CN113268856A - Probability-based crack characterization and reconstruction method, storage medium and terminal device - Google Patents
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Abstract
The invention discloses a probability-based crack characterization and reconstruction method, a storage medium and a terminal device, wherein the method comprises the following steps: acquiring coordinates of crack points in the crack image to be processed, and marking the coordinates as F; inducing the crack line segments among all crack points into a plurality of growth direction vectors, and recording the formed set as D; determining the starting point and the end point of the crack and the macroscopic growth vector thereof, and respectively recording the starting point and the end point as f1、fn、VL macroCounting to obtain a probability set of each growth direction vector, marking as P, and representing one bending crack by adopting the parameters; setting the growth step length t according to the requirementmaxCrack starting point f1Macro growth vector VL macroA growth direction vector set D and a corresponding probability set P parameter; a crack or cracks are generated by a reconstruction algorithm. The invention provides a novel bending crack and a characterization and reconstruction method of a network of the bending crack, which solve the problems of characterization and reconstruction of the bending crack and reconstruction of a crack network consisting of a plurality of bending cracks.
Description
Technical Field
The invention relates to the technical field of crack characterization and modeling, in particular to a probability-based crack characterization and reconstruction method, a storage medium and a terminal device.
Background
With the development of computing technology, the rock mechanics and seepage characteristics under the influence of complex crack forms can be judged more intuitively and conveniently by means of numerical simulation and the like, and the research cost is reduced. The research on characteristics such as crack initiation and development in materials such as rock by using methods such as numerical simulation and the like is receiving great attention.
During numerical simulation, complex crack forms are often required to be characterized, and the reasonable characterization of the complex crack forms directly determines the accuracy and reliability of calculation results. After the numerical simulation is over, the relationship between the characterization method employed and the mechanical properties of interest is discussed to guide the actual engineering project. Meanwhile, in order to construct a complex crack form, reconstruction of a crack network formed by a single crack or a plurality of cracks is often required through a crack generation algorithm. In the current numerical simulation research, as for the characterization means, there are characterization means such as crack density, tortuosity and fractal dimension; as for the reconstruction method, algorithms such as a correlation algorithm with brownian motion and fractal interpolation can be applied to crack reconstruction. However, the prior art has not provided a crack characterization and reconstruction method based on statistics and image pixel space.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention provides a crack characterization and reconstruction method based on probability, a storage medium and a terminal device, and aims to solve the problem that the crack characterization and reconstruction method based on probability theory is not provided in the prior art.
The technical scheme of the disclosure is as follows:
a crack characterization and reconstruction method based on probability is characterized by comprising the following steps:
acquiring coordinates of crack points in the crack image to be processed, and marking the coordinates as F;
inducing the crack line segments among all crack points into a plurality of growth direction vectors, and recording the formed set as D;
obtaining a probability set of each growth direction vector through a statistical method, and marking the probability set as P;
determining the coordinates of pixel points corresponding to the crack starting point and the crack end point, and respectively recording the coordinates as f1And fnAnd obtaining a macroscopic growth vector of the crack, which is recorded as VL macro(ii) a Setting the growth step length t according to the requirementmaxAnd combining the pixel point coordinate f of the crack starting point1Macro growth vector VL macroAnd generating one crack or a plurality of cracks by a reconstruction algorithm through the growth direction vector set D and the probability set P corresponding to the growth direction vector set D.
