CN115661133A - Geological type identification method - Google Patents
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Abstract
The invention relates to the technical field of graphic data identification, in particular to a geological type identification method. According to the method, the tool mark image data formed on the rock body by the drill bit in the working process of the rock breaking machine is collected, the concentric circle significance and the tool mark density are obtained according to the collected tool mark image data, the stratum geological density is further represented according to the concentric circle significance and the tool mark density, and the geological type is identified according to the stratum geological density. According to the method, the overall characteristics of the tool mark image are represented according to the significance of the concentric circles, the local characteristics of the tool mark image are represented according to the density of the tool marks, the geological type is accurately identified through the combination of the overall characteristics and the local characteristics, and the geological type is identified according to the tool mark image formed on the rock body by the drill bit, so that the cost is lower compared with the prior art. Therefore, the invention has lower cost while ensuring the accuracy.
Description
Technical Field
The invention relates to the technical field of graphic data identification, in particular to a geological type identification method.
Background
Before mining, tunnel construction and geological exploration, the geological environment of construction needs to be explored in advance, but the geological condition is often complicated and changeable, and the acquired geological information has many limitations and inaccuracy, so that the real-time geological information in the tunneling process needs to be analyzed.
In the prior art, a geological type identification method mainly comprises the following steps: and in the working process of the rock breaking machine, judging the geological type according to the vertical stress condition of a hob of the rock breaking machine. However, the method for judging the geological type according to the vertical stress condition of the hob of the rock breaker needs to arrange a device for detecting the strength of the hob on each hob, so that the cost is high; and the geological type is judged only according to the stress condition, so that the geological type is not accurately judged, and the method for judging the geological type according to the vertical stress condition of the hob of the rock breaker is high in cost and is not accurate enough. In the prior art, the geological image can be identified through the neural network, but the method for identifying through the neural network needs to artificially label a large amount of geological historical data, the cost is high, and the identification accuracy is low under the condition that the quantity of the historical data is insufficient.
Disclosure of Invention
In order to solve the above technical problems, an object of the present invention is to provide a method for identifying a geological type, which adopts the following technical solutions:
the invention provides a geological type identification method, which comprises the following steps:
acquiring a denoised face image generated by the excavation of a rock breaker, taking a part of the face image with a gray value larger than a preset first threshold value as a first screening area, wherein the first screening area comprises a plurality of connected domains, and screening out a bit tool mark sub-area of the connected domains according to the fitting degree of the connected domains and a circle;
obtaining the circle centers of the corresponding drill bit tool mark sub-regions according to the fitting circle corresponding to each drill bit tool mark sub-region, and obtaining the significance of the concentric circles of the tool marks according to the position distribution characteristics between the circle centers of the drill bit tool mark sub-regions and the number of the drill bit tool mark sub-regions;
obtaining the width of the cutter mark at each position of the cutter mark subregion of the drill bit, detecting the number of angular points of the cutter mark subregion of the drill bit, and obtaining the density of the cutter mark according to the width distribution characteristics of the cutter mark width and the number of the angular points;
and obtaining the geological density of the stratum according to the significance of the concentric circles of the tool marks and the density of the tool marks, and finishing the identification of the geological type according to the geological density of the stratum.
Further, the method for acquiring the position distribution characteristics comprises the following steps:
calculating Euclidean distance between every two circle centers of the drill bit tool mark sub-regions, calculating standard deviation of the Euclidean distance, arranging the Euclidean distances from small to large, and screening a mutation value through a BG (Block segmentation) algorithm; calculating a first mean value of the mutation value, screening out second mean values corresponding to other Euclidean distances except the mutation value, and obtaining a convex hull formed by the circle centers of the sub-regions of the drill bit tool marks according to a convex hull algorithm to obtain the area of the convex hull; if the mutation value does not exist, the first average value and the second average value are equal;
and taking the standard deviation, the first mean, the second mean and the area of the convex hull as the position distribution characteristic.
Further, the obtaining of the significance of the concentric circles of the tool marks according to the position distribution characteristics between the circle centers of the sub-regions of the tool marks of the drill bit and the number of the sub-regions of the tool marks of the drill bit comprises:
obtaining the significance of the concentric circles of the tool marks through a tool mark concentric circle significance calculation model according to the position distribution characteristics between the circle centers of the sub-regions of the tool marks of the drill bit and the number of the sub-regions of the tool marks of the drill bit, wherein the tool mark concentric circle significance calculation model comprises:
wherein ,
the significance of the concentric circles of the tool marks,
is the first average value of the first average value,
is the second average value of the first average value,
is the area of the convex hull and,
is the standard deviation of the euclidean distance,
the number of the drill bit cutting mark sub-areas,
is a preset adjustment factor.
