Matrix-based multipoint surface displacement monitoring method and device
By arranging multiple targets in the monitoring area and calculating the expansion rate of the ring, the problems of monitoring requirements and environmental factors of the movable measurement basis points in the prior art are solved, and accurate displacement monitoring and timely alarms are achieved under wind and vibration conditions.
Patent Information
- Application Number
- CN202510640867.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-19
- Publication Date
- 2025-08-15
AI Technical Summary
The existing monitoring methods cannot meet the monitoring needs of movable measurement basis points, and cannot avoid the adverse effects of environmental factors such as wind and vibration on the fixed measurement basis points, resulting in large errors in displacement analysis and judgment.
The matrix multi-point surface displacement monitoring method is used to determine the displacement by arranging M targets in the monitoring area and calculating the expansion rate of the ring. The area invariance of the ring is used to avoid the influence of environmental factors and adapt to the fixed and movable measurement base points.
It realizes accurate judgment of the surface displacement of the monitoring area under the influence of environmental factors, ensures timely alarm is issued, reduces disaster losses, and adapts to the needs of fixed and movable measurement base points.
Smart Images
Figure CN120488956A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of displacement monitoring, and in particular to a matrix-based multi-point surface displacement monitoring method and device. Background Art
[0002] Displacement, landslides, and subsidence disasters in mountains, slopes, reservoirs, tunnels, and bridges, caused by geological and structural factors, can cause damage to the national economy and people's lives and property. Early warning and preventative measures are crucial for effective response and prevention. This requires the establishment of single or multiple monitoring points on the surface (including shallow layers) of slopes, bridges, and buildings where displacement is to be detected. The number of monitoring points varies depending on the size of the monitoring area.
[0003] Traditional vision-based displacement monitoring methods utilize a camera (including video cameras, the same below) and a single target. This approach offers the advantages of simplicity, faster measurement, and relatively simple deployment. This method ensures measurement reliability and accuracy when the measurement base point (the fixed location of the camera) is stable and reliable. However, if the measurement base point is affected by wind, vibration, and other factors, significant errors can occur in the displacement analysis of the single target.
[0004] At present, the existing monitoring methods have high requirements for the fixed position of the measurement base point, which cannot meet the monitoring needs of mobile measurement base points (drone cameras). At the same time, they cannot avoid the adverse effects of environmental factors such as wind and vibration on fixed measurement base points, resulting in large errors in the displacement analysis and judgment of single targets, and then it is impossible to accurately determine whether surface displacement has occurred in the monitoring area. Summary of the Invention
[0005] The present application provides a matrix-based multi-point surface displacement monitoring method and device, which solves or partially solves the problems that existing monitoring methods cannot meet the monitoring needs of mobile measurement base points (drone cameras) and cannot avoid the adverse effects of environmental factors such as wind and vibration on fixed measurement base points.
[0006] The present application provides a matrix-based multi-point surface displacement monitoring method, comprising the following steps:
[0007] Place M targets on the surface of the monitoring area, M ≥ 3;
[0008] Collect monitoring images of the monitoring area at the measurement base point;
[0009] Obtaining pixel coordinates of the M targets in the monitoring image;
[0010] Construct corresponding circular rings according to the pixel coordinate points of any three of the M targets, forming N circular rings, where N≥1;
[0011] Calculate the current expansion rate of each ring in real time according to the expansion rate formula;
[0012] Whether risk displacement occurs on the surface of the monitoring area is determined based on the expansion rate; when the expansion rate is greater than a threshold, it is determined that risk displacement occurs on the surface of the monitoring area; when the expansion rate is less than or equal to the threshold, it is determined that risk displacement does not occur on the surface of the monitoring area.
[0013] Preferably, the surface of the monitoring area includes but is not limited to road slopes, reservoir slopes, mountains, tunnels and bridges.
[0014] Preferably, a plurality of monitoring points are set on the surface of the monitoring area, and M targets are set at each monitoring point.
[0015] Preferably, the measurement base point includes a fixed measurement base point and a movable measurement base point, the fixed measurement base point is provided with an image acquisition module with a fixed position; the movable measurement base point is provided with an image acquisition module with a variable position.
[0016] Preferably, the expansion rate formula is:
[0017] α=ΔS / S0, wherein α is the current expansion rate of the ring, ΔS is the current change of the ring, and S0 is the area of the ring at the last monitoring moment.
