CN115880275B - Remote control method of rock drilling and splitting integrated machine - Google Patents
Remote control method of rock drilling and splitting integrated machine Download PDFInfo
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Abstract
The invention relates to the technical field of equipment control, in particular to a remote control method of a rock drilling and splitting integrated machine, which comprises the steps of obtaining a rock surface area through dividing a gray level image of the rock surface to be mined, obtaining smoothness according to gray level values of pixel points in the rock surface area, and obtaining target pixel points according to the smoothness; dividing the target pixel point into at least two clusters by utilizing an improved DBSCAN density clustering algorithm, and determining an optimal drilling position according to the clusters; setting an initial hydraulic value, splitting an optimal drilling position, acquiring a second gray level image of rock fragments discharged in the splitting process, determining a motion pixel point according to the adjacent second gray level image, further acquiring a rock fragment area, and determining an actual pixel point according to the rock fragment area; and determining an actual rock chipping area according to the actual pixel points, further obtaining a splitting effect index, and adjusting an initial hydraulic value according to the splitting effect index. And optimizing the splitting effect according to the adjusted hydraulic value.
Description
Technical Field
The invention relates to the technical field of equipment control, in particular to a remote control method of a rock drilling and splitting integrated machine.
Background
The rock drilling and splitting integrated machine is mainly used for exploitation and excavation of rock, and relates to equipment for tunnel, mine and other engineering. The rock drilling and splitting integrated machine adopts an electrohydraulic integrated control mode to split the rock, and rapidly expands and splits the rock so as to facilitate efficient breaking of the rock, and the actions of the rock drilling and splitting integrated machine are all remotely controlled. The driver can use remote control rock drilling and splitting integrated machine to drill, pair holes, split and other operations on the rock in the cab.
In the prior art, the drilling and splitting integrated machine obtains the optimal drilling position through a DBSCAN density clustering algorithm, the drilling and splitting integrated machine splits the optimal drilling position through hydraulic control, and the discharged rock fragments are analyzed in the splitting process to adjust the proper hydraulic pressure so that the splitting effect of the drilling and splitting integrated machine is optimal; the DBSCAN density clustering algorithm obtains the optimal drilling position through the neighborhood sample number threshold value and the distance measurement value, but the traditional distance measurement value is flexible to obtain and wide in range, so that the optimal drilling position is obtained inaccurately, the hydraulic control is affected, and the rock drilling and splitting integrated machine cannot obtain the optimal splitting effect.
Disclosure of Invention
In order to solve the technical problem that the optimal splitting effect cannot be obtained due to inaccurate optimal drilling positions, the invention aims to provide a remote control method of a rock drilling and splitting integrated machine, and the adopted technical scheme is as follows:
an embodiment of the invention provides a remote control method of a rock drilling and splitting integrated machine, which comprises the following steps:
acquiring a rock surface image to be mined, obtaining a corresponding gray image, obtaining a rock surface area by dividing the gray image, obtaining the smoothness of each pixel point based on the gray value of the pixel point in the rock surface area, and obtaining a target pixel point according to the smoothness; dividing the target pixel point into at least two clusters by utilizing an improved DBSCAN density clustering algorithm, wherein one cluster corresponds to one drilling position to be selected, and determining the optimal drilling position according to the smoothness of the target pixel point in the drilling position to be selected;
setting an initial hydraulic value, splitting an optimal drilling position, collecting each frame of image of rock fragments continuously discharged in the splitting process, acquiring a corresponding second gray level image, and determining a motion pixel point according to the gray level value of the corresponding pixel point in the adjacent second gray level image; taking the area formed by the moving pixel points as a rock debris area, and determining actual pixel points according to the rock debris areas representing the same area in all the second gray level images;
Determining an actual rock fragment area according to the actual pixel points, acquiring a splitting effect index under an initial hydraulic value according to the actual rock fragment area, and adjusting the initial hydraulic value according to the splitting effect index;
the specific method for dividing the target pixel point into at least two clusters by utilizing the improved DBSCAN density clustering algorithm comprises the following steps: taking a target pixel point as a circle center, acquiring a circular neighborhood with a set size, and acquiring a distance measurement value between each neighborhood pixel point and the central pixel point according to the gray difference absolute value of the central pixel point of the circular neighborhood and each neighborhood pixel point, wherein the neighborhood pixel point is the target pixel point; and determining the number of the effective pixels in the circular neighborhood according to the distance measurement value, and determining the effective pixels in the corresponding circular neighborhood as a cluster when the number of the effective pixels meets the neighborhood sample number threshold.
Further, the method for obtaining the smoothness of each pixel point based on the gray value of the pixel point in the rock surface area comprises the following steps:
taking each pixel point in the rock surface area as a central pixel point to acquire a neighborhood with a set size, calculating the gray difference absolute value between each neighborhood pixel point and the central pixel point, taking the inverse number of the sum of all the gray difference absolute values in each neighborhood as an index of a natural constant e, and taking the obtained result as a first result; setting a gray difference absolute value threshold, obtaining a first number of neighborhood pixel points, in which the gray difference absolute value in each neighborhood is larger than the gray difference absolute value threshold, calculating a ratio of the first number to the total number of the neighborhood pixel points in the corresponding neighborhood, taking the difference value of a constant 1 and the ratio as a second result, and calculating the product of the second result and the first result as smoothness of the corresponding center pixel point.
