CN111007067A - Automatic identification method and system for rock mass structural plane - Google Patents
Automatic identification method and system for rock mass structural plane Download PDFInfo
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- CN111007067A CN111007067A CN201911421778.9A CN201911421778A CN111007067A CN 111007067 A CN111007067 A CN 111007067A CN 201911421778 A CN201911421778 A CN 201911421778A CN 111007067 A CN111007067 A CN 111007067A
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Abstract
The invention provides an automatic identification method and system for a rock mass structural plane. The automatic identification method of the rock mass structural plane comprises the steps of matching and fusing three-dimensional laser point cloud data and a panoramic two-dimensional image, and enabling all pixel points in the panoramic two-dimensional image to correspond to corresponding three-dimensional coordinates of the three-dimensional laser point cloud data one by one; extracting a structural surface trace in the panoramic two-dimensional image, and identifying a corresponding three-dimensional structural surface trace in the three-dimensional laser point cloud data according to the corresponding relation of coordinates so as to obtain the length of the three-dimensional structural surface trace; predicting the diameter range of the structural surface disc according to the probability distribution relation between the diameter of the structural surface disc and the trace length of the three-dimensional structural surface; and fitting the structural plane disc by using a three-dimensional structural plane trace in the three-dimensional laser point cloud data to ensure that the sum of the distances between all points on the structural plane trace and the structural plane disc is minimum, and finally judging that the plane where the fitted structural plane disc is located is a rock mass structural plane, wherein the diameter range of the rock mass structural plane is the same as that of the structural plane disc.
Description
Technical Field
The invention belongs to the field of automatic identification of rock mass structural planes, and particularly relates to an automatic identification method and system of a rock mass structural plane.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The inventor finds that the traditional rock mass structure method can only identify rock fractures in a two-dimensional image, does not consider the combination of three-dimensional point cloud data and panoramic image data and the relation between the diameter of a structural surface and the length of a structural surface trace, and defaults to wireless extension of the structural surface; and the influence of construction site light is large, and shadow generated by rock protrusion has large influence on automatic identification, so that the identification accuracy is low.
Disclosure of Invention
In order to solve the above problems, a first aspect of the present invention provides a method for automatically identifying a rock mass structural plane, which combines three-dimensional point cloud data and panoramic image data and considers the relationship between the diameter of the structural plane and the length of the structural plane trace to improve the accuracy of identifying the rock mass structural plane.
In order to achieve the purpose, the invention adopts the following technical scheme:
an automatic identification method for rock mass structural plane comprises the following steps:
receiving a panoramic two-dimensional image and three-dimensional laser point cloud data around a rock mass structure;
matching and fusing the three-dimensional laser point cloud data and the panoramic two-dimensional image to enable all pixel points in the panoramic two-dimensional image to correspond to the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data one by one;
extracting a structural surface trace in the panoramic two-dimensional image, and identifying a corresponding three-dimensional structural surface trace in the three-dimensional laser point cloud data according to the corresponding relation of coordinates so as to obtain the length of the three-dimensional structural surface trace;
predicting the diameter range of the structural surface disc according to the probability distribution relation between the diameter of the structural surface disc and the trace length of the three-dimensional structural surface;
and fitting the structural plane disc by using a three-dimensional structural plane trace in the three-dimensional laser point cloud data to ensure that the sum of the distances between all points on the structural plane trace and the structural plane disc is minimum, and finally judging that the plane where the fitted structural plane disc is located is a rock mass structural plane, wherein the diameter range of the rock mass structural plane is the same as that of the structural plane disc.
In order to solve the above problems, a second aspect of the present invention provides an automatic identification system for a rock mass structural plane, which combines three-dimensional point cloud data and panoramic image data and considers the relationship between the diameter of the structural plane and the length of the structural plane trace to improve the identification accuracy of the rock mass structural plane.