The probability-based crack characterization and reconstruction method comprises the following steps of:
carrying out binarization processing on the crack image to be processed;
performing morphological thinning processing on the crack image subjected to binarization processing to obtain a standard crack contour line image;
extracting the pixel position of the crack in the standard crack contour line image to obtain the coordinate data of the crack point, and recording the coordinate data as F ═ Fi},fi＝(xi,yi,zi)TWhere F denotes a set of crack points, symbol T denotes a transposition, and F1 denotes coordinates of the ith point in the crack line, the crack start point is F1＝(x1,y1,z1)TCrack end point of fn＝(xn,yn,zn)T。
The probability-based crack characterization and reconstruction method is characterized in that crack line segments among all crack points are generalized into 8 growth direction vectors in a two-dimensional pixel plane, and the set of the crack line segments is as follows:
in the probability-based crack characterization and reconstruction method, crack line segments among all crack points are generalized into 26 growth direction vectors in a three-dimensional pixel space, and the set of the crack line segments is as follows:
wherein D represents a growth direction matrix, DiRepresents the i-th growth direction vector, di＝(D1,i,D2,i,D3,i)T，i＝1,2...,26。
The probability-based crack characterization and reconstruction method is characterized in that the probability set of each growth direction vector is represented as: p ═ Pi},pi∈[0,1]. Wherein the cumulative growth times along the 26 growth directions is Ti(i ═ 1,2.., 26), then
And is
The crack characterization and reconstruction method based on probability is characterized in that the crackThe macroscopic growth vector is represented as:
wherein, the pixel point coordinate f of the starting point of the crack1＝(x1,y1,z1)TCoordinates f of pixel points at crack end pointn＝(xn,yn,zn)T。
The crack characterization and reconstruction method based on the probability is characterized in that the growth step length t is set according to the requirementmaxAnd combining the pixel point coordinate f of the crack starting point1Macro growth vector VL macroThe step of generating a crack through a reconstruction algorithm by the growth direction vector set D and the probability set P corresponding to the growth direction vector set D specifically comprises the following steps:
inputting initial parameters including a growth direction vector set D, a growth direction probability set P and a growth step length tmaxMacro growth vector VL macroAnd a crack starting point f1；
Obtaining a growth direction vector d according to the growth direction probability set PiObtaining a random number between 0 and 1, judging which growth direction vector the random number belongs to, and further determining the next coordinate growth vector;
adding the coordinate of the last step and the coordinate growing vector to obtain the crack end point coordinate after the crack grows for one time;
continuing to generate random numbers until the number of generated random numbers equals to the growth step tmax；
Judging whether the vector formed by the starting point and the end point of the crack is equal to the macroscopic growth vector V or notL macroAnd if the two are consistent, the operation is ended, and if the two are not consistent, the crack is regenerated.
The probability-based crack characterization and reconstruction method specifically comprises the following steps of:
if the initial parameters comprise position information, sequentially generating a plurality of cracks;
if the initial parameters do not comprise position information, randomly generating a starting point coordinate after obtaining the point data of the single bending crack according to the input parameters of the single crack, judging whether the crack is in the set interval, and if not, re-generating; if the crack is within the interval, the next crack is generated.
A storage medium having one or more programs stored thereon that are executable by one or more processors to implement the steps of the probability based crack characterization and reconstruction method of the present invention.
A terminal device, comprising a processor adapted to implement instructions; and a storage medium adapted to store a plurality of instructions adapted to be loaded by a processor and to perform the steps of the probability based crack characterization and reconstruction method of the present invention.
Has the advantages that: compared with the prior art, the method provided by the invention is simple and convenient to operate, and can solve the problem that a crack characterization and reconstruction method based on a probability theory is not provided in the prior art. The method can be used for characterization and reconstruction of single or multiple bending cracks, makes up for the shortage of the characterization and reconstruction method of the bending cracks, and greatly facilitates research of seepage and mechanical properties of materials such as rocks, concrete and the like under the influence of natural cracks and artificial cracks by scientific research personnel.
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FIG. 1 is a flowchart of an embodiment of a probability-based crack characterization and reconstruction method of the present invention.
Fig. 2 is a schematic diagram of 8 directions in a two-dimensional pixel plane according to an embodiment of the present invention.
FIG. 3 is a schematic view of a standard joint profile in an embodiment of the present invention.
Fig. 4 is a schematic flow chart of a reconstruction method of a single crack in an embodiment of the present invention.
FIG. 5 is a flow chart of multi-crack generation with all starting points known in the examples of the present invention.
FIG. 6 is a flow chart of multi-crack generation for all random starting points in an embodiment of the present invention.
FIG. 7 is a single crack reconstruction result graph obtained by a reconstruction method after a characterization parameter extracted from a standard joint profile image is adopted.
