constant, and x′0 represents the preset standard width of the road surface to be monitored.

[0017] On the basis of the above-mentioned embodiment, the settlement influence coefficient of the road surface to be monitored in each area is analyzed as follows: the area and the deepest depth of the settlement area of ​​the road surface to be monitored in each area are respectively denoted as S a and H a , extract the area of ​​the road surface to be monitored in each region from the database and record it as S′ a .

[0018] By formula Obtain the settlement influence coefficient ε of the road surface to be monitored in each area a , H0 represents the preset allowable settlement depth of the road surface to be monitored.

[0019] Based on the above embodiment, the obstacle influence coefficient of the road surface to be monitored in each area is analyzed as follows: the number of obstacles and the total volume corresponding to the obstacles in the obstacle data of the road surface to be monitored in each area are extracted and recorded as d a and By formula Obtain the obstacle influence coefficient φ of the road surface to be monitored in each area a , d0 represents the preset allowed number of obstacles on the road surface to be monitored, It is expressed as the preset allowable volume of the road obstacle to be monitored.

[0020] On the basis of the above embodiments, the degree of change of the defect impact of the road surface of each area to be monitored is specifically analyzed as follows: based on the BIM model images of the roads to be monitored in each area in each historical monitoring, the defect data of the road surface of each area to be monitored in each historical monitoring is obtained.

[0021] The crack area of ​​the road surface of each area to be monitored in each historical monitoring is recorded as y represents the number of the yth historical monitoring, y = 1, 2, ..., z, and the crack area of ​​the road surface to be monitored in each area is recorded as

[0022] By formula Get the crack defect influence variation degree ζ of the road surface to be monitored in each area a , It is represented by the preset reference change value of crack area of ​​the road surface to be monitored. It is represented by the crack area of ​​the road surface of the monitored highway in the ath area in the y-1th historical monitoring. It is expressed as the crack area of ​​the road surface of the monitored highway in the ath region in the zth historical monitoring. Similarly, the influence variation of deformation defects and settlement defects on the road surface of each region can be obtained, which are recorded as ψ a and a .

[0023] By formula γ a =ζ a *θ1+ψ a *θ2+ξ a *θ3 obtains the influence variation of defects of the road surface to be monitored in each area γ a , θ1, θ2 and θ3 respectively represent the weights of the preset crack defect influence variation degree, deformation defect influence variation degree and settlement defect influence variation degree of the highway pavement to be monitored.

[0024] The defect impact variation degree of the road surface to be monitored in each area is compared with the preset reference variation degree of the defect impact of the road surface to be monitored. If the defect impact variation degree of the road surface to be monitored in a certain area is greater than the preset reference variation degree of the defect impact of the road surface to be monitored, the number corresponding to the road to be monitored in this area will be sent to relevant personnel and an early warning will be issued.

[0025] On the basis of the above embodiments, the displacement offset influence coefficient of the characteristic points on the slopes corresponding to the roads to be monitored in each area is analyzed as follows: through the BIM model images of the roads to be monitored in each area, the BIM model images of the slopes corresponding to the roads to be monitored in each area are obtained, and a two-dimensional coordinate system is established with any point on the slopes corresponding to the roads to be monitored in each area, and the coordinates of each characteristic point on the slopes corresponding to the roads to be monitored in each area are obtained.

[0026] Extract the BIM model image of the slope corresponding to the most recent road to be monitored in each region from the database, obtain the coordinates of each feature point on the slope corresponding to the most recent road to be monitored in each region, compare the coordinates of each feature point on the slope corresponding to the most recent road to be monitored in each region with the coordinates of each feature point on the slope corresponding to the most recent road to be monitored in each region, and obtain the displacement offset distance of each feature point on the slope corresponding to the road to be monitored in each region, which is recorded as o represents the number of the o-th feature point in history, o=1,2,...,p.