[0018] As an advantage, the method further comprises the following steps:
[0019] When the risk displacement occurs on the surface of the monitoring area, the pixel coordinates of the target with the largest risk displacement are determined based on the triangle relationship principle of the three targets in the ring;
[0020] According to a coordinate transformation formula, the pixel coordinates of the target with the largest risk displacement are converted into actual earth-sky coordinates;
[0021] The actual earth-sky coordinates of the target with the largest current risk displacement, the expansion rate, and the radius of the ring are sent to the information monitoring backend.
[0022] Preferably, the pixel coordinates of the target where the risk displacement is the largest are determined, and the triangle relationship principle is: when the displacement of the midpoint A of the triangle △ABC is the largest, the sum of the absolute values of the length changes of its two adjacent sides AB and AC (ΔAB+ΔAC) is the largest, where ΔAB=|A′B-AB|, ΔAC=|A′C-AC|;
[0023] The target point A with the largest risk displacement in each of the circular rings is determined by the triangle relationship principle. t, t = 1 ~ n; then compare each of the target points A t The sum of the absolute values of the length changes (ΔA t B+ΔA t C), the sum of the absolute values of length changes (ΔA t B+ΔA t C) The largest target point A t The target that has the greatest risk of displacement;
[0024] The target point A t The pixel coordinates are (x tp ,y tp ), the target point A t The actual earth-sky coordinates are (x te ,y te ); the coordinate transformation formula is: x te =f*x tp ,y te =f*y tp , f is the coordinate change coefficient, f = Le / Lp, Le is the calibration length in the actual world coordinates, and Lp represents the calibration length in the pixel coordinates.
[0025] Based on the same inventive concept, the present application also provides a matrix-based multi-point surface displacement monitoring device for implementing the matrix-based multi-point surface displacement monitoring method. The matrix-based multi-point surface displacement monitoring device includes: a plurality of the aforementioned targets, a support structure, an image acquisition module, an image processing module, a communication module, and an information monitoring background.
[0026] M targets are fixed at the monitoring points according to set positions, and a plurality of monitoring points are set on the surface of the monitoring area;
[0027] The image acquisition module is provided on the supporting structure and is used to acquire a monitoring image of the monitoring area and generate monitoring image information, wherein the monitoring image information includes pixel coordinates of all the targets at each of the monitoring points;
[0028] The image processing module generates image processing information after receiving the monitoring image information; the image processing information includes: the pixel coordinates of the center of the ring, the radius of the ring, the area of the ring, the current expansion rate of each ring, whether the surface of the monitoring area has a risk displacement, and the pixel coordinates of the target with the largest displacement when the risk displacement occurs;
[0029] The communication module sends the image processing information to the information monitoring background;
[0030] The information monitoring background receives and stores the image processing information, and issues a displacement alarm on the surface of the monitoring area according to the image processing information.
[0031] Preferably, the image acquisition module is a camera or a video camera;
[0032] The supporting structure is a fixed pole or a drone pod. The fixed pole is set at a fixed monitoring point to form a fixed measurement base point; the drone pod is set at multiple monitoring points on the line inspection path to form a movable measurement base point.
[0033] Preferably, the image processing module includes: a ring construction unit, an expansion rate calculation unit, and a risk displacement judgment unit.
[0034] The ring construction unit determines the pixel coordinates of the center of the ring, the radius of the ring, and the area of the ring through the pixel coordinates of any three of the M targets;
[0035] The expansion rate calculation unit calculates the current expansion rate of each ring in real time using an expansion rate formula;
[0036] The risk displacement judgment unit judges whether risk displacement occurs on the surface of the monitoring area by the current expansion rate of the ring. The specific judgment process is: when the expansion rate is greater than a threshold, it is determined that risk displacement occurs on the surface of the monitoring area; when the expansion rate is less than or equal to the threshold, it is determined that risk displacement does not occur on the surface of the monitoring area.