Further, the width distribution characteristic of the tool mark width comprises:
constructing a three-dimensional coordinate system based on the positions of pixel points in the drill bit tool mark sub-area and the tool mark widths corresponding to the pixel points, wherein the x axis of the three-dimensional coordinate system is the horizontal axis of the image coordinate system, the y axis is the longitudinal axis of the image coordinate system, and the z axis is the tool mark width; mapping each pixel point in the drill bit cutter mark sub-area to the three-dimensional coordinate system; clustering pixels in the three-dimensional coordinate system through a clustering algorithm in the three-dimensional coordinate system to obtain a pixel clustering set; and taking the difference between the width of each knife mark and the mean value of the widths of the knife marks and the number of the pixel point clustering sets as the width distribution characteristics of the widths of the knife marks.
Further, the obtaining of the tool mark density according to the width distribution characteristics of the tool mark width and the number of the corner points includes:
obtaining the tool mark density according to the tool mark width distribution characteristics, the angular point quantity and the pixel clustering set through a tool mark density model, wherein the tool mark density model comprises:
wherein ,
the density of the knife mark is the density of the knife mark,
is as follows
The width of each knife mark is equal to the width of each knife mark,
is the average value of the widths of the tool marks,
for the number of said corner points,
for the number of the pixel point cluster sets,
is the number of said rays.
Further, the obtaining of the geological density of the stratum according to the significance of the concentric circles of the tool marks and the density of the tool marks comprises:
and accumulating the cutter mark densities to obtain a cutter mark density accumulated value, mapping the cutter mark density accumulated value to an exponential function with a natural constant as a base, and taking the product of the mapping value and the corresponding concentric circle significance as the geological density of the stratum.
Further, the identification of the geological type according to the geological density of the stratum comprises:
dividing the stratum with the geological density of the stratum being greater than the first preset density threshold into a hard rock stratum, dividing the stratum with the geological density being less than the second preset density threshold into a soft stratum, dividing the stratum with the geological density being less than or equal to the first preset density threshold and being greater than or equal to the second preset density threshold into a stratum with uneven hardness, and enabling the first preset density threshold to be greater than the second preset density threshold.
Further, screening out the drill bit tool mark sub-region of the connected domain according to the fitting degree of the connected domain and the circle comprises:
and recording the region where the pixel point set corresponding to the circle with the fitting degree larger than a preset fitting degree threshold value is located as a drill bit tool mark sub-region.
Further, the obtaining of the tool mark width of each position of the drill bit tool mark sub-region comprises:
and taking the center of a fitting circle corresponding to the drill bit cutting mark sub-region as a starting point, obtaining rays in all directions, and taking the length of the line of the rays in the edge of the drill bit cutting mark sub-region as the width of the cutting mark.
Further, the connected component obtaining method in the first screening area includes:
and carrying out clustering analysis on the pixel points contained in the first screening area by using a spectral clustering algorithm to obtain a plurality of connected domains.
The invention has the following beneficial effects:
according to the embodiment of the invention, the significance of the concentric circles of the tool marks is obtained according to the difference between the centers of the sub-areas of the tool marks of the drill bit and the number of the sub-areas of the tool marks of the drill bit, the significance of the concentric circles of the tool marks formed by the drill bit of the rock breaking machine is used as one parameter for judging the geological type, the density of the tool marks is obtained according to the width of the tool marks, the number of the angular points and the corresponding clustering set of the pixel points, and the density of the tool marks is used as the other parameter for judging the geological type. The concentric circle significance degree characterizes the overall distribution of the cutter mark sub-regions, the cutter mark density characterizes the specific shape characteristics of each cutter mark sub-region, the overall cutter mark morphological characteristics of the palm surface image, namely the bottom layer geological density, are obtained by combining the concentric circle significance degree and the cutter mark density, and the geology can be identified through the overall cutter mark morphological characteristics in the image. Compared with the existing method, the geological type recognition is carried out only according to the cutter mark image formed by the drill bit, the cost is lower, and the tool mark morphological characteristics are further specifically represented by combining two parameters of the concentric circle significance and the cutter mark significance, so that the overall distribution of the cutter mark sub-regions is represented, the specific shape characteristics of each cutter mark sub-region are also embodied, and the geological type recognition is more accurate. In conclusion, in the geological type identification process, the accuracy of geological type identification is improved while the low cost is ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a geological type identification method according to an embodiment of the present invention.
Fig. 2 is a sectional image of the rock breaker tunneling.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description of a geological type identification method according to the present invention, its specific implementation, structure, features and effects will be given in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
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.