[0027] By formula Get the displacement influence coefficient η of the characteristic points on the slope corresponding to the monitored highway in each area a , p represents the number of feature points, and x′0 represents the safe displacement offset distance of the feature points on the slope corresponding to the preset road to be monitored.

[0028] On the basis of the above embodiment, the displacement offset change rate of the characteristic points on the slopes corresponding to the roads to be monitored in each region is analyzed as follows: the BIM model images of the slopes corresponding to the roads to be monitored in each region in each historical monitoring are extracted from the database, and the displacement offset distances of the characteristic points on the slopes corresponding to the roads to be monitored in each region in each historical monitoring are obtained, which are recorded as

[0029] By formula Get the displacement change rate of the characteristic points on the slope corresponding to the monitored highway in each area a , It is represented by the displacement distance of each feature point on the slope corresponding to the road to be monitored in the ath area in the y-1th historical monitoring. It is represented by the displacement distance of each feature point on the slope corresponding to the road to be monitored in the ath area in the zth historical monitoring. It is represented by the displacement offset reference change value of the characteristic point on the slope corresponding to the preset road to be monitored.

[0030] On the basis of the above embodiments, the influence coefficient of the center of gravity position offset of the characteristic points on the slopes corresponding to the roads to be monitored in each area is analyzed as follows: the BIM model images of the slopes corresponding to the roads to be monitored in each area are obtained, the center of gravity position and the critical drop center of gravity position of each characteristic point on the slopes corresponding to the roads to be monitored in each area are obtained, the center of gravity position of each characteristic point on the slopes corresponding to the roads to be monitored in each area are compared with the critical drop center of gravity position, and the influence coefficient κa of the center of gravity position offset of foreign objects on the slopes corresponding to the roads to be monitored in each area is obtained.

[0031] On the basis of the above-mentioned embodiment, the influence coefficient of geological disasters on the slopes corresponding to the roads to be monitored in each area is analyzed as follows: Obtain the geological disaster impact coefficient λ on the slope corresponding to the monitored highway in each area a .

[0032] The geological disaster impact coefficient on the slope corresponding to the roads to be monitored in each area is compared with the preset reference coefficient of geological disaster impact on the slope corresponding to the roads to be monitored. If the geological disaster impact coefficient on the slope corresponding to the roads to be monitored in a certain area is greater than the preset reference coefficient of geological disaster impact on the slope corresponding to the roads to be monitored, the number corresponding to the roads to be monitored in this area will be sent to relevant personnel and an early warning will be issued.

[0033] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention realizes continuous and real-time monitoring of highways and their surrounding areas by utilizing remote sensing and BIM technology, captures subtle changes in geological disasters, and accurately reflects these change information in the three-dimensional model, providing real-time and accurate data support for the monitoring and early warning of geological disasters. At the same time, no human intervention is required, which reduces the overall workload and cost. In addition, the present invention is objective, not affected by human factors, and improves the reliability of monitoring results.

[0034] 2. The present invention obtains the defect conditions of the road surface and the sliding conditions of obstacles in each area to be monitored by real-time analysis of the defect data and the sliding data of obstacles on the road surface to be monitored in each area, and sends early warning reminders to relevant personnel in time, thereby reducing the risk of highway safety hazards.

[0035] 3. The present invention analyzes the displacement offset coefficient, displacement offset change rate and center of gravity position offset coefficient of the characteristic points on the slopes corresponding to the roads to be monitored in each area, so as to predict the falling of trees, falling rocks, etc. on the slopes, and then timely discover and take measures when geological disasters occur, thereby reducing the risk of disaster losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0037] Figure 1 The present invention is a schematic flow chart of the steps for implementing the method. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] See also Figure 1 As shown, the present invention provides a highway geological disaster monitoring method based on remote sensing and BIM, the method comprising: step one, using remote sensing technology to monitor the highway to be monitored, dividing the highway to be monitored into regions according to preset lengths, and obtaining a BIM model image of the highway to be monitored in each region through BIM technology.