In order to achieve the purpose, the invention adopts the following technical scheme:
an automatic identification system for rock mass structural planes, comprising:
the data receiving module is used for receiving the panoramic two-dimensional image and the three-dimensional laser point cloud data around the rock mass structure;
the coordinate matching module is used for matching and fusing the three-dimensional laser point cloud data and the panoramic two-dimensional image so that all pixel points in the panoramic two-dimensional image correspond to the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data one by one;
the structure surface trace identification module is used for extracting a structure surface trace in the panoramic two-dimensional image, identifying a corresponding three-dimensional structure surface trace in the three-dimensional laser point cloud data according to the corresponding relation of the coordinates, and further obtaining the length of the three-dimensional structure surface trace;
the structure surface disc diameter prediction module is used for predicting the diameter range of the structure surface disc according to the probability distribution relation between the diameter of the structure surface disc and the trace length of the three-dimensional structure surface;
and the rock mass structural plane determining module is used for fitting the structural plane disc by utilizing a three-dimensional structural plane trace in the three-dimensional laser point cloud data, so that the sum of the distances between all points on the structural plane trace and the structural plane disc is minimum, and finally, the plane where the fitted structural plane disc is located is judged to be the rock mass structural plane, and the diameter range of the rock mass structural plane is the same as that of the structural plane disc.
A third aspect of the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the method of automatic identification of a rock mass structural plane as described above.
A fourth aspect of the present invention provides a computer device, comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor executes the program to implement the steps of the automatic rock mass structural plane identification method as described above.
The invention has the beneficial effects that:
(1) according to the method, based on the one-to-one correspondence of all pixel points in the panoramic two-dimensional image and the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data, the three-dimensional point cloud data and the panoramic two-dimensional image data are combined to automatically identify the rock mass structure by means of the coordinate correspondence, the corresponding three-dimensional structure surface trace in the three-dimensional laser point cloud data can be prepared to be identified, the diameter of the structure surface is predicted according to the probability distribution relationship between the diameter of the structural surface disc and the length of the three-dimensional structure surface trace, and the identified rock mass structure surface is more accurate.
(2) The method can acquire the three-dimensional shape of the automatic rock fracture so as to acquire the attitude of the structural plane; the interference of shadow can be eliminated, so that the accuracy of rock mass structure identification is greatly improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a flow chart of an automatic identification method of a rock mass structural plane provided by an embodiment of the invention;
FIG. 2(a) is a two-dimensional pixel information provided by an embodiment of the present invention;
fig. 2(b) is three-dimensional laser point cloud data consistent with two-dimensional pixel information coordinates provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram of a spherical projection of a two-dimensional image according to an embodiment of the present invention;
fig. 4 is a schematic diagram illustrating fusion of image data and laser point cloud data according to an embodiment of the present invention;
FIG. 5 shows an edge detection result according to an embodiment of the present invention;
FIG. 6 is a relationship between the diameter of a structured surface disk and the length of a structured surface trace according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an automatic identification system for a rock mass structural plane according to an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Fig. 1 is a flow chart of an automatic identification method of a rock mass structural plane provided by an embodiment of the invention.
As shown in fig. 1, the method for automatically identifying a rock mass structural plane of the embodiment includes:
s101: and receiving the panoramic two-dimensional image and the three-dimensional laser point cloud data around the rock mass structure.
Specifically, a side slope, a tunnel face and a side wall around a rock mass structure are shot through a panoramic camera to obtain a panoramic two-dimensional image; and obtaining three-dimensional laser point cloud data by using a coaxial laser scanning device for panoramic photography.
S102: and matching and fusing the three-dimensional laser point cloud data and the panoramic two-dimensional image to enable all pixel points in the panoramic two-dimensional image to correspond to the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data one by one.
In the process of obtaining rock mass structure information, two-dimensional pixel information and three-dimensional laser point cloud data are directly and coaxially obtained, the pixel information is subjected to spherical projection, pixel point RGB information at the same angle is directly given to a three-dimensional laser point to be directly spliced, measurement errors generated by a traditional method based on feature point registration or manual registration based on a reflector method are avoided, and calculation steps are simplified.
