Ground deformation measurement method, device, equipment and storage medium

Abstract

This application discloses a foundation deformation measurement method, apparatus, device, and storage medium, belonging to the field of deformation monitoring technology. This application obtains image data of a preset reference object at each monitoring point in the foundation; processes the image data to obtain a contour model of the preset reference object; and determines the foundation deformation value based on the contour model of the preset reference object and the standard contour model corresponding to the preset reference object. This eliminates the influence of human subjective factors on the measurement results and improves measurement accuracy.

Description

Technical Field

[0001] The present application relates to the field of deformation monitoring technology, and in particular to a foundation deformation measurement method, device, equipment and storage medium. Background Art

[0002] The foundation is the soil or rock mass beneath a building, supporting its foundations. It plays an irreplaceable role in the stability of the superstructure. Existing methods for measuring foundation deformation typically rely on manual measurement, using instruments like theodolites and levels. However, these measurements are susceptible to subjective influences, making accuracy difficult to guarantee. Summary of the Invention

[0003] The main purpose of this application is to provide a foundation deformation measurement method, device, equipment and storage medium, aiming to solve the technical problem of low measurement accuracy when measuring foundation deformation values ​​manually.

[0004] To achieve the above objectives, the present application provides a method for measuring foundation deformation, comprising the following steps:

[0005] Obtain image data of preset benchmarks at each monitoring point in the foundation;

[0006] Processing the image data to obtain a contour model of the preset reference object;

[0007] The foundation deformation value is determined based on the contour model of the preset benchmark object and the standard contour model corresponding to the preset benchmark object.

[0008] Optionally, the standard contour model includes a plurality of first feature points, the contour model includes a plurality of second feature points, the first feature points correspond to the second feature points, and the step of determining the foundation deformation value based on the contour model of the preset benchmark object and the standard contour model corresponding to the preset benchmark object includes:

[0009] When the center point of the contour model coincides with the center point of the standard contour model, calculating the distance between the first feature point and its corresponding second feature point to obtain a plurality of distance differences;

[0010] Determining a deformation value of each monitoring point based on the plurality of distance differences;

[0011] The foundation deformation value is determined based on the deformation value of each monitoring point.

[0012] Optionally, the step of determining the deformation value of each monitoring point based on the plurality of distance differences includes:

[0013] Classifying the distance differences according to the orientation information of the first feature point / the second feature point corresponding to the distance differences to obtain a horizontal distance difference and a vertical distance difference;

[0014] Calculating the average value of the horizontal distance difference to determine the horizontal deformation value of each monitoring point;

[0015] Calculating the average value of the distance difference in the vertical direction to determine the deformation value in the vertical direction of each monitoring point;

[0016] The deformation value of each monitoring point is determined based on the deformation value of each monitoring point in the horizontal direction and the deformation value of each monitoring point in the vertical direction.

[0017] Optionally, the step of determining the foundation deformation value based on the deformation value of each monitoring point includes:

[0018] fitting a foundation deformation surface according to the deformation values ​​of each monitoring point and the position information of each monitoring point;

[0019] The foundation deformation surface is compared with the foundation deformation surface of the previous time series to determine the foundation deformation value.

[0020] Optionally, the step of determining the foundation deformation value based on the contour model of the preset benchmark object and the standard contour model corresponding to the preset benchmark object includes:

[0021] When the center point of the contour model coincides with the center point of the standard contour model, obtaining an area in the standard contour model that does not coincide with the contour model;

[0022] Performing color value extraction processing on the pixel points in the non-overlapping area to obtain the RGB color value of each pixel point in the non-overlapping area;

[0023] Mean clustering is performed on the RGB color value of each pixel, and the foundation deformation value is determined according to the clustering result.

[0024] Optionally, the step of determining the foundation deformation value according to the clustering result includes:

[0025] Determining a deformation correlation coefficient according to the clustering result, wherein the clustering result is proportional to the deformation correlation coefficient;

[0026] The foundation deformation value is determined based on the area of ​​the region in the standard contour model that does not overlap with the contour model and the deformation correlation coefficient.

