CN113011368A - Mine mining surface conduction goaf crack identification method and electronic equipment - Google Patents
Mine mining surface conduction goaf crack identification method and electronic equipment Download PDFInfo
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Abstract
The invention discloses a mine mining surface conduction goaf crack identification method and electronic equipment, wherein the method comprises the following steps: acquiring a ground surface thermal infrared image obtained by flying an unmanned aerial vehicle carrying thermal infrared imaging device according to a designed air route and a designed altitude; identifying cracks in the thermal infrared image by adopting an edge detection algorithm, and extracting to generate an edge detection image; extracting the relationship between the fracture temperature in the thermal infrared image and the accumulated length of the fracture and the relationship between the fracture width and the accumulated length of the fracture; and judging whether the fracture is communicated with the gob according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length. The mine exploitation ground surface conduction goaf crack identification method based on the unmanned aerial vehicle infrared can nondestructively acquire ground surface crack thermal infrared images, realize rapid identification of ground surface cracks, and effectively judge whether the ground surface cracks above the mine exploitation goaf are conducted or not.
Description
Technical Field
The invention relates to the technical field of coal mine correlation, in particular to electronic equipment for a mine mining ground surface conduction goaf crack identification method.
Background
At present, high-resolution unmanned aerial vehicle remote sensing images are used for analyzing and counting distribution characteristics of surface cracks and subsidence basins, coal mining ground subsidence disasters such as subsidence pits and surface cracks are interpreted and identified, MSPS software is used for predicting subsidence values, a subsidence contour map of a mining area is obtained, monitoring and analysis are carried out on goaf surface subsidence based on InSAR technology, and a crack distribution map is discussed for application problems of a three-dimensional laser scanning technology in subsidence monitoring.
However, the prior art does not have a reliable and effective means for identifying the mine mining surface-surface crack and judging whether the mine mining surface-surface crack is conducted with the goaf, and the existing mine mining surface-surface conduction goaf crack identification method is to detect through a geological radar and a transient electromagnetic instrument. Geological radar and transient electromagnetic instrument detection have limitations in construction and detection, human resource consumption cost is high, and detection result accuracy is not high. In particular, it is difficult to detect surface fractures in a large area of a mine.
Disclosure of Invention
Based on this, it is necessary to provide a method for identifying a mine-mining ground-surface-conduction goaf crack and an electronic device for solving the technical problem that the prior art does not have a reliable and effective means for identifying the mine-mining ground-surface crack and judging whether the mine-mining ground-surface-conduction goaf crack conducts the goaf or not.
The invention provides a method for identifying fractures of a mine mining ground surface conduction goaf, which comprises the following steps:
acquiring a ground surface thermal infrared image obtained by flying an unmanned aerial vehicle carrying thermal infrared imaging device according to a designed air route and a designed altitude;
identifying the cracks in the thermal infrared image by adopting an edge detection algorithm, and extracting to generate an edge detection image;
extracting the relationship between the fracture temperature in the thermal infrared image and the accumulated length of the fracture and the relationship between the fracture width and the accumulated length of the fracture;
and judging whether the fracture is communicated with the gob according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length.
Further, the extracting of the relationship between the fracture temperature in the thermal infrared image and the cumulative length of the fracture and the relationship between the fracture width and the cumulative length of the fracture specifically includes:
dividing the thermal infrared image into M multiplied by N pixels, wherein the pixel coordinate of each pixel is the row and the column of the pixel in the thermal infrared image;
extracting a temperature value of each pixel from the thermal infrared image, and generating a temperature matrix containing M multiplied by N temperature matrix elements, wherein each temperature matrix element of the temperature matrix is a temperature value of a corresponding pixel coordinate in the thermal infrared image;
determining the pixel coordinates of the crack edge in the edge detection image in the thermal infrared image, reserving the temperature matrix elements corresponding to the pixel coordinates of the crack edge in the temperature matrix, and modifying the rest thermometer matrix elements into 0;
acquiring an included angle between each pixel row of the crack in the thermal infrared image and the vertical direction;
calculating the temperature of each pixel row of the crack in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the included angle between each pixel row of the crack in the thermal infrared image and the vertical direction;
and splicing and integrating the temperature of each pixel row of the crack, the width of each pixel row and the accumulated length of the crack in sequence to obtain the relationship between the crack temperature and the accumulated length of the crack and the relationship between the crack width and the accumulated length of the crack.