As shown in fig. 2(a) and 2(B), assuming that the x-axis of the local coordinate system of the uniform pixel information is a regular n-polygon, the y-axis is half of a regular m-polygon, the image width is w, the height is u, the coordinate of one point B in the trajectory image of the rock mass structure identified by the two-dimensional rock mass structure is (x, y), the coordinate of a projection point B' (R, α, R) in the coordinate system with the radius of a projection sphere is R, and the chord length is a, as shown in fig. 3, there are:
2πR＝nw (1)
πR＝mu (2)
and theta is a spherical projection included angle of the two-dimensional image.
From the trigonometric cosine theorem we can obtain:
in the same way, the method for preparing the composite material,
after the projection transformation, the pseudo three-dimensional coordinate system of the pixel data is changed into a smooth spherical coordinate system.
In the three-dimensional laser point cloud data, assuming that the coordinates of a point M in the point cloud data are (x ', y', z '), the coordinates of a point M' in the corresponding spherical coordinate system are (r, α ', β'), where:
because the spherical coordinate system of the pixel data and the spherical coordinate system of the three-dimensional laser point cloud data have a common origin and the coordinate axes are in the same direction, any point coordinate in the pixel data has a coordinate and only one coordinate in the three-dimensional laser point cloud data corresponds to the coordinate. The RGB values in the pixel data and the space coordinate values in the three-dimensional laser point cloud data are butted under an angular bridge, so that the fusion of the pixel data and the three-dimensional laser point cloud data is realized, a two-dimensional rock mass structure trace is endowed with three-dimensional characteristics, the three-dimensional rock mass structure identification is realized, and meanwhile, a high-precision true-color three-dimensional face surface and side wall model is constructed. Taking the slope of the riple high-speed reconstruction and extension project as an example, as shown in fig. 4, the data obtained by photogrammetry is fused with the three-dimensional laser scanning data, and a high-precision true color point cloud model is established.
S103: and extracting a structural surface trace in the panoramic two-dimensional image, and identifying a corresponding three-dimensional structural surface trace in the three-dimensional laser point cloud data according to the corresponding relation of the coordinates so as to obtain the length of the three-dimensional structural surface trace.
The rock mass structure information is mostly represented in the data image as a part with intense local intensity change of the image. And (3) performing edge detection on the digital image, and detecting an area in the digital image, which has gentle gray scale change in a certain direction but severe change in a direction perpendicular to the area, so that automatic detection of rock mass structure information can be realized to a certain extent. After image binarization, denoising and image gradient domain significance optimization processing, the rock structure information is extracted by using an edge detection algorithm, so that the detection precision can be effectively improved. Common edge detection operators include Canny, Sobel, LoG, Prewitt and the like, but different operators have different noise sensitivity degrees, and have larger difference in edge detection and positioning accuracy when facing a tunnel environment. And selecting a Canny operator for edge detection after multiple tests and comparisons.
In specific implementation, the process of extracting the structural plane trace in the panoramic two-dimensional image is as follows:
and (3) selecting a Canny operator to detect the edge of the rock mass structure in the panoramic two-dimensional image, and fitting the extracted edge into a straight line through Hough transform to form a linear structural plane trace, as shown in figure 5.
In a specific implementation, the three-dimensional structure surface trace length is calculated according to the distance between two end points of the three-dimensional structure surface line.
The traditional geological logging method is a window measuring method, a line measuring method or a half line measuring method for counting the trace length of a rock mass structural plane, and only the trace length can be estimated. In addition, the structural surface trace length estimated by the method does not consider three-dimensional factors, and only the structural surface trace length on a certain projection plane is estimated. By adopting the method for calculating the trace length of the structural surface based on the true color three-dimensional laser point cloud model, the linear distance between two points in the three-dimensional space of the trace of the structural surface is directly calculated to be used as the trace length of the structural surface, and the result is more accurate.
In the practical application process, two end points of one trace are directly selected by the mouse, and the selection of the two end points can cause inaccurate results. In order to reduce the selection error, two end points are selected from the two-dimensional structure surface trace by means of automatic identification in the two-dimensional true color image data, the two-dimensional true color image data and the three-dimensional laser point cloud data are converted into three-dimensional points by means of the fusion method, and the selection precision can be effectively improved.