[0027] Optionally, before the step of processing the image data to obtain the contour model of the preset reference object, the method further includes:

[0028] performing correction processing on the image data to obtain corrected image data;

[0029] The step of processing the image data to obtain the contour model of the preset reference object includes:

[0030] The corrected image data is processed to obtain a contour model of the preset reference object.

[0031] In addition, to achieve the above-mentioned purpose, the present application also provides a foundation deformation measurement device, which includes:

[0032] A data acquisition module is used to obtain image data of preset benchmarks at each monitoring point in the foundation;

[0033] An image processing module, configured to process the image data to obtain a contour model of the preset reference object;

[0034] The deformation determination module is used to determine the foundation deformation value based on the contour model of the preset benchmark object and the standard contour model corresponding to the preset benchmark object.

[0035] In addition, to achieve the above-mentioned purpose, the present application also provides a foundation deformation measurement device, which includes: a memory, a processor, and a foundation deformation measurement program stored on the memory and executable on the processor, wherein the foundation deformation measurement program is configured to implement the steps of the foundation deformation measurement method as described above.

[0036] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, on which a foundation deformation measurement program is stored. When the foundation deformation measurement program is executed by a processor, the steps of the foundation deformation measurement method described above are implemented.

[0037] The present application discloses a foundation deformation measurement method, device, equipment and storage medium. Compared with the prior art in which the measurement accuracy is low when the foundation deformation value is measured manually, the present application obtains image data of a preset reference object at each monitoring point in the foundation; processes the image data to obtain a contour model of the preset reference object; and determines the foundation deformation value based on the contour model of the preset reference object and a standard contour model corresponding to the preset reference object, thereby eliminating the influence of human subjective factors on the measurement results and improving the measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[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, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0040] Figure 1 It is a structural diagram of a foundation deformation measurement device in the hardware operating environment involved in the embodiment of the present application;

[0041] Figure 2 This is a flow chart of a first embodiment of a method for measuring foundation deformation according to the present application;

[0042] Figure 3 This is a schematic diagram of the functional modules of the first embodiment of the foundation deformation measuring device of the present application.

[0043] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0044] It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0045] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of the foundation deformation measurement equipment in the hardware operating environment involved in the embodiment of the present application.

[0046] like Figure 1 As shown, the foundation deformation measurement device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (WI-FI) interface). The memory 1005 may be a high-speed random access memory (RAM) memory or a stable non-volatile memory (NVM), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0047] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation to the foundation deformation measuring device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0048] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a data storage module, a network communication module, a user interface module and a foundation deformation measurement program.

[0049] exist Figure 1 In the foundation deformation measuring device shown, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the foundation deformation measuring device of the present application can be set in the foundation deformation measuring device, and the foundation deformation measuring device calls the foundation deformation measurement program stored in the memory 1005 through the processor 1001 and executes the foundation deformation measurement method provided in the embodiment of the present application.

[0050] The present invention provides a method for measuring foundation deformation. Figure 2 , Figure 2 This is a flow chart of a first embodiment of a method for measuring foundation deformation according to the present application.

[0051] In this embodiment, the foundation deformation measurement method includes:

[0052] Step S10: Acquire image data of preset benchmarks at each monitoring point in the foundation.

[0053] It should be noted that in this embodiment, when the preset reference object is initially set at each monitoring point in the foundation, initial image data of the preset reference object at the current moment is acquired, and the vertical elevation angle, horizontal angle, and actual distance between the monitoring point and the camera at the time of acquiring the initial image data are recorded. In subsequent measurement processes, the vertical elevation angle, horizontal angle, and actual distance between the camera and the monitoring point used to acquire image data of the preset reference object at each monitoring point in the foundation are the same as the vertical elevation angle, horizontal angle, and actual distance between the camera and the monitoring point at the time of acquiring the initial image data.