The following describes a specific scheme of the geological type identification method provided by the invention in detail with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of a method for identifying a geological type according to an embodiment of the present invention is shown, where the method includes:
step S1: the method comprises the steps of obtaining a denoised face image generated by the excavation of a rock breaker, taking a part of the face image with the gray value larger than a preset first threshold value as a first screening area, wherein the first screening area comprises a plurality of connected domains, and screening out a bit tool mark sub-area of the connected domains according to the fitting degree of the connected domains and circles.
A camera is erected at the tunneling section of the rock breaker, and a tunnel face image of the tunneling section is obtained through camera shooting in the tunneling process of the rock breaker, wherein the tunnel face image is an RGB image. Meanwhile, the rock breaker is located in a mountain or a rock body in the tunneling process, so that the environment is dark, and extra illumination is required to be provided when a camera is used for shooting a tunnel face of a tunneling section. In the embodiment of the present invention, the camera is selected as a CCD camera, and the adopted illumination device can make the image of the tunnel face shot by the camera clear enough, which is not further limited herein.
Furthermore, in the excavation process of the rock breaker, the caused rock mass fragmentation inevitably generates smoke dust, and the smoke dust can cause inevitable noise of the face image shot by the camera, so that the quality of the face image is further influenced, and the face image preliminarily collected by the camera needs to be denoised. Image denoising is a common prior art in image processing, and denoising methods that can be used herein include, but are not limited to, a smooth filtering denoising technique, a median filtering denoising technique, a bilateral filtering denoising technique, and the like. In the embodiment of the invention, the collected tunnel face line is subjected to denoising pretreatment by adopting a bilateral filtering denoising technology to obtain a denoised tunnel face image. According to the embodiment of the invention, only the collected face image is analyzed, and a professional data acquisition device is not needed, so that the cost of the method for identifying the geological type according to the image is lower than that of the prior art. It should be noted that all the subsequently processed face images are denoised face images, and the bilateral filtering denoising technique is a prior art well known to those skilled in the art and is not further limited and described herein.
Referring to fig. 2, which shows a sectional image of the rock breaking machine provided by the embodiment of the present invention, as can be seen from fig. 2, a plurality of drill bits are arranged on a section of the rock breaking machine, and during the operation of the rock breaking machine, a plurality of circular tool marks are formed on the surface of the formation by performing rotational friction on the formation by each drill bit on the surface of the rock breaking machine, and the circular tool marks form tracks similar to concentric circles. After the denoised face image is obtained, the tool marks formed by the drill bit of the rock breaker in the face image are analyzed, the tool marks formed by the drill bit are concentric, but when the rock breaker breaks natural rough rock, different bulges or recesses can be generated at different positions, so that the tool marks are mistakenly divided into tool marks in concentric circles due to different light reflection degrees at different positions, and the denoised face image is further screened to prevent the influence of the different light reflection degrees at different positions on tool mark analysis.
In the embodiment of the invention, for convenience of subsequent calculation, the palm surface image is subjected to graying processing, and an area with a gray value larger than a preset first threshold value is selected as a first screening area. In the embodiment of the invention, the palm image is subjected to preliminary division by using the OTSU maximum inter-class variance method, namely, the first threshold is obtained by using the OTSU maximum inter-class variance method.
Carrying out clustering analysis on the pixel points contained in the first screening area by using a spectral clustering algorithm to obtain a plurality of pixel point clustering sets, and recording the number of the pixel point clustering sets as
，
And the pixel point sets are positive integers, and different pixel point sets correspond to different connected domains.
It should be noted that the variance method between the maximum classes of OTSUs and the spectral clustering algorithm are well known in the prior art by those skilled in the art, and the first preset threshold is specifically set according to different illumination degrees, which is not further limited and described herein.
Fitting all pixel points contained in different connected domains to a circleAnd enabling each different connected domain to correspond to the fitting degree of different circles, and obtaining the fitting degree of the circles, wherein the fitting degree of the circles comprises an equation of the fitting circle and the fitting goodness of the circles. Further screening the fitting degree of the circles corresponding to different connected domains by setting a fitting degree threshold value, wherein the fitting degree is greater than the fitting degree threshold value
The screened connected domains are screened out, the screened connected domains correspond to tool marks formed by the drill bit, each screened connected domain is marked as a drill bit tool mark sub-region, and the number of the screened connected domains is marked as
That is, the number of corresponding drill bit cutting mark sub-areas is
，
Is a positive integer. In the embodiment of the invention, the fitting degree threshold value is set
Set to 0.82. It should be noted that the technical means for obtaining the fitting circle corresponding to the connected component through the distribution of the connected component pixels is the prior art well known to those skilled in the art, and is not further limited and described herein.