Further, the calculating the temperature of each pixel row of the crack in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the included angle of each pixel row of the crack in the thermal infrared image with the vertical direction specifically includes:
calculating the temperature of the crack in each pixel row in the thermal infrared image
Wherein T (i, j) is the temperature matrix element of the ith row and the jth column of the temperature matrix, NumiIs the number of non-zero temperature matrix elements, T, of the ith row in the temperature matrixiThe temperature of the ith pixel row of the crack in the thermal infrared image is obtained;
calculating the width of the crack in each pixel row in the thermal infrared image
Wherein n is the resolution of the thermal infrared image, WiThe width of the ith pixel row of the crack in the thermal infrared image;
calculating a cumulative crack length for a crack for each pixel row in the thermal red image
Wherein s is the line number of the pixel line of the crack starting end in the thermal infrared image, thetamIs the included angle L between the mth pixel row of the crack in the thermal infrared image and the vertical directioniThe accumulated length of the crack for the ith pixel row of the crack in the thermal infrared image.
Further, the acquiring an included angle between each pixel row of the crack in the thermal infrared image and the vertical direction specifically includes:
the fracture is divided into a plurality of sections, and an included angle between each section of the fracture in the thermal infrared image and the vertical direction is obtained;
and the included angle of each pixel row of the crack in the thermal infrared image and the vertical direction is the included angle of the segment where the pixel row is located and the vertical direction.
Further, before calculating the temperature of the crack in each pixel row in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the included angle of the crack in each pixel row in the thermal infrared image with the vertical direction, the method further comprises:
and counting the number of non-zero temperature matrix elements of each row in the temperature matrix and storing the non-zero temperature matrix elements as a pixel number array comprising M array elements, wherein each array element in the pixel number array is the number of non-zero temperature matrix elements of the row corresponding to the array element in the temperature matrix.
Further, before calculating the temperature of the crack in each pixel row in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the included angle of the crack in each pixel row in the thermal infrared image with the vertical direction, the method further comprises:
determining a fracture pixel row of a pixel row covered by the fracture in the thermal infrared image, and deleting temperature matrix elements corresponding to other pixel rows except the fracture pixel row in a temperature matrix;
determining a first pixel row of a crack of pixel rows of a crack starting end in the thermal infrared image;
correcting the row number of the temperature matrix element corresponding to the fissure pixel row in the temperature matrix as follows: and subtracting the original row number of the temperature matrix element corresponding to the first pixel row of the crack from the original row number of the temperature matrix element, and then adding one.
Further, before calculating the temperature of the crack in each pixel row in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the included angle of the crack in each pixel row in the thermal infrared image with the vertical direction, the method further comprises:
determining pixels of a size reference object from the thermal infrared image, the size reference object being pre-arranged on the ground surface photographed by the drone;
acquiring the real size of a size reference object;
and determining the resolution n of the thermal infrared image according to the real size of the size reference object and the pixel of the size reference object.
Further, the determining whether the fracture conducts the gob according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length specifically includes:
if the relationship of the fracture temperature relative to the fracture accumulated length is negatively correlated with the relationship of the fracture width relative to the fracture accumulated length, judging that the fracture conducts the gob;
and if the relationship of the fracture temperature relative to the fracture accumulated length is positively correlated with the relationship of the fracture width relative to the fracture accumulated length, judging that the fracture does not conduct the gob.
Further:
the method is characterized in that the thermal infrared image of the earth's surface obtained by the unmanned aerial vehicle carrying the thermal infrared imaging device flying according to the designed air route and the designed altitude is acquired, and the method specifically comprises the following steps: acquiring a ground surface thermal infrared image obtained by an unmanned aerial vehicle carrying a thermal infrared imaging device in daytime and a ground surface thermal infrared image obtained in morning according to a designed air route and high-altitude flight, taking the ground surface thermal infrared image obtained in daytime as a daytime thermal infrared image, and taking the ground surface thermal infrared image obtained in morning as a morning thermal infrared image;
the judging whether the fracture is conducted with the goaf or not according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length specifically comprises the following steps:
if the relation of the fracture temperature on the fracture cumulative length calculated based on the white day thermal infrared image is negatively correlated with the relation of the fracture width on the fracture cumulative length, and the relation of the fracture temperature on the fracture cumulative length calculated based on the early morning thermal infrared image is not correlated with the relation of the fracture width on the fracture cumulative length, judging that the fracture conducts the goaf;
and if the relationship of the fracture temperature and the fracture cumulative length calculated based on the early morning thermal infrared image is positively correlated with the relationship of the fracture width and the fracture cumulative length, the fracture cannot be identified in the thermal infrared image of the earth surface obtained in daytime, and the fracture can be identified in the thermal infrared image of the earth surface obtained in morning, judging that the fracture does not conduct the goaf.
