A device and method for generating a rockfill material grading curve based on a compacted warehouse surface image

Abstract

The application discloses a kind of based on compaction yard face image's rockfill material grading curve generation device and method, its method includes: obtaining the image of rockfill material compaction yard face, and pre-processing to image;Obtain the contour of particle in image;Ray is generated in image, whether the line segment formed in the contour of particle of ray reaches setting value, if yes, then the frequency distribution of line segment length is counted if no, then the number of generated ray is increased and the step is repeated;Rockfill material grading function of fractal distribution is used to construct line segment length distribution theoretical solution P 1D (L);The frequency distribution of line segment length is fitted by line segment length distribution theoretical solution P 1D (L) corresponding grading parameter is obtained;Rockfill material grading curve is constructed based on grading parameter;The application can reduce the economic and time cost of obtaining rockfill material grading curve.

Description

TECHNICAL FIELD

[0001] The present application relates to a kind of based on compaction warehouse surface image's rockfill material grading curve generation device and method, belong to water conservancy technical field. BACKGROUND

[0002] Earth-rock dam is one of the main dam types in the development of water resources in China, and its construction and safety and stability are closely related to the grading curve of dam material. The internal filling of rockfill material with excellent grading curve is sufficient, and it usually shows high density and deformation modulus. On the contrary, the rockfill material with poor grading has poor internal particle filling, and not only the density and modulus cannot meet the design requirements of earth-rock dam, but also it is easy to cause dam material penetration failure under the condition of water head gradient. Therefore, the design stage of earth-rock dam needs to give the upper and lower envelope lines of the grading of rockfill material used for dam construction, and ensure that the grading of rockfill material meets the design requirements combined with the tracking detection in the construction stage.

[0003] At present, the main method of on-site grading detection of earth-rock dam is through sieve analysis test, that is, the rockfill material in a certain area of the compaction warehouse surface is sieved and weighed to determine the mass of each particle size component. Although the grading curve detected by the on-site sieve analysis method has high accuracy, it has the following limitations: (1) the on-site sieve analysis test needs to be sieved manually by on-site test personnel, which is not consistent with the current situation of mechanical construction of earth-rock dam, and the delay of sieve analysis test will affect the overall filling construction progress of the dam; (2) due to the high cost of test time and labor, the on-site detection of the dam can only detect the grading of a few test points of dam material, and cannot reflect the overall grading of the rockfill material in the warehouse surface.

[0004] In order to solve the above problems, the present application provides a kind of based on compaction warehouse surface image's rockfill material grading curve generation device and method. SUMMARY

[0005] The present application aims to overcome the deficiencies in the prior art, and provides a kind of based on compaction warehouse surface image's rockfill material grading curve generation device and method, solves the technical problems of high economic and time cost in prior art.

[0006] To achieve the above-mentioned purpose, the present application is realized by using the following technical scheme:

[0007] In the first aspect, the present application provides a kind of based on compaction warehouse surface image's rockfill material grading curve generation method, comprising:

[0008] obtaining the image of the rockfill material compaction warehouse surface, and pre-processing the image;

[0009] obtaining the contour of the particle in the image;

[0010] generating rays in the image, judging whether a line segment formed by the rays in the contour of the particle reaches a set value, if yes, counting a frequency distribution of the length of the line segment if no, increasing the number of the generated rays and repeating the step;

[0011] adopting a fractal distribution of the rockfill material grading function to construct a theoretical solution P of the line segment length distribution 1D (L);

[0012] fitting the frequency distribution of the line segment length by the theoretical solution P of the line segment length distribution 1D (L) obtaining corresponding grading parameters;

[0013] constructing a rockfill material grading curve based on the grading parameters.

[0014] Preferably, the image of the compacted rockfill surface is obtained by:

[0015] acquisition time: after the paving is completed and before the rolling starts;

[0016] acquisition device: a camera arranged above the compacted surface;

[0017] acquisition method: the length and width of the shooting area are both greater than 5 times the maximum particle size of the rockfill material, and the normal of the shooting angle is less than 10° from the normal of the compacted surface.