[0040] It should be noted that the present invention realizes continuous and real-time monitoring of the highway and its surrounding areas by utilizing remote sensing and BIM technology, captures subtle changes in geological disasters, and accurately reflects these change information in the three-dimensional model, providing real-time and accurate data support for the monitoring and early warning of geological disasters. At the same time, no human intervention is required, thus reducing the overall workload and cost. In addition, the present invention is objective, not affected by human factors, and improves the reliability of the monitoring results.

[0041] Step 2: Based on the acquired BIM model images of the roads to be monitored in each area, the defect data and obstacle data of the road surface of each area to be monitored are obtained, thereby analyzing the geological disaster impact coefficient of the road surface of each area to be monitored and issuing an early warning.

[0042] Specifically, the geological disaster impact coefficient of the road pavement to be monitored in each area is analyzed as follows: the crack area, contour line length, longest width of the road, shortest width of the road, area and deepest depth of the settlement area in the defect data of the road pavement to be monitored in each area are extracted, and the crack impact coefficient of the road pavement to be monitored in each area is obtained according to the crack area of ​​the road pavement to be monitored in each area, which is recorded as β a , a represents the number of the ath region, a=1,2,...,b, according to the contour line length, the longest width and the shortest width of the road surface to be monitored in each region, the deformation influence coefficient of the road surface to be monitored in each region is obtained, which is recorded as δ a According to the area and the deepest depth of the settlement area of ​​the road surface to be monitored in each area, the settlement influence coefficient of the road surface to be monitored in each area is obtained, which is recorded as ε a According to the obstacle data of the road surface to be monitored in each area, the obstacle influence coefficient of the road surface to be monitored in each area is obtained, which is recorded as φ a .

[0043] It should be noted that: the method for obtaining the crack area of ​​the road surface to be monitored in each region is as follows: based on the acquired BIM model images of the roads to be monitored in each region, a grayscale image of the road surface to be monitored in each region is obtained; by extracting each pixel point from the grayscale image of the road surface to be monitored in each region, the grayscale value of each pixel point in the grayscale image of the road surface to be monitored in each region is obtained; if the grayscale value of a pixel point in the grayscale image of the road surface to be monitored in a certain region is within the grayscale value range of the pixel point in the preset crack grayscale image, the pixel point is marked as a crack edge point, the position of each crack edge point is counted, each crack edge point is connected with the crack edge point at its adjacent position to form each largest closed image contour, each closed image contour is recorded as each crack, and the crack area of ​​the road surface to be monitored in each region is obtained according to the number of pixel points corresponding to each crack in the road surface to be monitored in each region.

[0044] It should be noted that the contour line length of the road surface to be monitored in each area is obtained by obtaining the BIM model images of the roads to be monitored in each area, and accumulating them to obtain the contour line length of the road surface to be monitored in each area.

[0045] It should be noted that the longest width and the shortest width of the road surface to be monitored in each area are obtained by setting up monitoring points on both sides of the contour lines of the road surface to be monitored in each area, obtaining the length between each monitoring point on one side of the contour line and the corresponding monitoring point on the other side of the contour line, and recording it as the width of each road on the road surface to be monitored in each area, from which the longest width and the shortest width of the road surface to be monitored in each area are screened out.