[0054] It should be noted that when obtaining image data of preset benchmarks at each monitoring point in the foundation, if the brightness of the surrounding lighting environment is lower than the preset brightness value, infrared lighting can be activated. At this time, the camera needs to be equipped with an infrared filter.

[0055] Step S20: Process the image data to obtain a contour model of the preset reference object.

[0056] In this embodiment, specifically, processing the image data to obtain the contour model of the preset reference object includes:

[0057] Performing binarization processing on the preset target area in the image data;

[0058] Performing edge extraction on the preset target object area after the binarization process to obtain a fuzzy contour model of the preset target object, wherein the edge extraction process can be implemented by using a dual-threshold edge extraction method;

[0059] The fuzzy contour model of the preset reference object is made transparent to obtain the contour model of the preset reference object.

[0060] It should be noted that the transparency processing of the fuzzy contour model of the preset reference object is: all pixels except the contour in the fuzzy contour model are fully transparent, and the pixels of the contour in the fuzzy contour model are semi-transparent, where the transparency ratio between the full transparency processing and the semi-transparency processing can be set according to the actual application situation.

[0061] Furthermore, in this embodiment, before the step of processing the image data to obtain the contour model of the preset reference object, the method further includes:

[0062] Correction processing is performed on the image data to obtain corrected image data.

[0063] In this embodiment, a correction area is provided in the central area of ​​the preset reference object, and the center of the correction area coincides with the center of the preset reference object.

[0064] Specifically, the image data is corrected to obtain corrected image data:

[0065] The correction region of the preset reference object in the image data is compared with the correction region of the preset reference object in the initial image data, and the image data is corrected according to the comparison result to obtain the corrected image data.

[0066] For example, if the area ratio of the correction area in the preset reference object in the image data to the correction area in the preset reference object in the initial image data is 2:3, the image data is enlarged and corrected according to the aforementioned area ratio; if the area ratio of the correction area in the preset reference object in the image data to the correction area in the preset reference object in the initial image data is 3:2, the image data is reduced and corrected according to the aforementioned area ratio.

[0067] Step S30: determining a foundation deformation value based on the contour model of the preset benchmark object and a standard contour model corresponding to the preset benchmark object.

[0068] It should be noted that the method for obtaining the standard contour model corresponding to the preset reference object in this embodiment includes:

[0069] When the preset benchmark is initially set at each monitoring point in the foundation, initial image data of the preset benchmark at the current moment is obtained, wherein the initial image data includes the preset benchmark area and the foundation area surrounding the preset benchmark;

[0070] Performing binarization processing on the preset target area in the initial image data;

[0071] Performing edge extraction on the preset reference object area after the binarization process to obtain an initial contour model of the preset reference object, wherein the edge extraction process can be implemented by using a dual-threshold edge extraction method;

[0072] The initial contour model of the preset reference object is made transparent to obtain a standard contour model of the preset reference object.

[0073] It should be noted that the transparency processing of the initial contour model of the preset reference object is: all pixels except the contour in the initial contour model are fully transparent, and the pixels of the contour in the initial contour model are semi-transparent, where the transparency ratio between the full transparency processing and the semi-transparency processing can be set according to the actual application situation.

[0074] It should be noted that the preset reference object may be of a regular shape or an irregular shape, and the outer surface of the preset reference object may be of the same color or of multiple colors.

[0075] In this embodiment, when the predetermined reference object is of a regular shape and its outer surface is of a single color, a number of first feature points can be set in the standard contour model based on the predetermined reference object's regular shape. If the predetermined reference object is a polygon, the first feature points are the vertices and midpoints of the sides of the polygon. If the predetermined reference object is a circle, the first feature points are the points dividing the circumference of the circle. For example, a point dividing the circumference is set every 30 degrees. Because the standard contour model and the contour model both correspond to the same predetermined reference object, the contour model includes a number of second feature points, and the second feature points in the contour model correspond one-to-one with the first feature points in the standard contour model.