Let the coordinates of two end points of the structural surface trace in the three-dimensional space be (x)1,y1,z1),(x2,y2,z2) Then the structure trace length l is:
s104: and predicting the diameter range of the structural surface disc according to the probability distribution relation between the diameter of the structural surface disc and the trace length of the three-dimensional structural surface.
Structural face disks exist in rock masses, and the shapes of the structural face disks change along with the structural face disks when the rock masses are destroyed, so that the real diameters of the structural face disks in the rock masses cannot be actually measured. In most rock mass structure researches based on the block theory, the diameter of a structural plane disc is supposed to be infinitely extended and is inconsistent with the actual engineering condition. The embodiment provides a probability distribution model of the trace length and the diameter of the structural surface, which is used for predicting the extension scale of the structural surface with the known trace length and improving the accuracy of the description of the structural surface.
The structural surface trace can be regarded as the cutting of the structural surface disc by the construction excavation surface and is the intersection line of the two planes of the construction excavation surface and the structural surface disc. The structural plane occurrence is possibly distributed according to a certain rule, the construction excavation surface is generated along with the construction progress, but the circle centers of the structural plane disks are randomly distributed in the rock mass, so that the structural plane trace is generated by randomly cutting the structural plane disks by a straight line.
Let the disk in fig. 6 be a structural plane disk with a diameter D. A straight line AB randomly cuts the disc, and both ends A, B of the straight line are considered to be on the edge of the disc, and both ends move randomly. When one end point A is fixed and the other end point B moves randomly at the edge of the disc, the probability distribution is the same as that when both end points move randomly. And because the probability that the randomly moving endpoint B falls on each position of the circle is the same, the endpoint B can be regarded as performing uniform circular motion with the speed omega on the circle, the motion time is t, and the AB length is l. Equations (12) to (19) are the probability density function solving process of the length and diameter of the structural trace.
According to the trigonometric function relationship, it can be obtained:
substituting equation (12) into equation (14) yields:
the conditional probability density function is then:
because the structural plane disc diameter D is constantly greater than zero, the actual probability density is:
the probability that the full trace length is greater than l is:
the diameter probability density function is:
substituting the probability density function of the formula (19) into MATLAB to carry out one million times of random simulation, setting the diameter of the structural plane disc to be 2, and averagely dividing the length of the generated trace into ten groups according to 0-2 to carry out statistics, which is shown in Table 1.
TABLE 1 Long probability distribution chart of structural surface trace
From the table analysis, it is known that there is a clear probability distribution relationship between the diameter of the structural plane and the trace length, and the probability is higher as the trace length is closer to the diameter of the structural plane disk. When the diameter of the structural surface is approximately equal to the trace length, the probability is 0.19; and the probability is almost 0 when the diameter of the structural surface is more than 10 times of the length of the track. When the structure surface trace length l and the structure surface disc diameter D have the relationship of the formula (20) and the formula (21):
p(l≤D≤3l)＝0.99 (20)
p(l≤D≤10l)＝0.01 (21)
in practical engineering applications, the diameter D of the structured surface disk can be considered to be one to ten times the structure track length l, and substantially one to three times the structure track length l.
S105: and fitting the structural plane disc by using a three-dimensional structural plane trace in the three-dimensional laser point cloud data to ensure that the sum of the distances between all points on the structural plane trace and the structural plane disc is minimum, and finally judging that the plane where the fitted structural plane disc is located is a rock mass structural plane, wherein the diameter range of the rock mass structural plane is the same as that of the structural plane disc.
The three-dimensional attitude of the structural plane cannot be obtained by traditional geological sketch, but the true color three-dimensional laser point cloud data can truly reflect the three-dimensional characteristics of the rock mass structure, so that the attitude analysis of the structural plane is carried out. From the foregoing, the structure surface is assumed to be a circular disk, and the three-dimensional equation of the plane where the circular disk is located is determined, so that the attitude of the structure surface can be obtained. In engineering practice, the excavation free face cannot be a complete plane, so that the structure face trace disclosed by the excavation free face is not a straight line or a line segment, but a curve line segment with three-dimensional characteristics. The plane of the structural plane can be fitted according to the three-dimensional characteristics of the structural plane trace, the plane three-dimensional equation is calculated, and the extraction of the structural plane attitude is realized through conversion.