[0037] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:
[0038] The matrix-based multi-point surface displacement monitoring method of the present application determines whether a surface risk displacement has occurred at the monitoring target point by calculating the expansion rate of the circular ring. Due to the invariance of the circular rotation area, when the image acquisition module of the measurement base point vibrates or shakes, the expansion rate of the circular ring will not change, thereby avoiding the adverse effects of environmental factors such as wind and vibration on the fixed measurement base point, and quickly determining whether a surface risk displacement has occurred, ensuring the accuracy of the judgment, and ensuring that an alarm can be issued in time to reduce the loss of life and property caused by the disaster. At the same time, when the position of the monitoring base point changes significantly, the expansion rate of the circular ring determined by the pixel coordinates of the target will still not change; therefore, this monitoring method can not only adapt to the situation of fixed measurement base points (cameras installed on fixed poles), but also adapt to the situation of movable measurement base points (cameras mounted on drone pods), meeting the current demand for rapid drone patrol-based monitoring of surface risk displacement. BRIEF DESCRIPTION OF THE DRAWINGS
[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0040] Figure 1 This is a flowchart of a matrix-based multi-point surface displacement monitoring method provided in an embodiment of the present application. DETAILED DESCRIPTION
[0041] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.
[0042] See attached Figure 1 The first aspect of the present invention proposes a matrix-based multi-point surface displacement monitoring method, comprising the following steps:
[0043] 1. Data Collection
[0044] Fixed monitoring points (such as poles) or drone pods use dedicated or ordinary cameras (including video cameras) to collect images of the monitoring area.
[0045] 2. Image Recognition
[0046] An image recognition algorithm is used to identify M targets in the image, preferably 3 targets.
[0047] 3. Ring matching
[0048] Find N matching rings from M targets, and 3 targets correspond to 1 ring.
[0049] 4. Expansion rate calculation
[0050] Use the three target points to establish the equation of the circle, solve for the center and radius, and then calculate the expansion rate of each ring, specifically:
[0051] Step 1: Create an equation using three points
[0052] Substituting the three points into the circle equation, we get three equations:
[0053]
[0054] Eliminate r by pairwise subtraction2 , we get two linear equations:
[0055]
[0056] Expanding and simplifying, we obtain a system of linear equations about h and k:
[0057]
[0058] Step 2: Solve the system of equations to find the center of the circle (h, k)
[0059] Solve the above linear equations to obtain the coordinates of the center of the circle (h, k).
[0060] Step 3: Find the radius r
[0061] Substitute the center (h, k) into the equation for any point to calculate the radius:
[0062]
[0063] Step 4: r conversion. The above r is the r in the pixel coordinates of the image; it needs to be converted to the real R in the actual sky and earth coordinates;
[0064] R = r × f, where:
[0065]
[0066] f: coordinate transformation coefficient;
[0067] Le: the actual length of the target in earth-sky coordinates;
[0068] Lp: represents the length in pixel coordinates.
[0069] Calculation of the area of the ring in actual celestial coordinates: S = π(r×f) 2 .
[0070] Calculate the expansion rate: α = ΔS / S0, where α is the expansion rate, ΔS is the area change, and S0 is the area value of the last measurement.
[0071] 5. Displacement judgment
[0072] If the expansion rate is less than the set threshold, the monitoring is completed.
[0073] If the expansion rate exceeds the set threshold, it is determined that there is surface displacement.
[0074] 6. Find the target with the maximum displacement and calculate its displacement value
[0075] According to the angular relationship between the midpoints of the ring, the point P with the largest change is found. By converting pixel coordinates and world coordinates, the actual displacement of point P is calculated as follows:
[0076] Principle of triangle relationship: When the displacement of a point in a triangle is the largest, the sum of the absolute values of the changes in the lengths of the two adjacent sides is the largest;
[0077] Suppose that in triangle △ABC, point A moves to A′, and study the relationship between the changes in side lengths ΔAB=|A′B-AB| and ΔAC=|A′C-AC| and the changes in other sides.
[0078] Triangle inequality: The sum of any two sides is greater than the third side, and after displacement, the constraints such as A′B+A′C>BC are still satisfied.
[0079] Extreme point analysis: When A' is displaced to maximize ΔAB+ΔAC, it is usually located at a boundary position (such as the intersection of the extended lines or the collinear state). At this time: If A' makes B, A', and C collinear, then ΔAB+ΔAC=BC, reaching the theoretical maximum value. When not collinear, the extreme value of ΔAB+ΔAC can be proved by coordinate system or vector analysis.
[0080] Assume the initial coordinates A(x0,y0), after displacement A′(x0+δ x ,y0+δ y ),but:
[0081]
[0082] Taking partial derivatives of ΔAB+ΔAC and analyzing the extreme points, we can verify that when δ x , δ y Direction and When they are consistent, the sum of the changes is the largest.
[0083] Therefore, through geometric constraints, algebraic extreme value analysis and example verification, it can be strictly proved that when the displacement of a point in a triangle is the largest, the absolute value of the sum of the changes in the lengths of its two adjacent sides must be the largest. This is determined by the triangle inequality and the extreme value principle.