[0076] Specifically, determining the foundation deformation value based on the contour model of the preset benchmark object and the standard contour model corresponding to the preset benchmark object includes:

[0077] Step S31a: When the center point of the contour model coincides with the center point of the standard contour model, the distance between the first feature point and its corresponding second feature point is calculated to obtain a plurality of distance differences.

[0078] It should be noted that, in this embodiment, the process of calculating the distance between the first feature point and its corresponding second feature point to obtain a number of distance differences is as follows:

[0079] A two-dimensional coordinate system is constructed with the center point of the standard contour model and the center point of the contour model as the origin, and the coordinate values ​​of the first feature point and the second feature point in the two-dimensional coordinate system are obtained. Based on the straight-line distance calculation formula between the two points, the coordinate value of the first feature point and the coordinate value of its corresponding second feature point, the distance difference is calculated.

[0080] Step S32a: Determine the deformation value of each monitoring point based on the plurality of distance differences.

[0081] Specifically, based on the plurality of distance differences, determining the deformation value of each monitoring point includes:

[0082] Step S32a1: classify the distance differences according to the orientation information of the first feature point / the second feature point corresponding to the distance differences to obtain the distance differences in the horizontal direction and the distance differences in the vertical direction.

[0083] It should be noted that, in this embodiment, the step of classifying a plurality of distance differences according to the orientation information of the first feature point corresponding to the distance difference to obtain the horizontal distance difference and the vertical distance difference includes:

[0084] A two-dimensional coordinate system is constructed with the center point of the standard contour model as the origin, and the standard contour model is placed in the two-dimensional coordinate system according to the placement direction of the preset reference object in the image data. The angle between the first feature point and the X-axis is calculated. If the angle between the first feature point and the X-axis is greater than or equal to the preset angle value, the distance difference corresponding to the first feature point is determined to be the horizontal distance difference. Conversely, if the angle between the first feature point and the X-axis is less than the preset angle value, the distance difference corresponding to the first feature point is determined to be the vertical distance difference.

[0085] It should be noted that, in this embodiment, the step of classifying a plurality of distance differences according to the orientation information of the second feature points corresponding to the distance differences to obtain the horizontal distance differences and the vertical distance differences includes:

[0086] A two-dimensional coordinate system is constructed with the center point of the contour model as the origin, and the contour model is placed in the two-dimensional coordinate system according to the placement direction of the preset reference object in the image data. The angle between the second feature point and the X-axis is calculated. If the angle between the second feature point and the X-axis is greater than or equal to the preset angle value, the distance difference corresponding to the second feature point is determined to be the distance difference in the horizontal direction. Conversely, if the angle between the second feature point and the X-axis is less than the preset angle value, the distance difference corresponding to the second feature point is determined to be the distance difference in the vertical direction.

[0087] Step S32a2: Calculate the average value of the horizontal distance difference to determine the horizontal deformation value of each monitoring point.

[0088] It should be noted that, in this embodiment, the average value of the distance differences in the horizontal direction is the deformation value of each monitoring point in the horizontal direction.

[0089] Step S32a3: Calculate the average value of the distance difference in the vertical direction to determine the deformation value of each monitoring point in the vertical direction.

[0090] It should be noted that, in this embodiment, the average value of the distance differences in the vertical direction is the deformation value of each monitoring point in the vertical direction.

[0091] Step S32a4: Determine the deformation value of each monitoring point based on the horizontal deformation value of each monitoring point and the vertical deformation value of each monitoring point.

[0092] It should be noted that, in this embodiment, based on the deformation value of each monitoring point in the horizontal direction and the deformation value of each monitoring point in the vertical direction, the deformation value of each monitoring point can be determined as follows: first, the sum of the squares of the deformation value of each monitoring point in the horizontal direction and the deformation value of each monitoring point in the vertical direction is calculated, and then the square root of the above-mentioned sum of squares is obtained, and the value obtained is the deformation value of each monitoring point.

[0093] Step S33a: Determine the foundation deformation value based on the deformation value of each monitoring point.