And selecting two end points of the structural plane trace and any point between the two end points to obtain a plane three-dimensional equation and realize the estimation of the attitude of the structural plane. However, in practical engineering, since the structural surface is rough, the opening degree is uneven, and the structural surface has a certain undulation degree, and only three points are used to fit a plane, a large model reconstruction error is caused. Selecting a plurality of points (x) comprising a head point and a tail point on a structural plane tracei,yi,zi) And i is 1,2, …, n, and the error is eliminated by adopting a robust characteristic value method to realize the fitting of the plane where the structural plane is located. The procedure for fitting the robust eigenvalue method to the plane is shown in equations (22) to (29).
The equation of the plane of the structural surface is as follows:
ax+by+cz＝d (22)
wherein, a2+b2+c21, and d is more than or equal to 0; a. b, c and d are all fitting coefficients.
The distance from the point to the plane of the structural plane is as follows:
di＝|axi+byi+czi-d| (23)
the best fit of the plane of the structural surface is that the sum K of the distances from all points to the plane of the structural surface is the smallest. And solving each parameter when the sum of the distances is minimum, namely the fitted optimal plane.
Using the lagrange multiplier method:
order to
x＝(a,b,c)T(26)
Then
Kmin＝λmin(28)
(A-λminI)x＝0 (29)
Wherein λ isminThe minimum eigenvalue of the matrix A is the corresponding eigenvector, i.e. the vector to be solved.
And the stable characteristic value method is applied to fit the plane, so that the error of plane reconstruction of the structural surface is reduced, and an accurate data basis is provided for subsequent block stability analysis.
For the plane equation ax + by + cz of the structural plane, d is the coordinate system of the right-hand orthogonal coordinate system with the x axis in the north direction, and z represents the elevation direction.
The structural surface trend line equation is as follows:
ax+by＝d (30)
since the trend line is perpendicular to the trend line, the trend line equation is:
ax-by＝e(31)
d and e are both constant coefficients.
The structural surface is inclined to form an included angle theta between the inclined line and the north direction (the x-axis direction) as follows:
the inclination angle delta of the structural surface is the included angle between the structural surface and the horizontal plane, and the value is as follows:
in the embodiment, based on the one-to-one correspondence of all pixel points in the panoramic two-dimensional image and the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data, the three-dimensional point cloud data and the panoramic two-dimensional image data are combined to automatically identify the rock mass structure by means of the coordinate corresponding relation, the corresponding three-dimensional structure surface trace in the three-dimensional laser point cloud data can be prepared to be identified, the diameter of the structure surface is predicted according to the probability distribution relation between the diameter of the structural surface disc and the length of the three-dimensional structure surface trace, and the identified rock mass structure surface is more accurate.
The three-dimensional form of the automatic rock fracture can be obtained, so that the structural plane attitude can be obtained; the interference of shadow can be eliminated, so that the accuracy of rock mass structure identification is greatly improved.
Example 2
As shown in fig. 7, the present embodiment provides an automatic identification system for a rock mass structural plane, which includes:
(1) the data receiving module is used for receiving the panoramic two-dimensional image and the three-dimensional laser point cloud data around the rock mass structure;
(2) the coordinate matching module is used for matching and fusing the three-dimensional laser point cloud data and the panoramic two-dimensional image so that all pixel points in the panoramic two-dimensional image correspond to the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data one by one;
(3) the structure surface trace identification module is used for extracting a structure surface trace in the panoramic two-dimensional image, identifying a corresponding three-dimensional structure surface trace in the three-dimensional laser point cloud data according to the corresponding relation of the coordinates, and further obtaining the length of the three-dimensional structure surface trace;
specifically, in the structural plane trace identification module, the process of extracting the structural plane trace in the panoramic two-dimensional image is as follows:
and (3) selecting a Canny operator to detect the edge of the rock mass structure in the panoramic two-dimensional image, and fitting the extracted edge into a straight line through Hough transform to form a linear structural plane trace.