FIG. 8 is a graph of multi-crack results generated using the reconstruction method of an embodiment of the present invention.
Fig. 9 is a schematic block diagram of the terminal device of the present invention.
Detailed Description
The invention provides a probability-based crack characterization and reconstruction method, a storage medium and a terminal device, and further detailed description is provided below to make the purpose, technical scheme and effect of the invention clearer and clearer. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including 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 will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
As is well known, the phenomenon of crack propagation occurs widely in nature, and research on materials such as cracked rocks has been conducted with some success. However, the current crack characterization and reconstruction methods still have disadvantages, such as fractal dimension number characterization and related fractal interpolation algorithm, where the obtained crack point data may have infinite decimals, which brings inconvenience to numerical modeling, numerical calculation and numerical analysis.
Based on this, the invention provides a probability-based crack characterization and reconstruction method, so as to make up for the defects of the crack characterization and reconstruction method and overcome the problems encountered by the original crack characterization and reconstruction method in use, as shown in fig. 1, the probability-based crack characterization and reconstruction method comprises the following steps:
s10, acquiring coordinates of crack points in the crack image to be processed, and recording the coordinates as F;
s20, inducing the crack line segments among all crack points into a plurality of growth direction vectors, and recording the formed set as D;
s30, obtaining a probability set of each growth direction vector through a statistical method, and marking the probability set as P;
s40, determining pixel point coordinates corresponding to the crack starting point and the crack end point, and respectively recording the pixel point coordinates as f1And fnAnd obtaining a macroscopic growth vector of the crack, which is recorded as VL macro；
S50, setting the growth step t according to the needmaxAnd combining the pixel point coordinate f of the crack starting point1Macro growth vector VL macroAnd generating one crack or a plurality of cracks by a reconstruction algorithm through the growth direction vector set D and the probability set P corresponding to the growth direction vector set D.
The basic theoretical model of the probability-based crack characterization and reconstruction method provided by the embodiment is as follows: a curved crack can be viewed as an uneven line segment formed by a plurality of points connected together, and if the spatial coordinates of the points contained in the crack are obtained, the characteristics of the crack are determined. In this embodiment, first, binarization processing is performed on a crack image to be processed, andperforming morphological thinning processing on the crack image subjected to binarization processing to obtain a standard crack contour line image; and then extracting the pixel position of the crack in the standard crack contour line image to obtain the coordinate data of the crack point, wherein F is { F ═ Fi},fi＝(xi,yi,zi)T1,2, n, wherein F denotes a set of crack points, the symbol T denotes a transposition, F denotes a base, and1the coordinates of the ith point in the crack line are shown, the crack starting point is f1＝(x1,y1,z1)TCrack end point of fn＝(xn,yn,zn)T。
In crack point bonding, the vector from any crack point to the next crack point is defined as the growth vector. The ordered growth vector set between adjacent crack points is: fg＝{fg,iIn which FgRepresenting an ordered set of growth vectors, fg,iRepresents the growth vector at step i, fg,i＝(xi+1-xi，yi+1-yi,zi+1-zi)T,i＝1,2,...n-1。
At this time, a completely determined crack point set system is: gF＝(f1,Fg) Wherein G isFRepresentative of a system of crack points, f1Representing the first point.
Thus, the set of points F for a crack can also be expressed as:
as can be seen from the formula, the growth vectors of any two points in any crack have great uncertainty, and if possible direction growth vectors are not restricted, the direction vectors of the crack and the probability representation thereof become a multi-dimensional problem which is difficult to solve. And the crack is characterized by only adopting the method, a large amount of storage space is occupied, and the method is inconvenient to use.