Further, the method for obtaining the distance measurement value between each neighborhood pixel point and the center pixel point includes:
taking the absolute value of the gray difference between the central pixel point of the circular neighborhood and each neighborhood pixel point as a first value, taking the opposite number of the first value as an index of a natural constant e, and taking the obtained result as a third result;
taking any one neighborhood pixel point in the circular field of the central pixel point as a target neighborhood pixel point, taking the target neighborhood pixel point as a circle center, setting a circular neighborhood with the same size as the central pixel point, and taking the neighborhood pixel points which exist in the circular neighborhood of the central pixel point and the same position in the circular neighborhood of the target neighborhood pixel point as a matching pair;
calculating the gray difference absolute value of each neighborhood pixel point in the target neighborhood pixel point and the round neighborhood thereof as a second value; respectively calculating the absolute value of the difference between the first value and the second value corresponding to each matching pair to obtain a mean value of the absolute value of the difference, taking the opposite number of the mean value of the absolute value of the difference as an index of a natural constant e, and taking the obtained result as a fourth result;
and taking the product of the third result and the fourth result as a distance measurement value of the target neighborhood pixel point and the center pixel point.
Further, the method for determining the number of effective pixel points in the circular neighborhood according to the distance measurement value comprises the following steps:
and setting a distance measurement value threshold value, and acquiring the number of target pixel points with the distance measurement value larger than the distance measurement value threshold value as the number of effective pixel points.
Further, the method for determining the optimal drilling position according to the smoothness of the target pixel point in the drilling position to be selected comprises the following steps:
taking the result of adding the smoothness of the target pixel points in the drilling positions to be selected as the confidence coefficient corresponding to the drilling positions to be selected, and respectively carrying out normalization processing on each obtained confidence coefficient to obtain normalized confidence coefficients; and setting a confidence coefficient threshold value, and when the normalized confidence coefficient is larger than the confidence coefficient threshold value, obtaining the position of the selected drill hole corresponding to the normalized confidence coefficient as the optimal drill hole position.
Further, the method for determining the motion pixel according to the gray value of the corresponding pixel in the adjacent second gray image includes:
taking any one second gray level image as a target second gray level image, taking any one pixel point in the target second gray level image as a first pixel point, taking the pixel point with the same position as the first pixel point as a second pixel point in the second gray level image adjacent to the target second gray level image, calculating the gray level difference absolute value between the first pixel point and the second pixel point, when the gray level difference absolute value is not equal to 0, acquiring a set number of pixel points under the second pixel point as sampling points, taking the pixel point with the smallest gray level difference between the sampling points and the first pixel point as a third pixel point, respectively setting first neighborhoods with the same size for the first pixel point and the third pixel point, respectively taking the t pixel point in the first neighborhoods of the first pixel point and the t pixel point in the first neighborhoods of the third pixel point as a pair, respectively calculating the difference absolute value between the two first neighborhoods as a molecular gray level pair absolute value, taking the largest difference value between the first pixel pair as a first average value and a fifth pixel value as a fifth pixel value, and taking the difference value between the first pixel pair as a fifth pixel value and a fifth pixel value as a corresponding value, and a fifth pixel value, and obtaining a similar result; and setting a similarity value threshold, and determining the first pixel point as a motion pixel point when the similarity value is larger than the similarity value threshold.
Further, the method for determining the actual pixel point according to the rock debris area representing the same area in all the second gray level images comprises the following steps:
determining center points of rock debris areas representing the same area in all second gray level images, projecting all the center points to the same position on the same plane, and projecting all the motion pixel points in the rock debris areas to the same plane according to the positions corresponding to the center points to obtain projection areas on the plane; the method comprises the steps of obtaining the number of repeated projection of each pixel point in a projection area, taking the ratio of the number of repeated projection of each pixel point to the total number of projected plane as a discrimination value, setting a discrimination value threshold, and confirming the corresponding moving pixel point as an actual pixel point of a rock debris area when the discrimination value is larger than the discrimination value threshold.
Further, the method for obtaining the splitting effect index under the initial hydraulic value according to the actual rock fragment area comprises the following steps:
and acquiring the number and the area average value of the actual rock fragment areas, taking the inverse number of the product of the area average value and the number as an index of a natural constant e, and taking the obtained result as a splitting effect index.
Further, the method for adjusting the initial hydraulic value according to the splitting effect index comprises the following steps:
setting a splitting effect range, and when the splitting effect index meets the splitting effect range, not adjusting an initial hydraulic value; when the splitting effect index does not meet the splitting effect range, calculating a difference value between the constant 2 and the splitting effect index, and taking the product of the initial hydraulic value and the difference value as the adjusted hydraulic value.