And S2, obtaining the circle centers of the corresponding drill bit tool mark sub-regions according to the fitting circle corresponding to each drill bit tool mark sub-region, and obtaining the significance of the concentric circles of the tool marks according to the position distribution characteristics between the circle centers of the drill bit tool mark sub-regions and the number of the drill bit tool mark sub-regions.
The tool marks formed by the rock breaker are concentric circles, so that the distribution characteristics of the circles corresponding to different tool mark sub-regions and the significance of the tool marks screened according to the brightness characteristics presented in the image on the presented concentric circle characteristics are further analyzed.
The stratum types of the working face of the rock breaker can be divided according to the structural compactness or looseness of the stratum, and are mainly divided into a hard rock stratum, a stratum with uneven hardness and a soft bottom layer. The drill bit of the rock breaking machine is clear and obvious in tool marks formed on the hard rock stratum when the drill bit works, the same tool marks are not prone to fracture, on the corresponding image of the hard rock stratum, the drill bit tool mark area is obvious, the number of the drill bit tool mark sub-areas is large, and the concentric circle characteristics of the corresponding drill bit tool mark area are more obvious. The stratum with uneven hardness is mainly a composite stratum, the position dug by the rock breaking machine contains various kinds of rock soil, the mechanical property and the geological difference are large, the cutter mark at the position with high hardness is clear, the cutter mark at the position with loose structure is fuzzy and is not easy to identify, and therefore the concentric circle characteristic corresponding to the cutter mark area of the drill bit on the image corresponding to the stratum with uneven hardness has certain visibility. The soft bottom layer is mainly clay stratum, sand-containing water-rich stratum and other mud soil layers and sand layer and other soft stratum, the corresponding stratum structure is loose, the rock breaker drill bit can collapse, form mud cakes and other conditions near the tool marks in the working process, the corresponding tool marks are loose, and therefore in the image corresponding to the soft bottom layer, the characteristics of concentric circles corresponding to the tool mark area of the drill bit are not obvious. The stratum types can be further identified according to the different concentric circle significances.
The significance of the concentric circles of the drill bit cutting mark area needs to be represented together according to the circle center position distribution characteristics of different drill bit cutting mark sub-areas and the number of the drill bit cutting mark sub-areas. When the circle center positions of the tool mark subregions of the drill bits are more discretely distributed and the number of the tool mark subregions is less, the structural compactness and hardness of the corresponding stratum are lower; on the contrary, when the circle center positions of the drill bit tool mark sub-areas are distributed more densely and the number of the tool mark sub-areas is more, the structural compactness and hardness of the corresponding stratum are higher.
The specific method for obtaining the circle center distribution characteristics of the cutter mark sub-area comprises the following steps: the method comprises the steps of firstly, calculating Euclidean distances among circle centers of equations of circles obtained by fitting corresponding to each drill bit cutting mark sub-region, calculating standard deviation of Euclidean distance values, arranging the Euclidean distances into a group of sequences from small to large, screening out mutation values in the sequences through a BG (Block segmentation) algorithm, recording the mean value of the mutation values as a first mean value, and recording the mean values of other values except the mutation values in the sequences as a second mean value. It should be noted that, when no mutation value is selected from the set of sequences, the value of the first mean value is assigned as the second mean value, and the BG segmentation algorithm is well known in the art, and will not be further limited and described herein.
When the degree that the areas in the images corresponding to the tool marks are concentric circles is high, the distances between the centers of the corresponding drill bit tool mark sub-areas are short, the corresponding Euclidean distances are small, the distribution of values is concentrated and uniform, no mutation value appears in the formed sequence, when the sequence has the mutation value, the position difference between the center of the drill bit tool mark sub-area corresponding to the mutation value and the centers of the other tool mark sub-areas is large, and when the mutation value is more, the concentric circle characteristics of the tool mark area in the corresponding image are less obvious. In the embodiment of the invention, the convex hulls of the pixel points corresponding to the centers of the circles are obtained through a convex hull algorithm, and the area of the convex hulls is calculated and recorded as
When the concentric circle features of the tool marks on the image are more obvious, the positions of the corresponding circle centers are closer, and the corresponding inner areas of the convex hulls are smaller. And taking the obtained Euclidean distance standard deviation between the circle centers, the first mean value, the second mean value and the area of the convex hull as the circle center distribution characteristics of the cutter mark sub-region. It should be noted that the convex hull algorithm is well known in the prior art, and is not further limited or described herein.