[0046] It should be noted that the area and the deepest depth of the settlement area of ​​the road surface to be monitored in each area are obtained in the following manner: based on the acquired BIM model images of the roads to be monitored in each area, a grayscale image of the road surface to be monitored in each area is obtained; by extracting each pixel point from the grayscale image of the road surface to be monitored in each area, the grayscale value of each pixel point in the grayscale image of the road surface to be monitored in each area is obtained; if the grayscale value of a pixel point in the grayscale image of the road surface to be monitored in a certain area is within the grayscale value range of the pixel point in the grayscale image of the settlement area, the pixel point is set as The points are marked as edge points of the subsidence areas, and the positions of the edge points of the subsidence areas are counted. The edge points of the subsidence areas are connected with the edge points of the subsidence areas at adjacent positions to form the largest closed image contours. The closed image contours are recorded as subsidence areas, and the subsidence area of ​​the road pavement to be monitored in each area is obtained according to the number of pixel points corresponding to each subsidence area of ​​the road pavement to be monitored in each area. The monitoring points are arranged in each subsidence area, and the height of each monitoring point from the horizontal ground is obtained. The height is screened to obtain the deepest depth of the subsidence area of ​​the road pavement to be monitored in each area.

[0047] By formula Obtain the geological disaster impact coefficient of the road surface to be monitored in each area

[0048] The geological disaster impact coefficient of the road surface to be monitored in each area is compared with the preset geological disaster impact reference coefficient of the road surface to be monitored. If the geological disaster impact coefficient of the road surface to be monitored in a certain area is greater than the preset geological disaster impact reference coefficient of the road surface to be monitored, the corresponding number of the road to be monitored in the area will be sent to relevant personnel and an early warning will be issued.

[0049] It should be noted that the crack influence coefficient of the road surface to be monitored in each area is obtained as follows: Based on the BIM model image of the road to be monitored in each area, the grayscale image of the road surface to be monitored in each area is obtained, and then the total crack area of ​​the road surface to be monitored in each area is obtained, which is recorded as a represents the number of the a-th area, a=1, 2, ..., b.

[0050] The area of ​​the road surface to be monitored in each region is extracted from the database and recorded as S a , through the formula Get the crack influence coefficient β of the road surface to be monitored in each area a .

[0051] It should be noted that the present invention obtains the defect conditions of the road surfaces to be monitored and the sliding conditions of obstacles in each area by performing real-time analysis on the defect data and sliding obstacle data of the road surfaces to be monitored in each area, and sends early warning reminders to relevant personnel in a timely manner, thereby reducing the risk of highway safety hazards.

[0052] The deformation influence coefficient of the road surface to be monitored in each area is analyzed as follows: the contour line length, the longest width of the road and the shortest width of the road surface to be monitored in each area are respectively denoted as x a , and

[0053] By formula Obtain the deformation influence coefficient δ of the road surface to be monitored in each area a , x0 represents the preset standard contour line length of the road surface to be monitored, e represents a natural constant, and x′0 represents the preset standard width of the road surface to be monitored.

[0054] The settlement influence coefficient of the road surface to be monitored in each area is analyzed as follows: The area and the deepest depth of the settlement area of ​​the road surface to be monitored in each area are respectively denoted as S a and H a , extract the area of ​​the road surface to be monitored in each region from the database and record it as S′ a .

[0055] By formula Obtain the settlement influence coefficient ε of the road surface to be monitored in each area a , H0 represents the preset allowable settlement depth of the road surface to be monitored.

[0056] The obstacle influence coefficient of the road surface to be monitored in each area is analyzed as follows: the number of obstacles and the total volume corresponding to the obstacles in the obstacle data of the road surface to be monitored in each area are extracted and recorded as d a and By formula Obtain the obstacle influence coefficient φ of the road surface to be monitored in each area a , d0 represents the preset allowed number of obstacles on the road surface to be monitored, It is expressed as the preset allowable volume of the road obstacle to be monitored.

[0057] Step 3: Obtain the road surface defect data of the roads to be monitored in each area in each historical monitoring, analyze the change degree of the road surface defect impact of the roads to be monitored in each area, and issue an early warning.

[0058] Specifically, the defect impact variation of the road surface of each area to be monitored is analyzed as follows: based on the acquired BIM model images of each area to be monitored in each historical monitoring, the defect data of the road surface of each area to be monitored in each historical monitoring is obtained.