The invention has the following beneficial effects: acquiring a rock surface image to be mined, obtaining a corresponding gray image, and dividing the gray image to obtain a rock surface area, so that the rock surface is conveniently and directly analyzed, and the interference of part of external factors is avoided; the smoothness of each pixel point is obtained based on the gray value of the pixel point in the rock surface area, so that the possibility of obtaining the optimal drilling position is improved; acquiring a circular neighborhood with a set size by taking a target pixel point as a circle center, setting a circular neighborhood with the same size as the center pixel point according to the gray difference absolute value of the center pixel point and each neighborhood pixel point of the circular neighborhood, simultaneously taking the neighborhood pixel point as the circle center, analyzing the gray difference change of the neighborhood pixel point and the center pixel point, further acquiring a distance metric value between each neighborhood pixel point and the center pixel point, determining the number of effective pixel points in the circular neighborhood according to the distance metric value, further improving the possibility of acquiring the optimal drilling position, and avoiding the interference of other pixel points; when the number of the effective pixels meets the threshold value of the number of the neighborhood samples, determining the effective pixels in the corresponding circular neighborhood as a cluster, wherein one cluster corresponds to one hole position to be selected, determining the optimal hole position according to the smoothness of the effective pixels in the hole position to be selected, and ensuring that the obtained optimal hole position is the flattest, so that the stress is more uniform when splitting is carried out, and the splitting effect is better; setting an initial hydraulic value, splitting an optimal drilling position, collecting each frame of image of rock fragments continuously discharged in the splitting process, acquiring corresponding second gray images, determining a moving pixel point according to gray values of corresponding pixel points in adjacent second gray images, acquiring a rock fragment area through the moving pixel point, determining an actual pixel point of the rock fragment area according to the rock fragment areas representing the same area in all second gray images, acquiring an actual rock fragment area according to the actual pixel points, and analyzing the splitting effect of the rock drilling splitting integrated machine under the initial hydraulic pressure more accurately through the actual rock fragment areas; according to the method, a splitting effect index under an initial hydraulic value is obtained according to an actual rock chipping area, and the hydraulic value is adjusted according to the splitting effect index, so that the hydraulic value of the rock drilling and splitting integrated machine is optimal, the rock drilling and splitting integrated machine is controlled to achieve the optimal splitting effect, and the working efficiency of the rock drilling and splitting integrated machine is improved.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for remotely controlling a rock drilling and splitting integrated machine according to an embodiment of the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following is a detailed description of a specific implementation, structure, characteristics and effects of a remote control method for a rock drilling and splitting integrated machine according to the invention with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
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 specifically describes a specific scheme of a remote control method of a rock drilling and splitting integrated machine provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of a remote control method of a rock drilling and splitting integrated machine according to an embodiment of the invention is shown, the method includes the following steps:
step S1: acquiring a rock surface image to be mined, obtaining a corresponding gray image, obtaining a rock surface area by dividing the gray image, obtaining the smoothness of each pixel point based on the gray value of the pixel point in the rock surface area, and obtaining a target pixel point according to the smoothness; dividing the target pixel point into at least two clusters by utilizing an improved DBSCAN density clustering algorithm, wherein one cluster corresponds to one drilling position to be selected, and determining the optimal drilling position according to the smoothness of the target pixel point in the drilling position to be selected;
specifically, the image acquisition module is arranged on the rock drilling and splitting integrated machine to acquire the image of the rock surface to be mined, the acquired image is an RGB image, and the acquired RGB image is subjected to gray processing by a weighted average method to obtain the gray image of the rock surface to be mined. The weighted average method is a well-known technique, and will not be described in detail herein.
According to the scheme, the gray level image of the rock surface to be mined is segmented through an Ojin threshold segmentation algorithm, the rock is taken as a foreground, a rock part is removed as a background, and a rock surface area in the gray level image is obtained after segmentation. The division algorithm of the oxford threshold is a known technique, and will not be described in detail here.
Analyzing the pixel points in the rock surface area, obtaining the smoothness of each pixel point, and obtaining the target pixel point according to the smoothness, wherein the operation is as follows:
(1) Taking each pixel point in the rock surface area as a central pixel point to acquire a neighborhood with a set size, calculating the gray difference absolute value between each neighborhood pixel point and the central pixel point, taking the inverse number of the sum of all the gray difference absolute values in each neighborhood as an index of a natural constant e, and taking the obtained result as a first result; setting a gray difference absolute value threshold, obtaining a first number of neighborhood pixel points, in which the gray difference absolute value in each neighborhood is larger than the gray difference absolute value threshold, calculating a ratio of the first number to the total number of the neighborhood pixel points in the corresponding neighborhood, taking the difference value of a constant 1 and the ratio as a second result, and calculating the product of the second result and the first result as smoothness of the corresponding center pixel point.
Taking a pixel p in a rock surface area as an example, acquiring 3*3 neighborhood of the pixel p, and calculating the absolute value of gray difference between the pixel p and the i-th neighborhood
Wherein i=1, 2, 3, …, 8;
the gray value of the ith neighborhood pixel point;
is the gray value of pixel p. The scheme sets the absolute value threshold of gray difference value as 10, and obtains
Making a judgment such that n=0, when
When n=n+1; when (when)
When n=n; corresponding to the neighborhood pixel point in the neighborhood of the pixel point p
All are carried out
Judging to obtain a final n value, and further obtaining the smoothness R of the pixel point p, wherein an obtaining formula of the smoothness R is as follows:
wherein n is the first number of neighborhood pixel points in which the absolute value of the gray difference value in the neighborhood of the pixel point p is larger than the threshold value of the absolute value of the gray difference value;
the absolute value of the gray difference between the pixel point of the i-th neighborhood and the pixel point p;
is a natural constant;
is the smoothness of the pixel point p.
It should be noted that the larger n is, the more obvious the gray scale difference is in the neighborhood of the pixel point p, the more uneven the rock area is in the neighborhood of the pixel point p,
the smaller n is with
Negative correlation is formed;
the larger the gray difference value between the neighborhood pixel point and the pixel point p, the more obvious the gray difference between the neighborhood pixel point and the pixel point p, the higher the possibility that the rock area in the neighborhood of the pixel point p is uneven, 
The smaller the size of the product,
and (3) with
Negative correlation is formed; therefore, the larger R is, the flatter the rock area in the vicinity of the pixel point p is, the more uniform stress is applied during splitting, and the better the splitting effect is.
The smoothness of each pixel point in the rock surface area is obtained by a method of obtaining the smoothness of the pixel point p.
(2) Setting a smoothness threshold, carrying out normalization processing on the obtained smoothness to obtain normalized smoothness, and setting a pixel point corresponding to the normalized smoothness as a target pixel point when the normalized smoothness is larger than the smoothness threshold.
In the scheme, a smoothness threshold value is set to be 0.8, and a pixel point p is taken as an example, when the normalized smoothness of the pixel point p is greater than the smoothness threshold value, the pixel point p is set as a target pixel point, and reservation and further analysis are carried out; when the normalized smoothness of the pixel point p is less than or equal to the smoothness threshold, the pixel point p is not reserved and analyzed.