Constructing a tool mark concentric circle significance calculation model through the circle center distribution characteristics of the drill bit tool mark sub-regions and the number of the drill bit tool mark sub-regions to obtain corresponding concentric circle significance, wherein the tool mark concentric circle significance calculation model comprises the following steps:
wherein ,
the significance of the concentric circles is shown,
is a first average value of the first average value,
is the second average value of the first average value,
is the area of the convex hull and is,
is the standard deviation of the euclidean distance,
the number of the sub-regions of the drill bit cutting mark,
in order to preset the adjustment coefficient, the adjustment coefficient is set,
the purpose of (2) is to prevent the denominator from being 0. In the embodiment of the present invention, it is,
is set to 1.
The tool mark concentric circle significance calculation model combines the position distribution characteristics of the circle centers corresponding to the tool mark subregions of the drill bits and the number of the tool mark subregions of the drill bits to jointly represent the significance of the tool marks concentric circles, when the number of the tool mark subregions of the drill bits identified in the image is more, the distance between the circle centers corresponding to the tool mark subregions of the drill bits is closer, the difference between the numerical value of the distance between the circle centers and the numerical value of the numerical value which is not identified as the mutation value in the distances is smaller, and the significance of the tool marks concentric circles corresponding to the tool mark regions of the drill bits in the image is smaller
The larger the image, the more distinct the concentric circle features of the corresponding tool marks. The tool mark concentric circle significance gives consideration to the number of the drill bit tool mark sub-areas and the distribution of the drill bit tool mark sub-areas corresponding to the centers of the fitting circles, so that the obtained tool mark concentric circle significance is further more accurate, and the concentric circle significance represents the overall tool mark morphological characteristics of the palm surface image.
And step S3: and obtaining the width of the cutter mark at each position of the cutter mark subregion of the drill bit, detecting the number of angular points of the cutter mark subregion of the drill bit, and obtaining the density of the cutter mark according to the width distribution characteristics of the cutter mark width and the number of the angular points.
In order to enable the geological type to be identified more accurately, on the basis of obtaining the significance of the concentric circles corresponding to the drill bit cutting mark sub-regions, the drill bit cutting mark sub-regions in the image are analyzed in more detail. Because the tool marks are formed by drilling the drill bit in a reciprocating impact manner, the forming reasons of different positions in the tool marks are the same, the formed characteristic textures are the same, and the widths of the tool marks at different positions on a communication domain corresponding to the same tool mark sub-region are basically the same; in addition, the number of corner points of the tool marks formed by geology with different densities is different; therefore, the geological type is further identified through the tool mark density obtained by the tool mark width distribution characteristics and the number of corner points corresponding to the tool mark sub-regions on the basis.
In the embodiment of the invention, the center of a circle of each drill bit cutting mark subregion is analyzed on the basis, a ray is led out in each direction by taking the center of a circle of each drill bit cutting mark subregion as a starting point, the ray and the drill bit cutting mark subregion are intersected to form a line segment, the length corresponding to the line segment corresponds to a pixel point in the line segment, the length of the line segment is recorded as the cutting mark width, namely the cutting mark width corresponding to the pixel point in the line segment is consistent, and the cutting mark width in each direction is obtained according to the method. Number of rays as
To be connected to
The width of each cutting mark is recorded as
, wherein 
The average of these tool mark widths is recorded as a positive integer
。
Preferably, a three-dimensional coordinate system is constructed according to the positions of the pixel points in the drill bit cutter mark sub-region and the cutter mark widths corresponding to the pixel points, the horizontal axis of the image coordinate system is used as the x axis of the three-dimensional coordinate system, the vertical axis of the image coordinate system is used as the y axis of the three-dimensional coordinate system, and the cutter mark widths are used as the z axis of the three-dimensional coordinate system. Mapping each pixel point in the drill bit cutter mark sub-area to a three-dimensional coordinate system, clustering the pixel points in the three-dimensional coordinate system by using 5 as the minimum contained point number and 3 as the scanning radius through a DBSCAN algorithm to obtain more than two pixel point clustering sets, and recording the number of the pixel point clustering sets as
. It should be noted that the DBSCAN algorithm is well known in the art, and is not further limited or described herein.
Taking the difference between the width of the tool mark and the mean value of the width of the tool mark and the number of the pixel point clustering sets as the width distribution characteristic of the width of the tool mark, wherein the smaller the difference between the width of the tool mark and the mean value in each direction of the sub-area of the tool mark of the drill bit is, the more the pixel point clustering sets are, and the more the corresponding width of the tool mark is distributed in the sub-area of the tool mark of the drill bit; on the contrary, the larger the difference between the width of the drill mark and the mean value in each direction of the drill bit tool mark sub-region is, the fewer the pixel point clustering sets are, and the more disordered the corresponding width of the drill mark is distributed in the drill bit tool mark sub-region.