[0059] The crack area of ​​the road surface of each area to be monitored in each historical monitoring is recorded as y represents the number of the yth historical monitoring, y = 1, 2, ..., z, and the crack area of ​​the road surface to be monitored in each area is recorded as

[0060] By formula Get the crack defect influence variation degree ζ of the road surface to be monitored in each area a , It is represented by the preset reference change value of crack area of ​​the road surface to be monitored. It is represented by the crack area of ​​the road surface of the monitored highway in the ath area in the y-1th historical monitoring. It is expressed as the crack area of ​​the road surface of the monitored highway in the ath region in the zth historical monitoring. Similarly, the influence variation of deformation defects and settlement defects on the road surface of each region can be obtained, which are recorded as ψ a and a .

[0061] By formula γ a =ζ a *θ1+ψ a *θ2+ξ a *θ3 obtains the influence variation of defects of the road surface to be monitored in each area γ a , θ1, θ2 and θ3 respectively represent the weights of the preset crack defect influence variation degree, deformation defect influence variation degree and settlement defect influence variation degree of the highway pavement to be monitored.

[0062] The defect impact variation degree of the road surface to be monitored in each area is compared with the preset reference variation degree of the defect impact of the road surface to be monitored. If the defect impact variation degree of the road surface to be monitored in a certain area is greater than the preset reference variation degree of the defect impact of the road surface to be monitored, the number corresponding to the road to be monitored in this area will be sent to relevant personnel and an early warning will be issued.

[0063] Step 4: Obtain the BIM model image of the slope corresponding to the roads to be monitored in each area, obtain the coordinates and center of gravity position of each feature point on the slope corresponding to the roads to be monitored in each area, and analyze the displacement offset coefficient, displacement offset change rate and center of gravity position offset coefficient of the feature points on the slope corresponding to the roads to be monitored in each area.

[0064] It should be noted that each feature point may be a tree, fallen rock, etc. on the slope corresponding to the road to be monitored, and the center point of the tree, fallen rock, etc. on the slope corresponding to the road to be monitored is used as the coordinate of each feature point.

[0065] The displacement offset influence coefficient of the characteristic points on the slopes corresponding to the monitored roads in each area is analyzed as follows: the BIM model images of the slopes corresponding to the monitored roads in each area are obtained through the BIM model images of the monitored roads in each area, and a two-dimensional coordinate system is established with any point on the slopes corresponding to the monitored roads in each area to obtain the coordinates of each characteristic point on the slopes corresponding to the monitored roads in each area.

[0066] Extract the BIM model image of the slope corresponding to the most recent road to be monitored in each region from the database, obtain the coordinates of each feature point on the slope corresponding to the most recent road to be monitored in each region, compare the coordinates of each feature point on the slope corresponding to the most recent road to be monitored in each region with the coordinates of each feature point on the slope corresponding to the most recent road to be monitored in each region, and obtain the displacement offset distance of each feature point on the slope corresponding to the road to be monitored in each region, which is recorded as o represents the number of the o-th feature point in history, o=1,2,...,p.

[0067] By formula Get the displacement influence coefficient η of the characteristic points on the slope corresponding to the monitored highway in each area a , p represents the number of feature points, and x′0 represents the safe displacement offset distance of the feature points on the slope corresponding to the preset road to be monitored.

[0068] The displacement change rate of the characteristic points on the slopes corresponding to the monitored roads in each region is analyzed as follows: the BIM model images of the slopes corresponding to the monitored roads in each region in each historical monitoring are extracted from the database, and the displacement distance of each characteristic point on the slopes corresponding to the monitored roads in each region in each historical monitoring is obtained, which is recorded as

[0069] By formula Get the displacement change rate of the characteristic points on the slope corresponding to the monitored highway in each area a , It is represented by the displacement distance of each feature point on the slope corresponding to the road to be monitored in the ath area in the y-1th historical monitoring. It is represented by the displacement distance of each feature point on the slope corresponding to the road to be monitored in the ath area in the zth historical monitoring. It is represented by the displacement offset reference change value of the characteristic point on the slope corresponding to the preset road to be monitored.