And determining target pixel points in the rock surface area according to the smoothness threshold value.
And (3) performing an improved DBSCAN density clustering algorithm on the target pixel points. In the invention, a neighborhood in a DBSCAN density clustering algorithm is set as a circular neighborhood taking a target pixel point as a circle center and D as a radius, wherein D is the radius of a drilling device on a rock drilling and splitting integrated machine. A clustering cluster obtained by final clustering is a drilling position of a rock surface area, so that the DBSCAN density clustering algorithm influences the selection of the drilling position, and the clustering effect of the traditional DBSCAN density clustering algorithm depends on a neighborhood sample number threshold value and a distance metric value during clustering.
The specific method for dividing the target pixel into at least two clusters by utilizing the improved DBSCAN density clustering algorithm through the obtained target pixel comprises the following steps: taking a target pixel point as a circle center, acquiring a circular neighborhood with a set size, and acquiring a distance measurement value between each neighborhood pixel point and the central pixel point according to the gray difference absolute value of the central pixel point of the circular neighborhood and each neighborhood pixel point, wherein the neighborhood pixel point is the target pixel point; and determining the number of the effective pixels in the circular neighborhood according to the distance measurement value, and determining the effective pixels in the corresponding circular neighborhood as a cluster when the number of the effective pixels meets the neighborhood sample number threshold.
The specific operation steps are as follows:
(1) According to the gray level difference absolute value of the central pixel point of the circular neighborhood and each neighborhood pixel point, the process of obtaining the distance measurement value between each neighborhood pixel point and the central pixel point is as follows:
taking the absolute value of the gray difference between the central pixel point of the circular neighborhood and each neighborhood pixel point as a first value, taking the opposite number of the first value as an index of a natural constant e, and taking the obtained result as a third result; taking any one neighborhood pixel point in the circular field of the central pixel point as a target neighborhood pixel point, taking the target neighborhood pixel point as a circle center, setting a circular neighborhood with the same size as the central pixel point, and taking the neighborhood pixel points which exist in the circular neighborhood of the central pixel point and the same position in the circular neighborhood of the target neighborhood pixel point as a matching pair; calculating the gray difference absolute value of each neighborhood pixel point in the target neighborhood pixel point and the round neighborhood thereof as a second value; respectively calculating the absolute value of the difference between the first value and the second value corresponding to each matching pair to obtain a mean value of the absolute value of the difference, taking the opposite number of the mean value of the absolute value of the difference as an index of a natural constant e, and taking the obtained result as a fourth result; and taking the product of the third result and the fourth result as a distance measurement value of the target neighborhood pixel point and the center pixel point.
Taking a target pixel point q as an example, acquiring a circular neighborhood taking the target pixel point q as a circle center and taking D as a radius, wherein D is a drilling hole on the rock drilling and splitting integrated machineThe radius of the device is equal to the number of the target pixel points in the circular neighborhood of the target pixel point q
Selecting any one of the neighborhood pixel points in the circular neighborhood of the target pixel point q as a target neighborhood pixel point e, wherein the neighborhood pixel point is the target pixel point, and the neighborhood pixel points in the circular neighborhood of the target pixel point are removed; acquiring a circular neighborhood with a target neighborhood pixel point e as a circle center and D as a radius, and taking a neighborhood pixel point existing in the same position in the circular neighborhood of the target neighborhood pixel point q and the circular neighborhood of the target neighborhood pixel point e as a matching pair; obtaining the matching pair number of the neighborhood pixel points in the circular neighborhood of the target pixel point q and the circular neighborhood of the target neighborhood pixel point e
. Based on the matching pair number
Obtaining a distance measurement value of a target neighborhood pixel point e and a target pixel point q, and obtaining the distance measurement value
The formula of (2) is:
wherein,,
a distance measurement value of a target neighborhood pixel point e and a target pixel point q;
the gray value of the target pixel point q; 
For the target neighborhood pixel point eGray values of (2);
the matching pair number of the neighborhood pixel points in the circular neighborhood of the target pixel point q and the circular neighborhood of the target neighborhood pixel point e;
the gray value of the ith neighborhood pixel point in the circular neighborhood of the target pixel point q;
the gray value of the ith neighborhood pixel point in the circular neighborhood of the target neighborhood pixel point e;
is a natural constant which is used for the production of the high-temperature-resistant ceramic material,
as a function of absolute value.
It should be noted that the number of the substrates,
the smaller the target neighborhood pixel point e is, the same as the gray value of the target pixel point q is, the more similar the target neighborhood pixel point e is to the target pixel point q,
the larger the size of the container,
and (3) with
Negative correlation is formed;
the smaller the circular neighborhood of the target pixel point q is, the more similar the gray scale variation in the circular neighborhood of the target neighborhood pixel point e is, the more similar the target pixel point q is to the target neighborhood pixel point e,
the larger the size of the container,
and (3) with
Negative correlation is formed; thus, the first and second substrates are bonded together,
the larger the target pixel point q is, the more similar the target neighborhood pixel point e is, and the flatter the circular neighborhood of the target pixel point q is.
According to the method for obtaining the distance metric value of the target neighborhood pixel point e and the target pixel point q, the distance metric value of each neighborhood pixel point in the circular neighborhood of the target pixel point q and the target pixel point q is obtained.
(2) The specific method for determining the number of effective pixel points in the circular neighborhood according to the distance measurement value comprises the following steps:
and setting a distance measurement value threshold value, and acquiring the number of target pixel points with the distance measurement value larger than the distance measurement value threshold value as the number of effective pixel points.