[0084] Therefore, the target point A with the largest risk displacement in each ring is determined by the above triangle relationship principle. t , t=1~n; then compare each target point A t The sum of the absolute values of the length changes (ΔA t B+ΔA t C), the sum of the absolute values of length changes (ΔA t B+ΔA t C) The largest target point A t This is the target with the greatest risk of displacement.
[0085] Target point A t The pixel coordinates are (x tp ,y tp ), target point At The actual earth-sky coordinates are (x te ,y te ); the coordinate transformation formula is: x te =f*x tp ,y te =f*y tp , f is the coordinate change coefficient, f = Le / Lp, Le is the calibration length in the actual world coordinates, and Lp represents the calibration length in the pixel coordinates.
[0086] 7. Result output
[0087] Output the displacement value, expansion rate and latest radius of the point with the largest displacement change to the back-end platform.
[0088] The second aspect of the present invention proposes a matrix-based multi-point surface displacement monitoring device for implementing the above method, comprising multiple targets, a support structure, an image acquisition module, an image processing module, a communication module, and an information monitoring background.
[0089] M (preferably M=3) targets are fixed at the monitoring points according to set positions, and 5 monitoring points are set on the surface of the monitoring area.
[0090] The image acquisition module is set on the supporting structure. The image acquisition module is a camera or a video camera, which is used to collect monitoring images of the monitoring area and generate monitoring image information. The monitoring image information contains the pixel coordinates of all targets in each monitoring point; the supporting structure is a fixed pole or a drone pod. The fixed pole is set at a fixed monitoring point to form a fixed measurement base point; the drone pod sets multiple monitoring points on the patrol path to form a movable measurement base point.
[0091] The image processing module generates image processing information after receiving the monitoring image information; the image processing information includes: the pixel coordinates of the center of the ring, the radius of the ring, the area of the ring, the current expansion rate of each ring, whether risk displacement occurs on the surface of the monitoring area, and the pixel coordinates of the target with the largest displacement when risk displacement occurs.
[0092] The communication module sends the image processing information to the information monitoring background.
[0093] The information monitoring background receives and stores image processing information, and issues displacement alarms on the surface of the monitoring area based on the image processing information.
[0094] The image processing module includes: a ring construction unit, an expansion rate calculation unit, and a risk displacement judgment unit. The ring construction unit determines the pixel coordinates of the center of the ring, the radius of the ring, and the area of the ring through the pixel coordinates of three targets; the expansion rate calculation unit calculates the current expansion rate of each ring in real time through the expansion rate formula; the risk displacement judgment unit judges whether the surface of the monitoring area has risk displacement based on the current expansion rate of the ring. The specific judgment process is: when the expansion rate is greater than the threshold, it is determined that the surface of the monitoring area has risk displacement; when the expansion rate is less than or equal to the threshold, it is determined that the surface of the monitoring area has not risk displacement.
[0095] In summary, this monitoring method is not only adaptable to the situation of fixed measurement base points (cameras installed on fixed poles), but also to the situation of movable measurement base points (cameras mounted on drone pods), meeting the current demand for rapid drone patrol-based monitoring of surface risk displacement.
[0096] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.
Claims
1. A matrix-based multi-point surface displacement monitoring method, characterized in that: The following steps are involved: Place M targets on the surface of the monitoring area, M ≥ 3; Collect monitoring images of the monitoring area at the measurement base point; Obtaining pixel coordinates of the M targets in the monitoring image; Construct corresponding circular rings according to the pixel coordinate points of any three of the M targets, forming N circular rings, where N≥1; Calculate the current expansion rate of each ring in real time according to the expansion rate formula; determining whether risky displacement occurs on the surface of the monitoring area according to the expansion rate; When the expansion rate is greater than a threshold, determining that the risk displacement occurs on the surface of the monitoring area; When the expansion rate is less than or equal to a threshold, it is determined that the risk displacement does not occur on the surface of the monitoring area.
2. The matrix-based multi-point surface displacement monitoring method according to claim 1, characterized in that: The surface of the monitoring area includes but is not limited to road slopes, reservoir slopes, mountains, tunnels and bridges.
3. The matrix-based multi-point surface displacement monitoring method according to claim 1, characterized in that: A plurality of monitoring points are set on the surface of the monitoring area, and M targets are set at each monitoring point.