[0094] Specifically, determining the foundation deformation value based on the deformation value of each monitoring point includes:

[0095] Step S33a1: fitting a foundation deformation surface based on the deformation value of each monitoring point and the position information of each monitoring point.

[0096] Step S33a2: Compare the foundation deformation surface with the foundation deformation surface of the previous time series to determine the foundation deformation value.

[0097] It should be noted that, in this embodiment, the difference between the area of ​​the foundation deformation curved surface and the foundation deformation curved surface in the previous time sequence is the foundation deformation value.

[0098] In this embodiment, when the preset reference object is irregular in shape and the outer surface of the preset reference object is multi-colored, specifically, determining the foundation deformation value based on the contour model of the preset reference object and the standard contour model corresponding to the preset reference object includes:

[0099] Step S31b: when the center point of the contour model coincides with the center point of the standard contour model, obtaining a region in the standard contour model that does not coincide with the contour model.

[0100] Step S32b: performing color value extraction processing on the pixel points in the non-overlapping area to obtain the RGB color value of each pixel point in the non-overlapping area.

[0101] Step S33b: performing mean clustering on the RGB color value of each pixel, and determining the foundation deformation value according to the clustering result.

[0102] In this embodiment, specifically, performing mean value clustering on the RGB color value of each pixel includes:

[0103] 1) Initialize K cluster centers, which are U1, U2, ..., Uk;

[0104] 2) All pixel R values ​​are assigned to the nearest cluster set according to the principle of minimum distance, where the distance is calculated using Euclidean distance;

[0105] 3) The mean of all R values ​​in each cluster set is used as the new cluster center;

[0106] 4) Repeat steps 1) to 3) until the cluster center no longer changes;

[0107] 5) End, and get the k cluster values ​​corresponding to the R value.

[0108] Repeat the above steps 1) to 5) for the G value and B value of each pixel point respectively to obtain j cluster values ​​corresponding to the G value and m cluster values ​​corresponding to the B value.

[0109] The k cluster values ​​corresponding to the R value, the j cluster values ​​corresponding to the G value, and the m cluster values ​​corresponding to the B value are added together to obtain the clustering result.

[0110] In this embodiment, specifically, determining the foundation deformation value according to the clustering result includes:

[0111] Determining a deformation correlation coefficient according to the clustering result, wherein the clustering result is proportional to the deformation correlation coefficient;

[0112] The foundation deformation value is determined based on the area of ​​the region in the standard contour model that does not overlap with the contour model and the deformation correlation coefficient.

[0113] It should be noted that, in this embodiment, the deformation correlation coefficient can be determined based on the clustering results by querying the deformation correlation coefficient from a clustering result-deformation correlation coefficient table based on the clustering results. The clustering result-deformation correlation coefficient table can be obtained through multiple experiments.

[0114] It should be noted that, in this embodiment, based on the area of ​​the area in the standard contour model that does not overlap with the contour model and the deformation correlation coefficient, the foundation deformation value can be determined by multiplying the area of ​​the area in the standard contour model that does not overlap with the contour model and the deformation correlation coefficient, and the final product is the foundation deformation value.

[0115] Compared with the prior art in which the measurement accuracy is low when the foundation deformation value is measured manually, this embodiment obtains image data of a preset reference object at each monitoring point in the foundation; processes the image data to obtain a contour model of the preset reference object; and determines the foundation deformation value based on the contour model of the preset reference object and the standard contour model corresponding to the preset reference object, thereby eliminating the influence of human subjective factors on the measurement results and improving the measurement accuracy.

[0116] The present application also provides a foundation deformation measuring device, referring to Figure 3 , Figure 3 This is a schematic diagram of the functional modules of the first embodiment of the foundation deformation measuring device of the present application.