In the scheme, a distance measurement value threshold value is set to be 0.9, taking a circular neighborhood of a target pixel point q as an example, the number m=0, and when the distance measurement value is greater than the distance measurement value threshold value, m=m+1; when the distance metric value is less than or equal to the distance metric value threshold, m=m; after the distance measurement values in the circular neighborhood of the target pixel point q are judged, the final number m is obtained, wherein the number m represents the number of the target pixel points in the circular neighborhood of the target pixel point q which can be used as effective pixel points; the neighborhood sample number threshold value of the circular neighborhood of the target pixel point q set by the scheme is
When (when)
In this case, the target pixel point in the circular neighborhood of the target pixel point q is formedThe reserved cluster is expressed as a hole position to be selected; when (when)
And when the pixel points are in the circular neighborhood, one cluster formed by the target pixel points in the circular neighborhood of the target pixel point q is not reserved.
And acquiring all the clusters which can be reserved in the rock surface area according to a method for determining whether the clusters at the target pixel point q can be reserved. Assuming that M reserved clusters are obtained, each reserved cluster corresponds to one hole position to be selected, and then M hole positions to be selected are obtained.
The specific method for determining the optimal drilling position according to the obtained drilling position to be selected is as follows: taking the result of adding the smoothness of the target pixel points in the drilling positions to be selected as the confidence coefficient corresponding to the drilling positions to be selected, and respectively carrying out normalization processing on each obtained confidence coefficient to obtain normalized confidence coefficients; and setting a confidence coefficient threshold value, and when the normalized confidence coefficient is larger than the confidence coefficient threshold value, obtaining the position of the selected drill hole corresponding to the normalized confidence coefficient as the optimal drill hole position.
Taking a drilling position to be selected as an example, acquiring the smoothness of a target pixel point in the drilling position to be selected, and acquiring the confidence coefficient of the drilling position to be selected according to the smoothness
The formula of (2) is:
wherein,,
the number of the target pixel points in the drilling position to be selected is the number of the target pixel points in the drilling position to be selected;
the smoothness of the ith target pixel point in the drilling position to be selected is obtained;
and the confidence of the position of the drilling hole to be selected.
It should be noted that the number of the substrates,
the larger the size of the container,
the larger the surface area of the drilling position to be selected is, the smoother the surface area is, and the more evenly the applied force can be dispersed into the rock when drilling is carried out, so that the better the splitting effect is;
the smaller the size of the product,
the smaller the surface area of the selected drilling location is, the more uneven the surface area is, the more likely the applied force is uneven when dispersed when drilling, and the worse the splitting effect is.
And acquiring the confidence degrees of all the positions of the holes to be selected according to the method for acquiring the confidence degrees of the positions of the holes to be selected.
And carrying out normalization processing on the obtained confidence coefficient to obtain normalized confidence coefficient, wherein the confidence coefficient threshold value is set to be 0.8, and when the normalized confidence coefficient is larger than the confidence coefficient threshold value, the position of the drill hole to be selected corresponding to the normalized confidence coefficient is the optimal drill hole position.
Step S2: setting an initial hydraulic value, splitting an optimal drilling position, collecting each frame of image of rock fragments continuously discharged in the splitting process, acquiring a corresponding second gray level image, and determining a motion pixel point according to the gray level value of the corresponding pixel point in the adjacent second gray level image; taking the area formed by the moving pixel points as a rock debris area, and determining actual pixel points according to the rock debris areas representing the same area in all the second gray level images;
specifically, according to the optimal drilling position obtained in the step S1, a control person can control the rock drilling and splitting integrated machine through a remote control device, the rock drilling and splitting integrated machine is enabled to move to the corresponding optimal drilling position through remote control, an initial hydraulic value is set manually, and splitting is carried out on the optimal drilling position; the rock debris in the splitting process is continuously discharged by the rock drilling and splitting integrated machine, an image acquisition module arranged on the rock drilling and splitting integrated machine acquires a plurality of continuous discharged rock debris images, and gray processing is carried out on the acquired discharged rock debris images by a weighted average method to obtain a gray image of the discharged rock debris as a second gray image; according to the scheme, the second gray level image is analyzed, so that the splitting effect index under the initial hydraulic value is obtained.
The weighted average method is a well-known technique, and will not be described in detail herein.
According to the scheme, the motion pixel point is determined according to the gray value of the corresponding pixel point in the adjacent second gray level image, and the specific operation steps for obtaining the motion pixel point are as follows:
taking any one second gray level image as a target second gray level image, taking any one pixel point in the target second gray level image as a first pixel point, taking the pixel point with the same position as the first pixel point as a second pixel point in the second gray level image adjacent to the target second gray level image, calculating the gray level difference absolute value between the first pixel point and the second pixel point, when the gray level difference absolute value is not equal to 0, acquiring a set number of pixel points under the second pixel point as sampling points, taking the pixel point with the smallest gray level difference between the sampling points and the first pixel point as a third pixel point, respectively setting first neighborhoods with the same size for the first pixel point and the third pixel point, respectively taking the t pixel point in the first neighborhoods of the first pixel point and the t pixel point in the first neighborhoods of the third pixel point as a pair, respectively calculating the difference absolute value between the two first neighborhoods as a molecular gray level pair absolute value, taking the largest difference value between the first pixel pair as a first average value and a fifth pixel value as a fifth pixel value, and taking the difference value between the first pixel pair as a fifth pixel value and a fifth pixel value as a corresponding value, and a fifth pixel value, and obtaining a similar result; and setting a similarity value threshold, and determining the first pixel point as a motion pixel point when the similarity value is larger than the similarity value threshold.