Splitting between all crack points in two-dimensional pixel planeThe segment of striae is summarized into 8 growth direction vectors, which form a set:
in voxel space, the crack line segments between all crack points are grouped into 26 growth direction vectors, which are grouped together:
where D represents a growth direction matrix, DiRepresents the i-th growth direction vector, di＝(D1,i,D2,i,D3,i)T，i＝1,2...,26。
If a crack contains n crack points and the number of crack segments contained in the crack is set as a growth step length, the maximum growth step length of the crack is tmaxN-1. Given a set of growth direction vectors, the set of sequential searches for all crack segment directions that make up the crack can be expressed as: s ═ St}. Wherein S istDirection search for the t-th crack line segment, St∈[1,2,...,26] T 1,2,. n-1; in two-dimensional pixel space. St∈[1,2,...,8]
At this time, the ordered growth vector assembly system of the crack: fg(D, S), then in pixel space, a fully determined crack point set system GF＝(f1,D,S)。
It can be seen from the above formula that when the starting point, the set of possible ordered growth direction vectors, and the ordered search set of growth direction vectors are determined, a completely determined crack profile can be obtained. When the order in the search set of the growth direction vector is adjusted, a crack profile with unchanged starting point position, end point position, macro growth vector, macro length and micro length can be obtained. The utility of reconstructing a similar crack contour from an ordered set of growing direction vector searches is clearly not high.
In fact, the statistical characteristics are applied to all directions in the pixel spaceThe number of the uniform crack lines is T in the cumulative growth in 26 directionsi( i 1,2.., 26), then the probability set P corresponding to the growth direction vector is { P ═ Pi},pi∈[0,1]Wherein, in the step (A),
and is
In a two-dimensional pixel plane, i is 1,2.
When the possible growth direction vector set D, the probability set P corresponding to the possible growth direction vector, and the growth step length t are knownmaxMacro growth vector VL macroAnd a starting point f1, a crack point set system having the same statistical characteristics and having a spatial position matching the macroscopic growth direction vector:
in the embodiment, after the crack image to be processed is acquired, the crack point coordinate F ═ F is acquired by an image processing methodi},fi＝(xi,yi,zi)T1,2, n; the crack line segments among all crack points are generalized into 8 or 26 growth direction vectors, and the set formed by the crack line segments is marked as D; counting to obtain a probability set P of each growth direction vector; finding out the coordinates of the pixel points corresponding to the starting point and the end point of the crack, and respectively recording the coordinates as f1＝(x1,y1,z1)TAnd fn＝(xn,yn,zn)T(ii) a Further macroscopic growth vectors for the cracks can be obtained, which are noted as:
at this time, one bending crack can be characterized by the above parameters; setting the growth step length t according to the requirementmaxAnd combining the pixel point coordinate f of the crack starting point1Macro growth vector VL macroGrowth direction vector set D and corresponding probability set PAnd generating one crack or a plurality of cracks through a reconstruction algorithm.
In some embodiments, the crack reconstruction algorithm has two main flows: one is a generation algorithm of a single bending crack, and the other is a generation algorithm of a crack network formed by a plurality of bending cracks. The specific implementation steps of the single bending crack generation algorithm comprise: inputting initial parameters, wherein the initial parameters comprise a growth direction vector set D, a probability set P corresponding to the growth direction vector set D and a growth step length tmaxMacro growth vector VL macroAnd pixel point coordinate f of crack starting point1(ii) a The growth step t can also be removedmaxMacro growth vector VL macroAnd a starting point f1To ignore crack location and morphological constraints; obtaining a growth direction vector d according to the growth direction probability set PiObtaining a random number between 0 and 1, judging which growth direction vector the random number belongs to, and further determining the next coordinate growth vector; the coordinates of the previous step (the coordinates of the starting point f when the coordinates are generated for the first time)1) Adding the coordinate growth vector to obtain the crack end point coordinate after the crack grows for one time; continuing to generate random numbers until the number of generated random numbers equals to the growth step tmax(ii) a Judging whether the vector formed by the starting point and the end point of the crack is equal to the macroscopic growth vector V or notL macroAnd if the two are consistent, the operation is ended, and if the two are not consistent, the crack is regenerated. When the macroscopic morphology or spatial position of the cracks is ignored, the macroscopic growth vector V may not be consideredL macroAnd a starting point f1The limit of (2); at this point, its associated steps are ignored accordingly.