[0070] The influence coefficient of the center of gravity position offset of the characteristic points on the slopes corresponding to the monitored roads in each area is analyzed as follows: the BIM model images of the slopes corresponding to the monitored roads in each area are obtained, the center of gravity positions and critical drop center of gravity positions of the characteristic points on the slopes corresponding to the monitored roads in each area are obtained, the center of gravity positions of the characteristic points on the slopes corresponding to the monitored roads in each area are compared with the critical drop center of gravity positions, and the influence coefficient κa of the center of gravity position offset of the foreign objects on the slopes corresponding to the monitored roads in each area is obtained.

[0071] Step 5: Based on the displacement offset coefficient, displacement offset change rate and center of gravity position offset coefficient of the characteristic points on the slopes corresponding to the monitored roads in each area, the geological disaster impact coefficient on the slopes corresponding to the monitored roads in each area is obtained, and an early warning is issued.

[0072] Specifically, the influence coefficient of geological disasters on the slopes of the roads to be monitored in each area is analyzed as follows: Obtain the geological disaster impact coefficient λ on the slope corresponding to the monitored highway in each area a .

[0073] The geological disaster impact coefficient on the slope corresponding to the roads to be monitored in each area is compared with the preset reference coefficient of geological disaster impact on the slope corresponding to the roads to be monitored. If the geological disaster impact coefficient on the slope corresponding to the roads to be monitored in a certain area is greater than the preset reference coefficient of geological disaster impact on the slope corresponding to the roads to be monitored, the number corresponding to the roads to be monitored in this area will be sent to relevant personnel and an early warning will be issued.

[0074] It should be noted that the present invention can predict the falling of trees, rocks, etc. on the slopes by analyzing the displacement offset coefficient, displacement offset change rate and center of gravity position offset coefficient of the characteristic points on the slopes corresponding to the roads to be monitored in each area, so as to timely discover and take measures when geological disasters occur, thereby reducing the risk of disaster losses.

[0075] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A highway geological disaster monitoring method based on remote sensing and BIM, characterized in that: The steps include: Step 1: Use remote sensing technology to monitor the road to be monitored, divide the road to be monitored into various areas according to preset lengths, and obtain the BIM model image of the road to be monitored in each area through BIM technology; Step 2: Based on the acquired BIM model images of the roads to be monitored in each region, the defect data and obstacle data of the road surface to be monitored in each region are obtained, thereby analyzing the geological disaster impact coefficient of the road surface to be monitored in each region and issuing an early warning; Step 3: Analyze the impact variation of defects on the road surface to be monitored in each area; The specific analysis is as follows: Obtain the road surface defect data of the highway to be monitored in each area in each historical monitoring according to the BIM model images of the highway to be monitored in each area in each historical monitoring; The crack area of ​​the road surface of each area to be monitored in each historical monitoring is recorded as , Indicates The number of the historical monitoring. , the crack area of ​​the road surface to be monitored in each area is recorded as ; Then the influence of crack defects on the road surface to be monitored in each area is analyzed and the variation degree is obtained. Similarly, the influence variation of deformation defect and settlement defect on the road surface to be monitored in each area can be obtained, which are recorded as and ; By formula Obtain the influence variation of the defects of the road surface to be monitored in each area , , and They are respectively represented as the weights of the preset crack defect influence variation degree, deformation defect influence variation degree and settlement defect influence variation degree of the road pavement to be monitored; The defect impact variation degree of the road surface to be monitored in each area is compared with the preset reference variation degree of the defect impact of the road surface to be monitored. If the defect impact variation degree of the road surface to be monitored in a certain area is greater than the preset reference variation degree of the defect impact of the road surface to be monitored, the number corresponding to the road to be monitored in the area is sent to relevant personnel, and an early warning is issued; Step 4: Obtain the BIM model image of the slope corresponding to the highway to be monitored in each area, obtain the coordinates and center of gravity position of each feature point on the slope corresponding to the highway to be monitored in each area, and analyze the displacement offset coefficient, displacement offset change rate and center of gravity position offset coefficient of the feature point on the slope corresponding to the highway to be monitored in each area; Step 5: Based on the displacement offset coefficient, displacement offset change rate and center of gravity position offset coefficient of the characteristic points on the slopes corresponding to the monitored roads in each area, the geological disaster impact coefficient on the slopes corresponding to the monitored roads in each area is obtained, and an early warning is issued.