In the structural surface trace identification module, the length of the three-dimensional structural surface trace is calculated according to the distance between two end points of the three-dimensional structural area line.
(4) The structure surface disc diameter prediction module is used for predicting the diameter range of the structure surface disc according to the probability distribution relation between the diameter of the structure surface disc and the trace length of the three-dimensional structure surface;
in the structural surface disc diameter prediction module, the probability distribution relation between the structural surface disc diameter and the three-dimensional structural surface trace length is as follows:
p(l≤D≤3l)＝0.99
p(l≤D≤10l)＝0.01
wherein D is the diameter of the structural plane disc; l is the three-dimensional structure surface trace length; p is the probability.
(5) And the rock mass structural plane determining module is used for fitting the structural plane disc by utilizing a three-dimensional structural plane trace in the three-dimensional laser point cloud data, so that the sum of the distances between all points on the structural plane trace and the structural plane disc is minimum, and finally, the plane where the fitted structural plane disc is located is judged to be the rock mass structural plane, and the diameter range of the rock mass structural plane is the same as that of the structural plane disc.
In the embodiment, based on the one-to-one correspondence of all pixel points in the panoramic two-dimensional image and the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data, the three-dimensional point cloud data and the panoramic two-dimensional image data are combined to automatically identify the rock mass structure by means of the coordinate corresponding relation, the corresponding three-dimensional structure surface trace in the three-dimensional laser point cloud data can be prepared to be identified, the diameter of the structure surface is predicted according to the probability distribution relation between the diameter of the structural surface disc and the length of the three-dimensional structure surface trace, and the identified rock mass structure surface is more accurate.
The three-dimensional form of the automatic rock fracture can be obtained, so that the structural plane attitude can be obtained; the interference of shadow can be eliminated, so that the accuracy of rock mass structure identification is greatly improved.
Example 3
The present embodiment provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor implements the steps in the method for automatic identification of a rock mass structural plane as shown in fig. 1.
In the embodiment, based on the one-to-one correspondence of all pixel points in the panoramic two-dimensional image and the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data, the three-dimensional point cloud data and the panoramic two-dimensional image data are combined to automatically identify the rock mass structure by means of the coordinate corresponding relation, the corresponding three-dimensional structure surface trace in the three-dimensional laser point cloud data can be prepared to be identified, the diameter of the structure surface is predicted according to the probability distribution relation between the diameter of the structural surface disc and the length of the three-dimensional structure surface trace, and the identified rock mass structure surface is more accurate.
The three-dimensional form of the automatic rock fracture can be obtained, so that the structural plane attitude can be obtained; the interference of shadow can be eliminated, so that the accuracy of rock mass structure identification is greatly improved.
Example 4
The embodiment provides a computer device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps in the automatic rock mass structural plane identification method shown in fig. 1.
In the embodiment, based on the one-to-one correspondence of all pixel points in the panoramic two-dimensional image and the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data, the three-dimensional point cloud data and the panoramic two-dimensional image data are combined to automatically identify the rock mass structure by means of the coordinate corresponding relation, the corresponding three-dimensional structure surface trace in the three-dimensional laser point cloud data can be prepared to be identified, the diameter of the structure surface is predicted according to the probability distribution relation between the diameter of the structural surface disc and the length of the three-dimensional structure surface trace, and the identified rock mass structure surface is more accurate.
The three-dimensional form of the automatic rock fracture can be obtained, so that the structural plane attitude can be obtained; the interference of shadow can be eliminated, so that the accuracy of rock mass structure identification is greatly improved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may 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 instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may 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 which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (10)
1. An automatic identification method for rock mass structural plane is characterized by comprising the following steps:
receiving a panoramic two-dimensional image and three-dimensional laser point cloud data around a rock mass structure;
matching and fusing the three-dimensional laser point cloud data and the panoramic two-dimensional image to enable all pixel points in the panoramic two-dimensional image to correspond to the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data one by one;
extracting a structural surface trace in the panoramic two-dimensional image, and identifying a corresponding three-dimensional structural surface trace in the three-dimensional laser point cloud data according to the corresponding relation of coordinates so as to obtain the length of the three-dimensional structural surface trace;
predicting the diameter range of the structural surface disc according to the probability distribution relation between the diameter of the structural surface disc and the trace length of the three-dimensional structural surface;
and fitting the structural plane disc by using a three-dimensional structural plane trace in the three-dimensional laser point cloud data to ensure that the sum of the distances between all points on the structural plane trace and the structural plane disc is minimum, and finally judging that the plane where the fitted structural plane disc is located is a rock mass structural plane, wherein the diameter range of the rock mass structural plane is the same as that of the structural plane disc.