As an example, a pixel point is arbitrarily selected as a first pixel point s in the target second gray level image Q, and a gray level value of the first pixel point s is obtained
And the coordinates of the first pixel point s in the target second gray level image Q
，
) Acquiring a second gray level image of the next adjacent moment of the target second gray level image Q
A second pixel point at the same coordinate as the first pixel point s
Determining a second pixel point
Gray value of (2)
Calculating a first pixel point s and a second pixel point
Absolute value of gray difference between
When C is equal to 0, the first pixel point s is a static pixel point; when C is not equal to 0, it indicates that the first pixel s may move, and further analysis is required for the first pixel s. From a priori knowledge, rock fragments fall in a vertical direction during discharge, so that the velocity is vertical downward, and thus for the firstTwo pixel points
Making a vertical straight line, and acquiring a second pixel point which is positioned on the vertical straight line
The 20 pixel points below are used as sampling points, a pixel point with the smallest gray level difference value with the first pixel point s is selected from the sampling points to be used as a third pixel point w, first neighborhoods of 3*3 are respectively set for the first pixel point s and the third pixel point w, similarity values of the first pixel point s and the third pixel point w are calculated, and the similarity values are obtained 
The formula of (2) is:
wherein,,
the gray value of the ith pixel point in the first adjacent area of the first pixel point s;
the gray value of the ith pixel point in the first adjacent area of the third pixel point w;
as a function of absolute value;
is a maximum function;
is the similarity value between the first pixel point s and the third pixel point w.
It should be noted that the number of the substrates,
the smaller, the more similar the matching pair of the first neighborhood of the first pixel point s and the first neighborhood of the third pixel point w is,
the larger; thus, the first and second substrates are bonded together,
the larger the first neighborhood of the first pixel point s and the first neighborhood of the third pixel point w are, the more similar the first pixel point s and the third pixel point w are, the more likely that the first pixel point s and the third pixel point w are the same pixel point, and the more likely that the first pixel point s is a motion pixel point.
The scheme sets the similarity threshold to 0.85 when
When the pixel value is larger than the similarity value threshold value, the first pixel point s is a motion pixel point; when (when)
And when the threshold value is smaller than or equal to the threshold value of the similarity value, the first pixel point s is a static pixel point.
And acquiring all the motion pixel points in each second gray level image according to the method for acquiring the motion pixel points.
And carrying out connected domain analysis on the moving pixel points to obtain rock fragment areas in the second gray level images, and obtaining actual rock fragment areas through the rock fragment areas, namely determining actual pixel points of the rock fragment areas through the rock fragment areas representing the same area in all the second gray level images, wherein the concrete operation is as follows:
Determining center points of rock debris areas representing the same area in all second gray level images, projecting all the center points to the same position on the same plane, and projecting all the motion pixel points in the rock debris areas to the same plane according to the positions corresponding to the center points to obtain projection areas on the plane; the method comprises the steps of obtaining the number of repeated projection of each pixel point in a projection area, taking the ratio of the number of repeated projection of each pixel point to the total number of projected plane as a discrimination value, setting a discrimination value threshold, and confirming the corresponding moving pixel point as an actual pixel point of a rock debris area when the discrimination value is larger than the discrimination value threshold.
Taking a rock debris area A in a target second gray level image Q as an example, acquiring a center point of the rock debris area A, wherein the center point is a motion pixel point with the smallest sum of Euclidean distances from the edge pixel points of the rock debris area A to the rock debris area A; determining a second gray level image based on the similarity value
A third pixel point corresponding to the center point of the rock fragment area A, a second gray level image
The third pixel point in (a) is the rock fragment area representing the rock fragment area A 
Thereby acquiring a second gray level image
Rock chip area denoted rock chip area a
The method comprises the steps of carrying out a first treatment on the surface of the And so on, acquiring rock fragment areas representing the rock fragment area A in all the second gray level images, which are respectively marked as
Wherein, the method comprises the steps of, wherein,
a rock debris area representing a rock debris area A in a 2 nd second gray level image after the target second gray level image Q;
for the purpose ofMark the second gray level image Q
The rock fragment area of the rock fragment area a is represented in the second gray scale image. Because the mine environment is complex and is easy to be disturbed by the outside, the acquired rock fragment areas representing the rock fragment area A are possibly inconsistent in different second gray level images, so the scheme is suitable for
Analyzing to determine the center points of all rock fragment areas representing the rock fragment area A, projecting all the center points to the same position on the same plane, projecting all the motion pixel points in the rock fragment area representing the rock fragment area A to the same plane according to the positions corresponding to the center points, and obtaining the projection areas on the plane
For the projection area
The analysis is performed on the pixel points in the image, taking a pixel point as an example, setting initial projection times y=0, when the pixel point is projected once, y=y+1, otherwise y=y, and taking a discrimination value v=of whether the pixel point is an actual pixel point or not 
Where y is the number of times the pixel is repeatedly projected, k+1 is the total number of times the plane is projected, and k+1 is the number of total second gray level images representing all of the rock debris areas of the rock debris area a. Projection area
Each pixel point in the image display device has a corresponding y value, and a discrimination value corresponding to each pixel point can be obtained. The larger the discrimination value is, the larger the frequency of the corresponding motion pixel point in different second gray level images isThe more likely it is an actual pixel point of the rock fragment area. According to the scheme, the discrimination value threshold is set to be 0.9, when the discrimination value is larger than the discrimination value threshold, the pixel points are reserved, and the corresponding motion pixel points are the actual pixel points.
And acquiring the actual pixel points of all the rock fragment areas according to the acquisition method of the actual pixel points.