When the quality of the rock is tighter, the edges of the formed cutter mark sub-areas are clearer, uniform and smoother, and the angular points are fewer; correspondingly whenWhen the rock mass is loose, sand grains, gravels, clay and the like near the tool marks are easy to agglomerate and fall off, the edges of the tool marks are relatively tortuous and rough, and the angular points are more. Therefore, angular point detection is carried out on each drill bit tool mark sub-region on the basis of obtaining the tool mark width distribution, and the obtained angular point quantity is recorded as
. It should be noted that the corner detection is a technical means well known to those skilled in the art, and is not described herein.
Obtaining the tool mark density according to the tool mark width distribution characteristics, the angular point quantity and the pixel point clustering set through the tool mark density model, wherein the tool mark density model comprises:
wherein ,
the density of the cutting mark is the same as that of the cutting mark,
is as follows
The width of each knife mark is equal to the width of each knife mark,
is the average value of the width of the cutter mark,
for the number of corner points,
for the number of pixel point cluster sets,
is the number of rays.
The tool mark density model represents the tool mark characteristics of one drill bit tool mark subregion, specifically analyzes each drill bit tool mark subregion, combines the number of angular points in the drill bit tool mark subregion, the number of pixel point clustering sets and the corresponding tool mark width distribution, and the tool mark density is inversely proportional to the product of the number of angular points and the number of pixel point clustering sets and is directly proportional to the tool mark width distribution characteristics. The tool mark density represents the specific morphological characteristics of each drill bit tool mark subregion, and each drill bit tool mark subregion is analyzed in more detail, so that the geological type is more accurately identified.
And step S4: and obtaining the geological density of the stratum according to the significance of the concentric circles of the tool marks and the density of the tool marks, and finishing the identification of the geological type according to the geological density of the stratum.
According to the significance of the concentric circles of the obtained tool marks of the tool mark area of the drill bit
The density of the tool marks corresponding to the tool mark sub-regions of each drill bit
Comprehensively evaluating the compactness of the rock mass material of the corresponding tunnel face of the image to construct the geological compactness of the stratum
. The method for constructing the stratum geological density according to the significance of the concentric circles and the cutter mark density comprises the following steps:
wherein ,
is a natural constant and is a natural constant,
in order to obtain the density of the stratum geology,
the accumulated value of the tool mark density of all drill bit tool mark sub-areas is obtained. And accumulating the tool mark densities corresponding to each drill bit tool mark sub-region to obtain a tool mark density accumulated value, mapping the obtained tool mark density accumulated value to an exponential function with a natural constant as a base, and taking the product of the mapping value of the tool mark density accumulated value and the significance of the concentric circles of the tool marks as the geological density of the stratum.
Significance of tool mark concentric circles in tool mark area of drill bit
The overall characteristics of the tool mark area are represented, and the tool mark density of each drill bit tool mark sub-area is characterized by the characteristics of each drill bit tool mark sub-area, namely the local characteristics of the tool mark area. According to the combination of the two parameters of the concentric circle significance and the tool mark significance, the morphological characteristics of the tool mark are represented, the whole is considered, and the local part is included, so that the geological type is more accurately identified.
Further, the geological type recognition is completed according to the obtained geological density of the stratum, specifically:
the various geology comprises but is not limited to hard rock stratum, hard rock broken bottom layer, uneven soft and hard stratum, clay stratum and sand-containing water-rich stratum, and the various geology is classified and marked into three types of hard rock stratum, uneven soft and hard stratum and soft bottom layer by manpower. Dividing the stratum with the geological density of the stratum being greater than the first preset density threshold into a hard rock stratum, dividing the stratum with the geological density being less than the second preset density threshold into a soft stratum, dividing the stratum with the geological density being less than or equal to the first preset density threshold and being greater than or equal to the second preset density threshold into a stratum with uneven hardness, and completing the identification of the geological type, wherein the first preset density threshold is greater than the second preset density threshold.
In the embodiment of the invention, the stratum density corresponding to the hard rock stratum
Is recorded as
(ii) a Stratum density corresponding to stratum with uneven hardness
Maximum value is noted
，
Minimum value is noted
(ii) a Stratum geology density corresponding to soft stratum
Maximum value is noted
. Recording a first preset density threshold value as
The second preset density threshold value is recorded as
. Wherein the first preset density threshold value
Stratum density corresponding to through hard rock stratum
Minimum value of (2)
Density of stratum corresponding to stratum with uneven hardness
Maximum value of
Is expressed by the mean value of (i.e.)