2. The automatic identification method of the rock mass structural plane as claimed in claim 1, wherein the process of extracting the structural plane trace in the panoramic two-dimensional image is as follows:
and (3) selecting a Canny operator to detect the edge of the rock mass structure in the panoramic two-dimensional image, and fitting the extracted edge into a straight line through Hough transform to form a linear structural plane trace.
3. The automatic identification method of the rock mass structural plane as claimed in claim 1, characterized in that the length of the trace of the three-dimensional structural plane is calculated according to the distance between the two end points of the three-dimensional structural area line.
4. The automatic identification method of the rock mass structural plane as claimed in claim 1, wherein the probability distribution relation between the structural plane disc diameter and the three-dimensional structural plane trace length is as follows:
p(l≤D≤3l)＝0.99
p(l≤D≤10l)＝0.01
wherein D is the diameter of the structural plane disc; l is the three-dimensional structure surface trace length; p is the probability.
5. An automatic identification system for rock mass structural plane is characterized by comprising:
the data receiving module is used for receiving the panoramic two-dimensional image and the three-dimensional laser point cloud data around the rock mass structure;
the coordinate matching module is used for matching and fusing the three-dimensional laser point cloud data and the panoramic two-dimensional image so that all pixel points in the panoramic two-dimensional image correspond to the corresponding three-dimensional coordinates of the three-dimensional laser point cloud data one by one;
the structure surface trace identification module is used for extracting a structure surface trace in the panoramic two-dimensional image, identifying a corresponding three-dimensional structure surface trace in the three-dimensional laser point cloud data according to the corresponding relation of the coordinates, and further obtaining the length of the three-dimensional structure surface trace;
the structure surface disc diameter prediction module is used for predicting the diameter range of the structure surface disc according to the probability distribution relation between the diameter of the structure surface disc and the trace length of the three-dimensional structure surface;
and the rock mass structural plane determining module is used for fitting the structural plane disc by utilizing a three-dimensional structural plane trace in the three-dimensional laser point cloud data, so that the sum of the distances between all points on the structural plane trace and the structural plane disc is minimum, and finally, the plane where the fitted structural plane disc is located is judged to be the rock mass structural plane, and the diameter range of the rock mass structural plane is the same as that of the structural plane disc.
6. The automatic identification system of rock mass structural plane according to claim 5, characterized in that in the structural plane trace identification module, the process of extracting the structural plane trace in the panoramic two-dimensional image is as follows:
and (3) selecting a Canny operator to detect the edge of the rock mass structure in the panoramic two-dimensional image, and fitting the extracted edge into a straight line through Hough transform to form a linear structural plane trace.
7. An automatic identification system of rock mass structural plane according to claim 5, characterized in that in the structural plane trace identification module, the length of the three-dimensional structural plane trace is calculated according to the distance between the two end points of the three-dimensional structural area line.
8. The automatic identification system of rock mass structural plane according to claim 5, characterized in that in the structural plane disc diameter prediction module, the probability distribution relation between the structural plane disc diameter and the three-dimensional structural plane trace length is as follows:
p(l≤D≤3l)＝0.99
p(l≤D≤10l)＝0.01
wherein D is the diameter of the structural plane disc; l is the three-dimensional structure surface trace length; p is the probability.
9. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the steps of the method for automatic identification of a rock mass structural plane according to any one of claims 1-4.
10. A computer apparatus comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor when executing the program performs the steps of the method of automatically identifying a rock mass structural plane according to any one of claims 1 to 4.
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