4. The matrix-based multi-point surface displacement monitoring method according to claim 1, characterized in that: The measurement base points include fixed measurement base points and movable measurement base points. The fixed measurement base points are provided with an image acquisition module with a fixed position; the movable measurement base points are provided with an image acquisition module with a variable position.
5. The matrix-based multi-point surface displacement monitoring method according to claim 1, characterized in that: The expansion rate formula is: α=ΔS / S0, wherein α is the current expansion rate of the ring, ΔS is the current change of the ring, and S0 is the area of the ring at the last monitoring moment.
6. The matrix-based multi-point surface displacement monitoring method according to claim 1, characterized in that: The following steps are also included: When the risk displacement occurs on the surface of the monitoring area, the pixel coordinates of the target with the largest risk displacement are determined based on the triangle relationship principle of the three targets in the ring; According to a coordinate transformation formula, the pixel coordinates of the target with the largest risk displacement are converted into actual earth-sky coordinates; The actual earth-sky coordinates of the target with the largest current risk displacement, the expansion rate, and the radius of the ring are sent to the information monitoring backend.
7. The matrix-based multi-point surface displacement monitoring method according to claim 6, characterized in that: The triangle relationship principle is: when the displacement of the midpoint A of the triangle △ABC is the largest, the sum of the absolute values of the length changes of its two adjacent sides AB and AC (ΔAB+ΔAC) is the largest, where ΔAB=|A′B-AB|, ΔAC=|A′C-AC|; The target point A with the largest risk displacement in each of the circular rings is determined by the triangle relationship principle. t , t = 1 ~ n; then compare each of the target points A t The sum of the absolute values of the length changes (ΔA t B+ΔA t C), the sum of the absolute values of length changes (ΔA t B+ΔA t C) The largest target point A t The target that has the greatest risk of displacement; The target point A t The pixel coordinates are (x tp ,y tp ), the target point A t The actual earth-sky coordinates are (x te ,y te ); the coordinate transformation formula is: x te =f*x tp ,y te =f*y tp , f is the coordinate change coefficient, f = Le / Lp, Le is the calibration length in the actual world coordinates, and Lp represents the calibration length in the pixel coordinates.
8. A matrix-based multi-point surface displacement monitoring device, characterized in that: For implementing the matrix-based multi-point surface displacement monitoring method according to any one of claims 1 to 7, the matrix-based multi-point surface displacement monitoring device comprises: a plurality of the targets, a support structure, an image acquisition module, an image processing module, a communication module and an information monitoring background, M targets are fixed at the monitoring points according to set positions, and a plurality of monitoring points are set on the surface of the monitoring area; The image acquisition module is provided on the supporting structure and is used to acquire a monitoring image of the monitoring area and generate monitoring image information, wherein the monitoring image information includes pixel coordinates of all the targets at each of the monitoring points; The image processing module generates image processing information after receiving the monitoring image information; the image processing information includes: the pixel coordinates of the center of the ring, the radius of the ring, the area of the ring, the current expansion rate of each ring, whether the surface of the monitoring area has a risk displacement, and the pixel coordinates of the target with the largest displacement when the risk displacement occurs; The communication module sends the image processing information to the information monitoring background; The information monitoring background receives and stores the image processing information, and issues a displacement alarm on the surface of the monitoring area according to the image processing information.
9. The matrix-based multi-point surface displacement monitoring device according to claim 8, characterized in that: The image acquisition module is a camera or a video camera; The supporting structure is a fixed pole or a drone pod. The fixed pole is set at a fixed monitoring point to form a fixed measurement base point; the drone pod is set at multiple monitoring points on the line inspection path to form a movable measurement base point.
10. The matrix-based multi-point surface displacement monitoring device according to claim 8, characterized in that: The image processing module includes: a ring construction unit, an expansion rate calculation unit, and a risk displacement judgment unit. The ring construction unit determines the pixel coordinates of the center of the ring, the radius of the ring, and the area of the ring through the pixel coordinates of any three of the M targets; The expansion rate calculation unit calculates the current expansion rate of each ring in real time using an expansion rate formula; The risk displacement judgment unit judges whether risk displacement occurs on the surface of the monitoring area by the current expansion rate of the ring. The specific judgment process is: when the expansion rate is greater than a threshold, it is determined that risk displacement occurs on the surface of the monitoring area; when the expansion rate is less than or equal to the threshold, it is determined that risk displacement does not occur on the surface of the monitoring area.