The key details of the crack network generation algorithm formed by a plurality of curved cracks include the steps of: if the input parameters contain position information, sequentially generating a plurality of bending cracks; if the input parameters do not contain position information, obtaining point data of the single bending crack according to the input parameters of the single bending crack, then randomly generating a starting point coordinate, judging whether the crack is in the set interval, if not, re-generating, and if so, generating the next bending crack.
In some embodiments, the crack may have a set of growth direction vectors D and its corresponding set of probabilities P, a growth step length tmaxMacro growth vector VL macroAnd a starting point f1As initial parameters. In fact, only the growth direction D, the growth direction probability P, and the growth step length t of the set of crack points need to be knownmaxA set of crack point sets may be obtained, but the overall distribution pattern of the crack point sets obtained at this time may be different from the overall distribution pattern of the desired crack point sets. If a crack origin is given, the spatial position of the set of crack points is also completely determined. Therefore, in practical applications, if the spatial position is not considered, the starting point f is ignored1. Disregarding the macroscopic morphology, neglecting the macroscopic growth vector VL macro。
In some embodiments, crack line data in a voxel space may be obtained after acquiring two-dimensional crack point data of a crack picture obtained by means of CT scanning or the like and estimating elevation data for crack lines in the voxel space.
In some embodiments, when the computer has insufficient computing power and sufficient storage capacity, an ordered set of growth vectors can be obtained from the crack point data, disordering the growth vectors in the set. And then setting the initial point coordinates, thereby generating the cracks.
In another aspect, the present invention provides a novel characterization method for flexural cracks, which is based on probability theory. When the crack needs to be accurately described, the crack comprises a growth direction vector set D, a growth direction probability set P and a growth step length tmaxMacro growth vector VL macroAnd a starting point f1Several parameters. When ignoring spatial positions, the starting point f is ignored1Ignoring the macroscopic growth vector V when ignoring the macroscopic morphologyL macro。
The probability-based crack characterization and reconstruction method of the invention is further explained by the following specific embodiments:
the present embodiment provides the contents of crack characterization and crack reconstruction, taking the example of summarizing crack line segments between all crack points into 8 growth direction vectors in a two-dimensional pixel plane, and fig. 2 is a schematic diagram of 8 directions in the two-dimensional pixel plane. An example of a standard joint profile is shown in fig. 3. And obtaining the coordinate data of the crack point by performing expansion, corrosion, binarization and other treatment on the crack-containing image. After the crack point coordinate data is obtained, the statistical growth times corresponding to 8 possible growth directions can be obtained by subtracting the corresponding coordinate of any crack point from the corresponding coordinate of the previous crack point, as shown in table 1.
TABLE 1 growth direction vector and statistical results
By dividing the statistical growth times for each growth direction by the total growth times, the statistical probabilities for the 8 possible growth directions of the crack in the pixel plane can be obtained, as shown in table 2.
TABLE 2 growth direction vectors and their corresponding probabilities
Tables 1 and 2 are numerical table results of the crack characterization method set forth herein. In this case, the set of growth direction vectors of the crack and the corresponding set of probabilities are known, and information on the coordinates of the starting point, the macroscopic growth direction vector, and the growth step length can be obtained by simple calculation. The above parameters are the approximate characterization method proposed herein to approximate the rock joints/cracks.
Fig. 4 is a schematic flow chart of a reconstruction method of a single crack proposed by the present invention. After the crack characterization method provided by the invention is adopted to characterize the rock joints/cracks, the characterization parameters can be further adopted to reconstruct the cracks. First, the space where the reconstructed crack is located is gridded, and N is set in the x directionxDots, set N in the y directionyDots, set N in the z directionzAnd (4) points. Sequentially defining grid coordinates of the grid;
setting initial input parameters, wherein the input parameters can comprise all the characterization parameters: growing direction vector set D and corresponding probability set P, starting point f1Macroscopic growth vector VL macroAnd a growth step tmax. Random starting points and growing steps can also be used, and can be ignored if necessary because the limitation of the macroscopic growing vector can cause a large number of loop calculations to reduce the generation efficiency. Meanwhile, the vector set in the growth direction and the corresponding probability set are necessary input parameters; dividing each interval corresponding to the long direction vector according to the input probability set; setting the initial growth step length as 0, generating a random number, judging the interval of the random number, and determining the growth direction vector corresponding to the interval; calculating the coordinate of the next crack point according to the determined growth direction vector by using the coordinate of the previous crack point, and then adding 1 to the actual growth step length in the step; sequentially generating all crack points until the actual growth step length is equal to the set growth step length; and judging whether the obtained vector formed by the starting point and the end point of the crack is consistent with the macroscopic growth vector, if not, recalculating, and if so, outputting crack point data.