. Second preset density threshold
Density of stratum corresponding to stratum with uneven hardness
Minimum value of (2)
Stratum geological density corresponding to soft stratum
Maximum value of
Is expressed by the mean value of (i.e.)
。
In conclusion, the tool mark image data formed on the rock body by the drill bit in the working process of the rock breaker are collected, the concentric circle significance and the tool mark density are obtained according to the collected tool mark image data, the stratum geological density is further represented according to the concentric circle significance and the tool mark density, and the geological type is identified according to the stratum geological density. According to the method, the overall characteristics of the tool mark image are represented according to the significance of the concentric circles, the local characteristics of the tool mark image are represented according to the density of the tool marks, the geological type is accurately identified through the combination of the overall characteristics and the local characteristics, and the geological type is identified according to the tool mark image formed on the rock body by the drill bit, so that the cost is lower compared with the prior art. Therefore, the invention has lower cost while ensuring the accuracy.
It should be noted that: the precedence order of the above embodiments of the present invention is only for description, and does not represent the merits of the embodiments. The processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A method for identifying a geological type, the method comprising:
acquiring a denoised face image generated by the excavation of a rock breaker, taking a part of the face image with a gray value larger than a preset first threshold value as a first screening area, wherein the first screening area comprises a plurality of connected domains, and screening out a bit tool mark sub-area of the connected domains according to the fitting degree of the connected domains and a circle;
obtaining the circle centers of the corresponding drill bit tool mark sub-regions according to the fitting circle corresponding to each drill bit tool mark sub-region, and obtaining the significance of the concentric circles of the tool marks according to the position distribution characteristics between the circle centers of the drill bit tool mark sub-regions and the number of the drill bit tool mark sub-regions;
obtaining the tool mark width of each position of the drill bit tool mark subregion, detecting the angular point quantity of the drill bit tool mark subregion, and obtaining the tool mark density according to the width distribution characteristic of the tool mark width and the angular point quantity;
and obtaining the geological density of the stratum according to the significance of the concentric circles of the tool marks and the density of the tool marks, and finishing the identification of the geological type according to the geological density of the stratum.
2. The geological type recognition method according to claim 1, wherein said location distribution feature obtaining method comprises:
calculating the Euclidean distance between every two circle centers of the drill bit cutting mark sub-regions, calculating the standard deviation of the Euclidean distance, arranging the Euclidean distances from small to large, and screening the mutation values through a BG (Block segmentation) algorithm; calculating a first mean value of the mutation value, screening out second mean values corresponding to other Euclidean distances except the mutation value, and obtaining a convex hull formed by the circle centers of the sub-regions of the drill bit tool marks according to a convex hull algorithm to obtain the area of the convex hull; if the mutation value does not exist, the first mean value and the second mean value are equal;
and taking the standard deviation, the first mean, the second mean and the area of the convex hull as the position distribution characteristic.
3. The geological type identification method according to claim 2, wherein the step of obtaining the significance of the concentric circles of the tool marks according to the position distribution characteristics between the circle centers of the tool mark sub-regions of the drill bit and the number of the tool mark sub-regions of the drill bit comprises the following steps:
obtaining the significance of the concentric circles of the tool marks through a tool mark concentric circle significance calculation model according to the position distribution characteristics between the circle centers of the sub-regions of the tool marks of the drill bit and the number of the sub-regions of the tool marks of the drill bit, wherein the tool mark concentric circle significance calculation model comprises:
wherein ,
the significance of the concentric circles of the tool marks,
is the first mean value
Is the second average value of the first average value,
is the area of the convex hull and,
is the standard deviation of the euclidean distance,
the number of the drill bit cutting mark sub-areas,
is a preset adjustment factor.
4. The geological type recognition method according to claim 1, wherein the width distribution characteristic of the cutting mark width comprises:
constructing a three-dimensional coordinate system based on the positions of pixel points in the drill bit tool mark sub-area and the tool mark widths corresponding to the pixel points, wherein the x axis of the three-dimensional coordinate system is the horizontal axis of the image coordinate system, the y axis is the longitudinal axis of the image coordinate system, and the z axis is the tool mark width; mapping each pixel point in the drill bit cutter mark sub-area to the three-dimensional coordinate system; clustering pixels in the three-dimensional coordinate system through a clustering algorithm in the three-dimensional coordinate system to obtain a pixel clustering set; and taking the difference between the width of each knife mark and the mean value of the widths of the knife marks and the number of the pixel point clustering sets as the width distribution characteristics of the widths of the knife marks.