[0018] Preferably, the pre-processing of the image comprises:

[0019] adopting Otsu gray threshold for binary processing;

[0020] adopting image perspective distortion for image correction processing, which comprises dividing the image into at least 3*3 nine regions, arranging a square object with a particle size of 2 times the maximum particle size of the rockfill material at the center of each region, and correcting by a bilinear correction method.

[0021] Preferably, the generating rays in the image comprises:

[0022] generating rays arranged in a vertical and horizontal staggered manner in the image, the rays dividing the image into M*N parts, the values of M and N maintaining a proportional relationship with the pixel size of the image, and the expression being M / N=L / B, wherein L and B are the pixel sizes of the length and width of the image, respectively.

[0023] Preferably, the counting the frequency distribution of the length of the line segment The expression is as follows:

[0024]

[0025] Wherein, L represents the length of the line segment, S(L) represents the number of line segments in the preset length interval in which the line segment length L is located in the particle, and S represents the total number of line segments.

[0026] Preferably, the rockfill material grading function constructed by using the fractal distribution is used to construct a theoretical solution P 1D (L) of the frequency distribution of the length of the line segment, and the expression is as follows:

[0027]

[0028] Wherein, L represents the length of the line segment, D represents the fractal dimension of the rockfill material grading, d M and d m respectively represent the maximum and minimum particle sizes of the rockfill material.

[0029] Preferably, the frequency distribution of the length of the line segment is fitted by using the theoretical solution P 1D (L) of the length of the line segment. The corresponding grading parameters include:

[0030] Based on the least square method, the fractal dimension D, the maximum particle size d M and the minimum particle size d m of the rockfill material are obtained.

[0031] Preferably, the rockfill material grading curve is constructed based on the grading parameters, and the expression is as follows:

[0032]

[0033] Wherein, d represents the particle size of the rockfill material, M(d) is the mass percentage of the particles less than the particle size d, d M and d m respectively represent the maximum and minimum particle sizes of the rockfill material, and D represents the fractal dimension of the rockfill material grading.

[0034] In the second aspect, the present application provides a rockfill material grading curve generation device based on a compacted warehouse surface image, comprising a processor and a storage medium.

[0035] The storage medium is used to store instructions.

[0036] The processor is used to operate according to the instructions to perform the steps of the method according to any one of the above.

[0037] Compared with the prior art, the present application has the following beneficial effects:

[0038] The application provides a kind of based on compaction stockpile surface image's rockfill material gradation curve generation device and method, the apparent image of rockfill material compaction stockpile surface is determined in real time to reduce the economic and time cost of obtaining rockfill material gradation curve;And, the quantitative relationship of line segment and gradation is established by generating ray cutting to determine the gradation curve of rockfill material, reduces the requirement of boundary extraction to the apparent image of rockfill material. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 It is a kind of based on compaction stockpile surface image's rockfill material gradation curve generation method flow chart provided in the embodiment of the application;

[0040] Figure 2 It is the schematic diagram after pre-processing of image provided in the embodiment of the application;

[0041] Figure 3 It is the schematic diagram of generating ray in image provided in the embodiment of the application;

[0042] Figure 4 It is the frequency distribution histogram of line segment length provided in the embodiment of the application;

[0043] Figure 5 It is the line segment length fitting schematic diagram provided in the embodiment of the application;

[0044] Figure 6 It is the rockfill material gradation curve schematic diagram provided in the embodiment of the application. DETAILED DESCRIPTION

[0045] The application will be further described below in conjunction with the drawings.The following embodiments are only used to more clearly illustrate the technical solutions of the application, and cannot limit the protection scope of the application.

[0046] Embodiment one:

[0047] As shown in Figure 1 The embodiment provides a kind of based on compaction stockpile surface image's rockfill material gradation curve generation method, comprising the following steps:

[0048] Step 1, obtain the image of rockfill material compaction stockpile surface, and pre-process image;

[0049] Step 2, obtain the contour of particle in image;

[0050] Step 3, generate ray in image, judge whether the line segment formed by ray in the contour of particle reaches set value, if yes, then the frequency distribution of line segment length is counted If not, increase the number of generated rays and repeat the step;

[0051] Step 4, the theoretical solution P of the line segment length distribution is constructed by using the fractal distribution of the rockfill material gradation function 1D (L);

[0052] Step 5, the frequency distribution of the line segment length is fitted by using the theoretical solution P of the line segment length distribution 1D (L); The corresponding gradation parameters are obtained;

[0053] Step 6, the rockfill material gradation curve is constructed based on the gradation parameters.