Fig. 5 is a flow chart of the multi-crack generation of all known starting points proposed by the present invention. After the characterization parameters of the invention are determined, multiple cracks can be formed in sequence according to a reconstruction method of a single crack directly through the known crack characterization parameters, and finally point data of the multiple cracks is output.
FIG. 6 is a flow chart of the multi-crack generation of all random starting points proposed by the present invention. As shown in fig. 5 and 6, at the time of the random starting point, it is necessary to determine whether or not all crack points included in the generated crack exist in the set space. When the mobile terminal is not in the set space, the starting point needs to be re-randomized; when the crack is in the set space, the next crack can be generated until the number of generated cracks is consistent with the set number of cracks.
After the characterization parameters extracted from the standard joint profile image are adopted, the single crack reconstruction result obtained by the reconstruction method of the invention is shown in fig. 7. Fig. 8 shows a multi-crack generated by the reconstruction method according to the present invention, wherein a in fig. 8 is a multi-crack obtained when the step size is set to 25, and b in fig. 8 is a multi-crack obtained when the step size is set to 30.
In some embodiments, a storage medium is also provided, wherein the storage medium stores one or more programs executable by one or more processors to implement the steps of any of the probability-based crack characterization and reconstruction methods of the present invention.
In some embodiments, there is also provided a terminal device, as shown in fig. 9, comprising at least one processor (processor) 20; a display screen 21; and a memory (memory)22, and may further include a communication Interface (Communications Interface)23 and a bus 24. The processor 20, the display 21, the memory 22 and the communication interface 23 can communicate with each other through the bus 24. The display screen 21 is configured to display a user guidance interface preset in the initial setting mode. The communication interface 23 may transmit information. The processor 20 may invoke logic instructions in the memory 22 to perform the probability-based crack characterization and reconstruction method of the above embodiments.
Furthermore, the logic instructions in the memory 22 may be implemented in software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product.
The memory 22, which is a computer-readable storage medium, may be configured to store a software program, a computer-executable program, such as program instructions or modules corresponding to the methods in the embodiments of the present disclosure. The processor 20 executes the functional application and data processing, i.e. implements the method in the above-described embodiments, by executing the software program, instructions or modules stored in the memory 22.
The memory 22 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal device, and the like. Further, the memory 22 may include a high speed random access memory and may also include a non-volatile memory. For example, a variety of media that can store program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, may also be transient storage media.
In addition, the specific processes loaded and executed by the storage medium and the instruction processors in the terminal device are described in detail in the method, and are not stated herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present disclosure are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present disclosure.
It is to be understood that the application of the present disclosure is not limited to the examples described above, and that modifications and variations may be made by persons skilled in the art in light of the above teachings, and all such modifications and variations are intended to fall within the scope of the appended claims.
Claims (10)
1. A crack characterization and reconstruction method based on probability is characterized by comprising the following steps:
acquiring coordinates of crack points in the crack image to be processed, and marking the coordinates as F;
inducing the crack line segments among all crack points into a plurality of growth direction vectors, and recording the formed set as D;
obtaining a probability set of each growth direction vector through a statistical method, and marking the probability set as P;
determining the coordinates of pixel points corresponding to the crack starting point and the crack end point, and respectively recording the coordinates as f1And fnAnd obtaining a macroscopic growth vector of the crack, which is recorded as VL macro；
Setting the growth step length t according to the requirementmaxAnd combining the pixel point coordinate f of the crack starting point1Macro growth vector VL macroAnd generating one crack or a plurality of cracks by a reconstruction algorithm through the growth direction vector set D and the probability set P corresponding to the growth direction vector set D.