5. The geological type recognition method as claimed in claim 4, wherein the step of obtaining the density of the tool marks according to the width distribution features of the tool mark width and the number of the corner points comprises:
obtaining the tool mark density according to the tool mark width distribution characteristics, the angular point quantity and the pixel clustering set through a tool mark density model, wherein the tool mark density model comprises:
wherein ,
the density of the knife mark is the density of the knife mark,
is a first
The width of each knife mark is equal to the width of each knife mark,
is the average value of the widths of the tool marks,
for the number of said corner points,
for the number of the pixel point cluster sets,
is the number of said rays.
6. The geological type recognition method of claim 1, wherein the obtaining of the geological density of the stratum according to the significance of the concentric circles of the tool marks and the density of the tool marks comprises:
and accumulating the cutter mark densities to obtain a cutter mark density accumulated value, mapping the cutter mark density accumulated value to an exponential function with a natural constant as a base, and taking the product of the mapping value and the corresponding concentric circle significance as the geological density of the stratum.
7. The method for identifying the geological type according to claim 1, wherein the identification of the geological type according to the geological density of the stratum comprises the following steps:
dividing the stratum with the geological density of the stratum being greater than the first preset density threshold into a hard rock stratum, dividing the stratum with the geological density being less than the second preset density threshold into a soft stratum, dividing the stratum with the geological density being less than or equal to the first preset density threshold and being greater than or equal to the second preset density threshold into a stratum with uneven hardness, and enabling the first preset density threshold to be greater than the second preset density threshold.
8. The geological type identification method according to claim 1, wherein the step of screening out the drill bit tool mark subarea of the connected component according to the fitting degree of the connected component and the circle comprises the following steps:
and recording the region where the pixel point set corresponding to the circle with the fitting degree larger than a preset fitting degree threshold value is located as a drill bit tool mark sub-region.
9. The geological type identification method according to claim 1, wherein the obtaining of the tool mark width of each position of the drill bit tool mark sub-region comprises:
and taking the center of a fitting circle corresponding to the drill bit cutting mark sub-region as a starting point, obtaining rays in all directions, and taking the length of the line of the rays in the edge of the drill bit cutting mark sub-region as the width of the cutting mark.
10. The geological type recognition method as claimed in claim 1, wherein the connected component obtaining method in the first screening area comprises:
and carrying out clustering analysis on the pixel points contained in the first screening area by using a spectral clustering algorithm to obtain a plurality of connected domains.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110091078A1 (en) * | 2007-08-31 | 2011-04-21 | Josselin Kherroubi | Identifying geological features in an image of an underground formation surrounding a borehole |
| US20120323495A1 (en) * | 2010-02-05 | 2012-12-20 | Hang Zhou | Rock property measurements while drilling |
| CN106225770A (en) * | 2016-08-26 | 2016-12-14 | 招商局重庆交通科研设计院有限公司 | Tunnel tunnel face geology multidimensional digitized record recognition methods and system |
| CN112990227A (en) * | 2021-02-08 | 2021-06-18 | 中国铁建重工集团股份有限公司 | Face geology detection method |
| WO2022100609A1 (en) * | 2020-11-11 | 2022-05-19 | 上海中联重科桩工机械有限公司 | Geological hardness identification method and system for engineering machinery |
-
2022
- 2022-12-07 CN CN202211563539.9A patent/CN115661133B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110091078A1 (en) * | 2007-08-31 | 2011-04-21 | Josselin Kherroubi | Identifying geological features in an image of an underground formation surrounding a borehole |
| US20120323495A1 (en) * | 2010-02-05 | 2012-12-20 | Hang Zhou | Rock property measurements while drilling |
| CN106225770A (en) * | 2016-08-26 | 2016-12-14 | 招商局重庆交通科研设计院有限公司 | Tunnel tunnel face geology multidimensional digitized record recognition methods and system |
| WO2022100609A1 (en) * | 2020-11-11 | 2022-05-19 | 上海中联重科桩工机械有限公司 | Geological hardness identification method and system for engineering machinery |
| CN112990227A (en) * | 2021-02-08 | 2021-06-18 | 中国铁建重工集团股份有限公司 | Face geology detection method |
Non-Patent Citations (2)
| Title |
|---|
| XINGZHI BA ET AL.: "Development Status of Digital Detection Technology for Unfavorable Geological Structures in Deep Tunnels", 《KSCE JOURNAL OF CIVIL ENGINEERING》 * |
| 刘明阳 等: "基于盾构机运行参数的局部切空间排列与Xgboost 融合的地质类型识别", 《中南大学学报(自然科学版)》 * |
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