[0054] Wherein:

[0055] (1) The image of the rockfill material compaction surface is obtained, which satisfies:

[0056] Acquisition time: after the material is laid, before the compaction starts;

[0057] Acquisition device: a camera arranged above the compaction surface;

[0058] Acquisition method: the length and width of the shooting area are both greater than 5 times the maximum particle size of the rockfill material, and the normal of the shooting angle is less than 10° from the normal of the compaction surface;

[0059] Usually, an unmanned aerial vehicle is suspended at a certain height from the compaction surface.

[0060] In this embodiment, the image parameter acquisition of the rockfill material is obtained by using DJI Mavic2, and the main parameters of the camera are: 12 million pixels, 1 / 2.3” CMOS sensor, the unmanned aerial vehicle is suspended at a height of 5.0 m from the ground during image acquisition, the lens is in the 2x optical zoom section, and the normal of the lens shooting angle is less than 10° from the normal of the compaction surface.

[0061] (2) The image is preprocessed, including:

[0062] Otsu gray threshold is used for binaryzation processing;

[0063] Image perspective distortion is used for image correction processing, which includes dividing the image into at least 3*3 nine regions, arranging a square object with a particle size of 2 times the maximum particle size of the rockfill material at the center of each region, and correcting by using the bilinear correction method.

[0064] In this embodiment, the surface image is divided into 5*4 20 regions, a 2m*2m square plate is arranged at the center of each region for correction, and the bilinear correction method is used for internal correction of each region. The subsequent images of the surface are corrected by using this set of correction coefficients. As Figure 2 shown is the result of binaryzation processing by using the Otsu gray threshold method. Note Figure 2The binarization process does not require extracting all particle boundaries; it only needs to distinguish most of the particle boundary contours.

[0065] (3) Generating rays in an image includes:

[0066] Generate crisscrossing rays in the image, such as Figure 3 As shown, the ray divides the image into M×N parts. The values ​​of M and N are proportional to the pixel size of the image, and the expression is M / N = L / B, where L and B are the pixel sizes of the length and width of the image, respectively.

[0067] In this embodiment, the image acquired by the UAV has a pixel size of 4000*3000. Rays generated on the binarized image are arranged in a crisscross pattern, dividing the image's pixel size into 80*60 parts. These rays intersect with the boundaries of particles, dividing the rays into several line segments. The total number of line segments formed by these rays is calculated to be 6673, which meets the requirement of being greater than 3000. The frequency distribution P of the lengths of these line segments is statistically analyzed. 1D (L), Figure 4 This is a histogram showing the frequency distribution of the above line segments.

[0068] (4) Frequency distribution of statistical line segment length Its expression is as follows:

[0069]

[0070] Where L represents the length of the line segment, S(L) represents the number of line segments within the preset length range where the length L of the line segment in the particle is located, and S represents the total number of line segments. Under normal circumstances, the total number of line segments S is greater than 3000.

[0071] (5) Using the fractal distribution of the riprap gradation function, a theoretical solution for the line segment length distribution P is constructed. 1D (L), whose expression is as follows:

[0072]

[0073] Where L represents the line segment length, D represents the fractal dimension of the gradation of the riprap, and d M and d m These represent the maximum and minimum particle sizes of the riprap, respectively.

[0074] (6) Solve P using the line segment length distribution theory 1D (L) Frequency distribution of fitted line segment length The corresponding gradation parameters include:

[0075] like Figure 5 As shown, based on the least squares method for fitting, the fractal dimension D and the maximum particle size d of the riprap are obtained. M, the minimum particle size d m .

[0076] (7) The graded rock material grading curve is constructed based on the grading parameters, as shown in FIG. 7, and the expression is as follows: Figure 6

[0077]

[0078] wherein d represents the particle size of the graded rock material, M(d) is the mass percentage of the particles less than the particle size d, d M and d m respectively represent the maximum and minimum particle size of the graded rock material, and D represents the fractal dimension of the graded rock material.

[0079] Example Two:

[0080] The embodiment provides a graded rock material grading curve generation device based on a compacted warehouse surface image, including a processor and a storage medium.