2. The highway geological disaster monitoring method based on remote sensing and BIM according to claim 1 is characterized in that: The analysis of the geological disaster impact coefficient of the road surface to be monitored in each area is as follows: The crack area, contour line length, longest width of the road, shortest width of the road, area and deepest depth of the settlement area are extracted from the defect data of the road pavement to be monitored in each area. According to the crack area of ​​the road pavement to be monitored in each area, the crack influence coefficient of the road pavement to be monitored in each area is obtained, which is recorded as , Indicates The number of the region, According to the contour line length, the longest width and the shortest width of the road surface to be monitored in each area, the deformation influence coefficient of the road surface to be monitored in each area is obtained and recorded as According to the area and the deepest depth of the settlement area of ​​the road surface to be monitored in each area, the settlement influence coefficient of the road surface to be monitored in each area is obtained and recorded as According to the obstacle data of the road surface to be monitored in each area, the obstacle influence coefficient of the road surface to be monitored in each area is obtained and recorded as ; By formula Obtain the geological disaster impact coefficient of the road surface to be monitored in each area ; The geological disaster impact coefficient of the road surface to be monitored in each area is compared with the preset geological disaster impact reference coefficient of the road surface to be monitored. If the geological disaster impact coefficient of the road surface to be monitored in a certain area is greater than the preset geological disaster impact reference coefficient of the road surface to be monitored, the corresponding number of the road to be monitored in the area will be sent to relevant personnel and an early warning will be issued.

3. The highway geological disaster monitoring method based on remote sensing and BIM according to claim 2 is characterized in that: The deformation influence coefficients of the road surfaces to be monitored in each area are analyzed as follows: The contour length of the road surface to be monitored in each area, the longest width of the road, and the shortest width of the road are recorded as , and ; By formula Obtain the deformation influence coefficient of the road surface to be monitored in each area , It is represented by the preset standard contour length of the road surface to be monitored. Expressed as a natural constant, It represents the preset standard width of the road surface to be monitored.

4. The method for monitoring highway geological disasters based on remote sensing and BIM according to claim 2, characterized in that: The settlement influence coefficients of the road surfaces to be monitored in each area are analyzed as follows: The area and the maximum depth of the subsidence area of ​​the road surface to be monitored in each area are recorded as and , extract the area of ​​the road surface to be monitored in each region from the database and record it as ; By formula Obtain the settlement influence coefficient of the road surface to be monitored in each area , It is expressed as the preset allowable settlement depth of the road surface to be monitored.

5. The highway geological disaster monitoring method based on remote sensing and BIM according to claim 2 is characterized in that: The obstacle influence coefficients of the road surfaces to be monitored in each area are analyzed as follows: The number of obstacles and the total volume of obstacles in the obstacle data of the road surface to be monitored in each area are extracted and recorded as and , through the formula Obtain the obstacle influence coefficient of the road surface to be monitored in each area , It is expressed as the preset allowed number of obstacles on the road surface to be monitored. It is expressed as the preset allowable volume of the road obstacle to be monitored.