[0117] In this embodiment, the foundation deformation measuring device includes:

[0118] The data acquisition module 10 is used to acquire image data of preset benchmarks at each monitoring point in the foundation;

[0119] An image processing module 20 is used to process the image data to obtain a contour model of the preset reference object;

[0120] The deformation determination module 30 is configured to determine a foundation deformation value based on the contour model of the preset benchmark object and a standard contour model corresponding to the preset benchmark object.

[0121] Optionally, the standard contour model includes a plurality of first feature points, the contour model includes a plurality of second feature points, the first feature points correspond to the second feature points, and the deformation determination module includes:

[0122] a distance difference determination subunit, configured to calculate the distance between the first feature point and its corresponding second feature point when the center point of the contour model coincides with the center point of the standard contour model, to obtain a plurality of distance differences;

[0123] a first deformation determination subunit, configured to determine a deformation value of each monitoring point based on the plurality of distance differences;

[0124] The second deformation determining subunit is configured to determine a foundation deformation value based on the deformation values ​​of the monitoring points.

[0125] Optionally, the first deformation determination subunit is configured to: classify the distance differences according to the orientation information of the first feature point / the second feature point corresponding to the distance differences, to obtain the distance differences in the horizontal direction and the distance differences in the vertical direction;

[0126] Calculating the average value of the horizontal distance difference to determine the horizontal deformation value of each monitoring point;

[0127] Calculating the average value of the distance difference in the vertical direction to determine the deformation value in the vertical direction of each monitoring point;

[0128] The deformation value of each monitoring point is determined based on the deformation value of each monitoring point in the horizontal direction and the deformation value of each monitoring point in the vertical direction.

[0129] Optionally, the second deformation determination subunit is configured to implement: fitting a foundation deformation surface according to the deformation values ​​of the monitoring points and the position information of the monitoring points;

[0130] The foundation deformation surface is compared with the foundation deformation surface of the previous time series to determine the foundation deformation value.

[0131] Optionally, the deformation determination module includes:

[0132] a non-overlapping region determining subunit, configured to obtain a non-overlapping region in the standard contour model when the center point of the contour model overlaps with the center point of the standard contour model;

[0133] A color value extraction subunit is used to perform color value extraction processing on the pixel points in the non-overlapping area to obtain the RGB color value of each pixel point in the non-overlapping area;

[0134] A mean clustering subunit, configured to perform mean clustering on the RGB color value of each pixel;

[0135] The third deformation determination subunit is used to determine the foundation deformation value according to the clustering result.

[0136] Optionally, the third deformation determining subunit is configured to implement:

[0137] Determining a deformation correlation coefficient according to the clustering result, wherein the clustering result is proportional to the deformation correlation coefficient;

[0138] The foundation deformation value is determined based on the area of ​​the region in the standard contour model that does not overlap with the contour model and the deformation correlation coefficient.

[0139] Optionally, the foundation deformation measuring device further includes:

[0140] A correction module, configured to perform correction processing on the image data to obtain corrected image data;

[0141] The image processing module is used to process the corrected image data to obtain the contour model of the preset reference object.

[0142] The specific implementation of the foundation deformation measuring device of the present application is basically the same as the embodiments of the above-mentioned foundation deformation measuring method, and will not be repeated here.

[0143] An embodiment of the present application further provides a storage medium, on which a foundation deformation measurement program is stored. When the foundation deformation measurement program is executed by a processor, the steps of the foundation deformation measurement method described above are implemented.

[0144] The specific implementation of the storage medium of the present application is basically the same as the embodiments of the above-mentioned foundation deformation measurement method, and will not be repeated here.