[0081] The storage medium is used for storing instructions.

[0082] The processor is used for operating according to the instructions to execute the steps of the method according to the embodiment one.

[0083] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0084] The present application is described with reference to the flowcharts and / or block diagrams according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices produce a device for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows or one or more blocks. Figure 1 The device for implementing the functions specified in one or more flows or one or more blocks.

[0085] ​These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flow Figure 1 The flow or flows and / or blocks Figure 1 The flow or flows and / or blocks

[0086] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions that execute on the computer or other programmable apparatus provide steps for implementing the flow Figure 1 The flow or flows and / or blocks Figure 1 The flow or flows and / or blocks

[0087] The above description is only preferred embodiments of the present application, it should be pointed out that for those skilled in the art, without departing from the technical principles of the present application, a number of improvements and modifications can be made, these improvements and modifications should also be considered as the protection scope of the present application.

Claims

1. A method for generating a rockfill material grading curve based on a compacted surface image, characterized in that, The method comprises: acquiring an image of a rockfill material compacted surface and pre-processing the image; acquiring the contour of a particle in the image; generating rays in the image, determining whether a line segment formed by the rays within the contour of the particle reaches a set value, if so, counting a frequency distribution of the length of the line segment if not, increasing the number of generated rays and repeating the step A theoretical solution P of the length distribution of line segments is constructed using a fractal distribution of the rockfill material gradation function 1D (L); Solving P by the theory of line segment length distribution 1D (L) Fitting the frequency distribution of line segment length Obtaining the corresponding grading parameters; constructing a rockfill material grading curve based on grading parameters; The frequency distribution of the length of the statistical line segment The expression is as follows: wherein L represents the length of a line segment, S(L) represents the number of line segments with a length L within a preset length interval, and S represents the total number of line segments; The rockfill material gradation function with fractal distribution constructs a theoretical solution P of line segment length distribution 1D (L), which is expressed as follows: wherein L represents a length of a line segment, D represents a fractal dimension of the rockfill material gradation, d M and d m respectively represent a maximum and a minimum particle size of the rockfill material; The solution P by the distribution of line segment lengths 1D (L) Frequency distribution of the fitted line segment lengths The corresponding grading parameters are obtained, comprising: Based on the least square method, the values of the fractal dimension D, the maximum particle size d M of the rockfill material and the minimum particle size d m are obtained.

2. The method for generating rockfill material grading curve based on rolling warehouse surface image according to claim 1, characterized in that, the acquisition of the image of the rockfill material compacted surface satisfies: acquisition time: after the completion of material paving and before the start of rolling; acquisition equipment: a camera arranged above the compacted surface; acquisition method: the length and width of the shooting area are both greater than 5 times the maximum particle size of the rockfill material, and the normal of the shooting angle is less than 10° from the normal of the compacted surface.

3. The method for generating rockfill material grading curve based on rolling warehouse surface image according to claim 1, characterized in that, the pre-processing of the image comprises: Otsu grayscale thresholding for binary processing; image correction using image perspective distortion, which includes dividing the image into at least 3*3 nine regions, arranging a square object with a particle size of 2 times the maximum particle size of the rockfill material at the center of each region, and correcting by bilinear correction method.

4. The method for generating rockfill material grading curve based on rolling warehouse surface image according to claim 1, characterized in that, the generation of rays in the image comprises: generating rays arranged in a longitudinal and horizontal staggered manner in the image, the rays dividing the image into M*N parts, the values of M and N maintaining a proportional relationship with the pixel size of the image, and the expression being M / N=L / B, wherein L and B are the pixel sizes of the length and width of the image, respectively.

5. The method for generating rockfill material grading curve based on rolling warehouse surface image according to claim 1, characterized in that, the construction of the rockfill material grading curve based on grading parameters, the expression being: where d represents the particle size of the rockfill material, M(d) is the mass percentage of the particles smaller than the particle size d, d M and d m respectively represent the maximum and minimum particle size of the rockfill material, and D represents the fractal dimension of the rockfill material gradation.

6. A device for generating a rockfill material grading curve based on a compacted surface image, characterized by a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to perform the steps of the method according to any one of claims 1-5.

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