6. The method for monitoring highway geological disasters based on remote sensing and BIM according to claim 1, characterized in that: The calculation formula for the influence variation of crack defects on the road pavement to be monitored in each area is: , It is represented by the preset reference change value of crack area of ​​the road surface to be monitored. Expressed as The roads to be monitored in the area are The crack area of ​​the road surface in the historical monitoring, Expressed as The roads to be monitored in the area are The crack area of ​​the pavement during the historical monitoring.

7. The highway geological disaster monitoring method based on remote sensing and BIM according to claim 1 is characterized in that: The displacement influence coefficient of the characteristic points on the slopes corresponding to the roads to be monitored in each area is analyzed as follows: Through the BIM model images of the roads to be monitored in each area, the BIM model images of the slopes corresponding to the roads to be monitored in each area are obtained, and a two-dimensional coordinate system is established with any point on the slopes corresponding to the roads to be monitored in each area, so as to obtain the coordinates of each characteristic point on the slopes corresponding to the roads to be monitored in each area; Extract the BIM model image of the slope corresponding to the most recent road to be monitored in each region from the database, obtain the coordinates of each feature point on the slope corresponding to the most recent road to be monitored in each region, compare the coordinates of each feature point on the slope corresponding to the most recent road to be monitored in each region with the coordinates of each feature point on the slope corresponding to the most recent road to be monitored in each region, and obtain the displacement offset distance of each feature point on the slope corresponding to the road to be monitored in each region, which is recorded as , Indicates the history The number of feature points, ; By formula Obtain the displacement influence coefficient of the characteristic points on the slope corresponding to the monitored highway in each area , Expressed as the number of feature points, It is expressed as the safe displacement offset distance of the characteristic point on the slope corresponding to the preset road to be monitored.

8. The method for monitoring highway geological disasters based on remote sensing and BIM according to claim 7 is characterized in that: The displacement change rate of the characteristic points on the slopes corresponding to the roads to be monitored in each area is analyzed as follows: The BIM model images of the slopes corresponding to the roads to be monitored in each area in each historical monitoring are extracted from the database, and the displacement offset distances of each feature point of the slopes corresponding to the roads to be monitored in each area in each historical monitoring are obtained, which are recorded as ; By formula Obtain the displacement change rate of the characteristic points on the slope corresponding to the monitored highway in each area , Expressed as The slope corresponding to the road to be monitored in the area is The displacement offset distance of each feature point in the historical monitoring, Expressed as The slope corresponding to the road to be monitored in the area is The displacement offset distance of each feature point in the historical monitoring, It is represented by the displacement offset reference change value of the characteristic point on the slope corresponding to the preset road to be monitored.

9. The highway geological disaster monitoring method based on remote sensing and BIM according to claim 8 is characterized in that: The influence coefficient of the centroid position offset of the characteristic points on the slopes corresponding to the roads to be monitored in each area is analyzed as follows: Obtain the BIM model images of the slopes corresponding to the roads to be monitored in each area, obtain the center of gravity position and critical drop center of gravity position of each feature point on the slopes corresponding to the roads to be monitored in each area, compare the center of gravity position of each feature point on the slopes corresponding to the roads to be monitored in each area with the critical drop center of gravity position, and obtain the center of gravity position offset influence coefficient of foreign objects on the slopes corresponding to the roads to be monitored in each area .

10. A highway geological disaster monitoring method based on remote sensing and BIM according to claim 9, characterized in that: The analysis of the influence coefficient of geological disasters on the slopes of the roads to be monitored in each area is as follows: By formula Obtain the geological disaster impact coefficient on the slope corresponding to the monitored highway in each area ; The geological disaster impact coefficient on the slope corresponding to the roads to be monitored in each area is compared with the preset reference coefficient of geological disaster impact on the slope corresponding to the roads to be monitored. If the geological disaster impact coefficient on the slope corresponding to the roads to be monitored in a certain area is greater than the preset reference coefficient of geological disaster impact on the slope corresponding to the roads to be monitored, the number corresponding to the roads to be monitored in this area will be sent to relevant personnel and an early warning will be issued.

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