[0145] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0146] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0147] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0148] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for measuring foundation deformation, characterized in that: The foundation deformation measurement method comprises the following steps: Obtain image data of preset benchmarks at each monitoring point in the foundation; Processing the image data to obtain a contour model of the preset reference object; Determining a foundation deformation value based on the contour model of the preset benchmark object and a standard contour model corresponding to the preset benchmark object; The step of determining the foundation deformation value based on the contour model of the preset benchmark object and the standard contour model corresponding to the preset benchmark object includes: When the center point of the contour model coincides with the center point of the standard contour model, obtaining an area in the standard contour model that does not coincide with the contour model; Performing color value extraction processing on the pixel points in the non-overlapping area to obtain the RGB color value of each pixel point in the non-overlapping area; Performing mean clustering on the RGB color value of each pixel, and determining the deformation correlation coefficient according to the clustering result; The foundation deformation value is determined based on the area of ​​the region in the standard contour model that does not overlap with the contour model and the deformation correlation coefficient, wherein the deformation correlation coefficient is obtained by querying the clustering result-deformation correlation coefficient table.

2. The method for measuring foundation deformation according to claim 1, wherein: The standard contour model includes a plurality of first feature points, the contour model includes a plurality of second feature points, the first feature points correspond to the second feature points, and the step of determining the foundation deformation value based on the contour model of the preset benchmark object and the standard contour model corresponding to the preset benchmark object includes: When the center point of the contour model coincides with the center point of the standard contour model, calculating the distance between the first feature point and its corresponding second feature point to obtain a plurality of distance differences; Determining a deformation value of each monitoring point based on the plurality of distance differences; The foundation deformation value is determined based on the deformation value of each monitoring point.

3. The method for measuring foundation deformation according to claim 2, wherein: The step of determining the deformation value of each monitoring point based on the plurality of distance differences includes: Classifying the distance differences according to the orientation information of the first feature point / the second feature point corresponding to the distance differences to obtain a horizontal distance difference and a vertical distance difference; Calculating the average value of the horizontal distance difference to determine the horizontal deformation value of each monitoring point; Calculating the average value of the distance difference in the vertical direction to determine the deformation value in the vertical direction of each monitoring point; The deformation value of each monitoring point is determined based on the deformation value of each monitoring point in the horizontal direction and the deformation value of each monitoring point in the vertical direction.

4. The method for measuring foundation deformation according to claim 2, wherein: The step of determining the foundation deformation value based on the deformation value of each monitoring point includes: fitting a foundation deformation surface according to the deformation values ​​of each monitoring point and the position information of each monitoring point; The foundation deformation surface is compared with the foundation deformation surface of the previous time series to determine the foundation deformation value.

5. The method for measuring foundation deformation according to claim 1, wherein: Before the step of processing the image data to obtain the contour model of the preset reference object, the method further includes: performing correction processing on the image data to obtain corrected image data; The step of processing the image data to obtain the contour model of the preset reference object includes: The corrected image data is processed to obtain a contour model of the preset reference object.

6. A foundation deformation measuring device, characterized in that: The foundation deformation measuring device comprises: A data acquisition module is used to obtain image data of preset benchmarks at each monitoring point in the foundation; An image processing module, configured to process the image data to obtain a contour model of the preset reference object; a deformation determination module, configured to determine a foundation deformation value based on a contour model of the preset benchmark object and a standard contour model corresponding to the preset benchmark object; The deformation determination module is specifically used to obtain the area in the standard contour model that does not overlap with the contour model when the center point of the contour model coincides with the center point of the standard contour model; perform color value extraction processing on the pixel points in the non-overlapping area to obtain the RGB color value of each pixel point in the non-overlapping area; perform mean clustering on the RGB color value of each pixel point, determine the deformation correlation coefficient according to the clustering result, and determine the foundation deformation value based on the area of ​​the area in the standard contour model that does not overlap with the contour model and the deformation correlation coefficient, wherein the deformation correlation coefficient is obtained by querying the clustering result-deformation correlation coefficient table.

7. A ground deformation measurement device, characterized in that: The device includes: a memory, a processor, and a foundation deformation measurement program stored in the memory and executable on the processor, wherein the foundation deformation measurement program is configured to implement the steps of the foundation deformation measurement method according to any one of claims 1 to 5.

8. A storage medium, characterized in that: The storage medium stores a foundation deformation measurement program, which, when executed by a processor, implements the steps of the foundation deformation measurement method according to any one of claims 1 to 5.

Images