Step S3: determining an actual rock fragment area according to the actual pixel points, acquiring a splitting effect index under an initial hydraulic value according to the actual rock fragment area, and adjusting the initial hydraulic value according to the splitting effect index;
specifically, determining an actual rock debris area according to actual pixel points in each rock debris area, acquiring the number and the area average value of the actual rock debris area, taking the inverse number of the product of the area average value and the number as an index of a natural constant e, taking the obtained result as a splitting effect index, and acquiring a splitting effect index 
The formula of (2) is:
wherein,,
is the average area of the rock fragment area,
is the number of actual rock fragment areas; e is a natural constant;
is an index of the splitting effect at the initial hydraulic pressure value.
It should be noted that the number of the substrates,
the smaller the area of rock debris, the smaller the rock is, the more the rock is crushed, the initial hydraulic pressureThe greater the value is,
the larger the size of the container,
and (3) with
Negative correlation is formed;
the smaller, the smaller the number of rock fragment areas,
the larger the size of the container,
and (3) with
Negative correlation is formed; thus, the larger F indicates that the smaller the rock chipping area, the more fully crushed the rock, and the greater the initial hydraulic pressure value; the smaller F indicates a larger area of rock chipping, the less the rock is fully crushed, and the smaller the initial hydraulic pressure value.
The specific method for adjusting the initial hydraulic value according to the splitting effect index comprises the following steps: setting a splitting effect range, and when the splitting effect index meets the splitting effect range, not adjusting an initial hydraulic value; when the splitting effect index does not meet the splitting effect range, calculating a difference value between the constant 2 and the splitting effect index, and taking the product of the initial hydraulic value and the difference value as the adjusted hydraulic value.
The scheme sets the splitting effect range as [0.6,0.8 ]]When the splitting effect index is [0.6,0.8 ]]In the middle, the fact that the splitting effect of the rock drilling and splitting integrated machine can reach the optimal value under the initial hydraulic value is explained, and the initial hydraulic value is not required to be adjusted; when the splitting effect index is not [0.6,0.8 ] ]When the hydraulic pressure is in the middle, the initial hydraulic pressure value is regulated, and the regulated hydraulic pressure value is obtained
The formula of (2) is:
wherein Y is an initial hydraulic value; f is a splitting effect index corresponding to the initial hydraulic value;
is the adjusted hydraulic pressure value.
The larger Y is,
the larger Y is with
Positive correlation is formed; the larger the F is, the more,
smaller F is with
And negative correlation is formed.
Acquiring a splitting effect index corresponding to the adjusted hydraulic value, and if the splitting effect index corresponding to the adjusted hydraulic value is between [0.6,0.8], obtaining the adjusted hydraulic value as an optimal hydraulic value; if the splitting effect index corresponding to the adjusted hydraulic value is not in the range of [0.6,0.8], when the splitting effect index corresponding to the adjusted hydraulic value is smaller than 0.6, adjusting the hydraulic value according to 110% of the current adjusted hydraulic value, and if the splitting effect index still does not reach the range of [0.6,0.8] after 15 times of adjustment, selecting the hydraulic value, closest to 0.6, of the splitting effect indexes corresponding to the 15 times as the optimal hydraulic value; when the splitting effect index corresponding to the adjusted hydraulic value is larger than 0.8, the hydraulic value is adjusted according to 90% of the current adjusted hydraulic value, the splitting effect index still does not reach [0.6,0.8] after 15 times of adjustment, and the hydraulic value, closest to 0.8, of the splitting effect indexes corresponding to 15 times is selected as the optimal hydraulic value.
Thus, the remote control of the rock drilling and splitting integrated machine is completed.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
The foregoing description of the preferred embodiments of the present invention is not intended to be limiting, but rather, any modifications, equivalents, improvements, etc. that fall within the principles of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. The remote control method of the rock drilling and splitting integrated machine is characterized by comprising the following steps of:
acquiring a rock surface image to be mined, obtaining a corresponding gray image, obtaining a rock surface area by dividing the gray image, obtaining the smoothness of each pixel point based on the gray value of the pixel point in the rock surface area, and obtaining a target pixel point according to the smoothness; dividing the target pixel point into at least two clusters by utilizing an improved DBSCAN density clustering algorithm, wherein one cluster corresponds to one drilling position to be selected, and determining the optimal drilling position according to the smoothness of the target pixel point in the drilling position to be selected;
Setting an initial hydraulic value, splitting an optimal drilling position, collecting each frame of image of rock fragments continuously discharged in the splitting process, acquiring a corresponding second gray level image, and determining a motion pixel point according to the gray level value of the corresponding pixel point in the adjacent second gray level image; taking the area formed by the moving pixel points as a rock debris area, and determining actual pixel points according to the rock debris areas representing the same area in all the second gray level images;
determining an actual rock fragment area according to the actual pixel points, acquiring a splitting effect index under an initial hydraulic value according to the actual rock fragment area, and adjusting the initial hydraulic value according to the splitting effect index;
the specific method for dividing the target pixel point into at least two clusters by utilizing the improved DBSCAN density clustering algorithm comprises the following steps: taking a target pixel point as a circle center, acquiring a circular neighborhood with a set size, and acquiring a distance measurement value between each neighborhood pixel point and the central pixel point according to the gray difference absolute value of the central pixel point of the circular neighborhood and each neighborhood pixel point, wherein the neighborhood pixel point is the target pixel point; determining the number of effective pixels in the circular neighborhood according to the distance measurement value, and determining the effective pixels in the corresponding circular neighborhood as a cluster when the number of the effective pixels meets the neighborhood sample number threshold;
The method for obtaining the distance measurement value between each neighborhood pixel point and the central pixel point comprises the following steps:
taking the absolute value of the gray difference between the central pixel point of the circular neighborhood and each neighborhood pixel point as a first value, taking the opposite number of the first value as an index of a natural constant e, and taking the obtained result as a third result;
taking any one of the neighborhood pixel points in the circular neighborhood of the central pixel point as a target neighborhood pixel point, setting a circular neighborhood with the same size as the central pixel point by taking the target neighborhood pixel point as a circle center, and taking the neighborhood pixel points which exist in the same positions in the circular neighborhood of the central pixel point and the circular neighborhood of the target neighborhood pixel point as a matching pair;
calculating the gray difference absolute value of each neighborhood pixel point in the target neighborhood pixel point and the round neighborhood thereof as a second value; respectively calculating the absolute value of the difference between the first value and the second value corresponding to each matching pair to obtain a mean value of the absolute value of the difference, taking the opposite number of the mean value of the absolute value of the difference as an index of a natural constant e, and taking the obtained result as a fourth result;
and taking the product of the third result and the fourth result as a distance measurement value of the target neighborhood pixel point and the center pixel point.