2. The probability-based crack characterization and reconstruction method according to claim 1, wherein the step of obtaining coordinates of crack points in the crack image to be processed specifically comprises:
carrying out binarization processing on the crack image to be processed;
performing morphological thinning processing on the crack image subjected to binarization processing to obtain a standard crack contour line image;
extracting the pixel position of the crack in the standard crack contour line image to obtain the coordinate data of the crack point, and recording the coordinate data as F ═ Fi},fi＝(xi,yi,zi)T1,2, n, wherein F denotes a set of crack points, the symbol T denotes a transposition, F denotes a base, and1the coordinates of the ith point in the crack line are shown, the crack starting point is f1＝(x1,y1,z1)TCrack end point of fn＝(xn,yn,zn)T。
3. The probability-based crack characterization and reconstruction method of claim 1, wherein crack line segments between all crack points are summarized into 8 growth direction vectors in a two-dimensional pixel plane, which are composed of the set of:
4. the probability-based crack characterization and reconstruction method of claim 1, wherein the crack line segments between all crack points are summarized into 26 growth direction vectors in the three-dimensional pixel space, and the set of the vectors is:
wherein D represents a growth direction matrix, DiRepresents the i-th growth direction vector, di＝(D1,i,D2,i,D3,i)T，i＝1,2...,26。
5. The method of probability-based crack characterization and reconstruction of claim 4, wherein the set of probabilities for each growth direction vector is represented as: p ═ Pi},pi∈[0,1]Wherein the cumulative growth times along the 26 growth directions is Ti(i ═ 1,2.., 26), then
And is
6. The probability-based crack characterization and reconstruction method of claim 1, wherein the macro growth vector of the crack is represented as:
wherein, the pixel point coordinate f of the starting point of the crack1＝(x1,y1,z1)TCoordinates f of pixel points at crack end pointn＝(xn,yn,zn)T。
7. The method according to claim 1, wherein the growth step length t is set as desiredmaxAnd combining the pixel point coordinate f of the crack starting point1Macro growth vector VL macroThe step of generating a crack through a reconstruction algorithm by the growth direction vector set D and the probability set P corresponding to the growth direction vector set D specifically comprises the following steps:
inputting initial parameters including a growth direction vector set D, a growth direction probability set P and a growth step length tmaxMacro growth vector VL macroAnd a crack starting point f1；
Obtaining a growth direction vector d according to the growth direction probability set PiObtaining a random number between 0 and 1, judging which growth direction vector the random number belongs to, and further determining the next coordinate growth vector;
adding the coordinate of the last step and the coordinate growing vector to obtain the crack end point coordinate after the crack grows for one time;
continuing to generate random numbers until the number of generated random numbers equals to the growth step tmax；
Judging whether the vector formed by the starting point and the end point of the crack is equal to the macroscopic growth vector V or notL macroAnd if the two are consistent, the operation is ended, and if the two are not consistent, the crack is regenerated.
8. The probability-based crack characterization and reconstruction method according to claim 7, wherein the step of generating a plurality of cracks by a reconstruction algorithm specifically comprises:
if the initial parameters comprise position information, sequentially generating a plurality of cracks;
if the initial parameters do not comprise position information, randomly generating a starting point coordinate after obtaining the point data of the single bending crack according to the input parameters of the single crack, judging whether the crack is in the set interval, and if not, re-generating; if the crack is within the interval, the next crack is generated.
9. A storage medium storing one or more programs executable by one or more processors to perform the steps of the probability based crack characterization and reconstruction method according to any one of claims 1-8.
10. A terminal device comprising a processor adapted to implement instructions; and a storage medium adapted to store a plurality of instructions adapted to be loaded by a processor and to perform the steps of the probability based crack characterization and reconstruction method according to any one of claims 1-8.
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