2. The remote control method of a rock drilling and splitting integrated machine according to claim 1, wherein the method for obtaining smoothness of each pixel point based on gray values of the pixel points in the rock surface area comprises the steps of:
taking each pixel point in the rock surface area as a central pixel point to acquire a neighborhood with a set size, calculating the gray difference absolute value between each neighborhood pixel point and the central pixel point, taking the inverse number of the sum of all the gray difference absolute values in each neighborhood as an index of a natural constant e, and taking the obtained result as a first result; setting a gray difference absolute value threshold, obtaining a first number of neighborhood pixel points, in which the gray difference absolute value in each neighborhood is larger than the gray difference absolute value threshold, calculating a ratio of the first number to the total number of the neighborhood pixel points in the corresponding neighborhood, taking the difference value of a constant 1 and the ratio as a second result, and calculating the product of the second result and the first result as smoothness of the corresponding center pixel point.
3. A method of remotely controlling a rock drilling and splitting integrated machine according to claim 1, wherein the method of determining the number of valid pixels in a circular neighborhood from a distance metric value comprises:
And setting a distance measurement value threshold value, and acquiring the number of target pixel points with the distance measurement value larger than the distance measurement value threshold value as the number of effective pixel points.
4. A method of remotely controlling a rock drilling and splitting integrated machine according to claim 1, wherein the method of determining an optimal drilling position based on the smoothness of a target pixel in a candidate drilling position comprises:
taking the result of adding the smoothness of the target pixel points in the drilling positions to be selected as the confidence coefficient corresponding to the drilling positions to be selected, and respectively carrying out normalization processing on each obtained confidence coefficient to obtain normalized confidence coefficients; and setting a confidence coefficient threshold value, and when the normalized confidence coefficient is larger than the confidence coefficient threshold value, obtaining the position of the selected drill hole corresponding to the normalized confidence coefficient as the optimal drill hole position.
5. The method for remotely controlling a rock drilling and splitting integrated machine according to claim 1, wherein the method for determining the motion pixel point according to the gray value of the corresponding pixel point in the adjacent second gray image comprises the following steps:
taking any one second gray level image as a target second gray level image, taking any one pixel point in the target second gray level image as a first pixel point, taking the pixel point with the same position as the first pixel point as a second pixel point in the second gray level image adjacent to the target second gray level image, calculating the gray level difference absolute value between the first pixel point and the second pixel point, when the gray level difference absolute value is not equal to 0, acquiring a set number of pixel points under the second pixel point as sampling points, taking the pixel point with the smallest gray level difference between the sampling points and the first pixel point as a third pixel point, respectively setting first neighborhoods with the same size for the first pixel point and the third pixel point, respectively taking the t pixel point in the first neighborhoods of the first pixel point and the t pixel point in the first neighborhoods of the third pixel point as a pair, respectively calculating the difference absolute value between the two first neighborhoods as a molecular gray level pair absolute value, taking the largest difference value between the first pixel pair as a first average value and a fifth pixel value as a fifth pixel value, and taking the difference value between the first pixel pair as a fifth pixel value and a fifth pixel value as a corresponding value, and a fifth pixel value, and obtaining a similar result; and setting a similarity value threshold, and determining the first pixel point as a motion pixel point when the similarity value is larger than the similarity value threshold.
6. A method of remotely controlling a rock drilling and splitting integrated machine according to claim 1, wherein said method of determining actual pixels from areas of rock chips representing the same area in all second gray scale images comprises:
determining center points of rock debris areas representing the same area in all second gray level images, projecting all the center points to the same position on the same plane, and projecting all the motion pixel points in the rock debris areas to the same plane according to the positions corresponding to the center points to obtain projection areas on the plane; the method comprises the steps of obtaining the number of repeated projection of each pixel point in a projection area, taking the ratio of the number of repeated projection of each pixel point to the total number of projected plane as a discrimination value, setting a discrimination value threshold, and confirming the corresponding moving pixel point as an actual pixel point of a rock debris area when the discrimination value is larger than the discrimination value threshold.
7. The remote control method of a rock drilling and splitting integrated machine according to claim 1, wherein the method for obtaining the splitting effect index under the initial hydraulic pressure value according to the actual rock fragment area comprises the following steps:
and acquiring the number and the area average value of the actual rock fragment areas, taking the inverse number of the product of the area average value and the number as an index of a natural constant e, and taking the obtained result as a splitting effect index.
8. The remote control method of a rock drilling and splitting integrated machine according to claim 1, wherein the method for adjusting the initial hydraulic value according to the splitting effect index comprises the following steps:
setting a splitting effect range, and when the splitting effect index meets the splitting effect range, not adjusting an initial hydraulic value; when the splitting effect index does not meet the splitting effect range, calculating a difference value between the constant 2 and the splitting effect index, and taking the product of the initial hydraulic value and the difference value as the adjusted hydraulic value.
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