The present invention provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to at least one of the processors; wherein the content of the first and second substances,
the memory stores instructions executable by at least one of the processors to enable the at least one of the processors to perform the mine mining surface-conduction goaf fracture identification method as previously described.
The mine exploitation ground surface conduction goaf crack identification method based on the unmanned aerial vehicle infrared can nondestructively acquire ground surface crack thermal infrared images, realize rapid identification of ground surface cracks, and effectively judge whether the ground surface cracks above the mine exploitation goaf are conducted or not. Meanwhile, whether the ground surface fracture is communicated with the goaf or not is judged according to the identification results of the ground surface fracture in the high-temperature environment and the low-temperature environment, and the criterion is simple. The method is simple and convenient to operate, has small workload, and has positive significance for quickly identifying and timely treating the mine ground surface fractures.
Drawings
Fig. 1 is a working flow chart of a method for identifying cracks in a mine mining ground surface conduction goaf according to an embodiment of the invention;
FIG. 2 is a flowchart illustrating the operation of a method for identifying cracks in a mine mined surface-communicated gob based on infrared rays of an unmanned aerial vehicle in accordance with a preferred embodiment of the present invention;
FIG. 3 is a schematic view of a route of an unmanned aerial vehicle according to an embodiment of the invention;
FIG. 4 is a schematic view of a visible light image, a thermal infrared image, and an edge detection image according to an embodiment of the present invention;
FIG. 5a is a schematic diagram of the extraction results of the fissure 1 at 11:00 am;
fig. 5b is a crack 1 morning 5:00 is a schematic diagram of the extraction result;
FIG. 5c is a graph showing the results of 5:00 extraction in 2 am of fissure;
FIG. 6 is a schematic diagram of the result of extracting data from temperature information of sand (soil) and vegetation;
fig. 7 is a schematic diagram of a hardware structure of an electronic device according to the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples.
Fig. 1 is a flowchart illustrating a method for identifying a goaf crack in a mine mining surface conduction mode according to an embodiment of the present invention, including:
s101, acquiring a ground surface thermal infrared image obtained by flying the unmanned aerial vehicle carrying the thermal infrared imaging device according to a designed air route and a designed altitude;
s102, identifying the cracks in the thermal infrared image by adopting an edge detection algorithm, and extracting to generate an edge detection image;
s103, extracting the relation between the fracture temperature in the thermal infrared image and the accumulated fracture length and the relation between the fracture width and the accumulated fracture length;
and S104, judging whether the fracture is communicated with the gob according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length.
Specifically, an unmanned aerial vehicle is used for carrying a thermal infrared imaging device to fly according to a designed route and a designed altitude, and then a terrestrial heat infrared image is acquired in step S101. Then, step S102 is executed, and the surface fractures in the thermal infrared image are identified and extracted by using an edge detection algorithm. And then, executing a step S103, and extracting the temperature information in the thermal infrared image and the width and the length of the ground fracture to obtain the relationship between the fracture temperature and the cumulative length of the fracture and the relationship between the fracture width and the cumulative length of the fracture. And finally, S104, judging whether the ground surface fracture is communicated with the gob according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length.
The mine exploitation ground surface conduction goaf crack identification method based on the unmanned aerial vehicle infrared can nondestructively acquire ground surface crack thermal infrared images, realize rapid identification of ground surface cracks, and effectively judge whether the ground surface cracks above the mine exploitation goaf are conducted or not. Meanwhile, whether the ground surface fracture is communicated with the goaf or not is judged according to the identification results of the ground surface fracture in the high-temperature environment and the low-temperature environment, and the criterion is simple. The method is simple and convenient to operate, has small workload, and has positive significance for quickly identifying and timely treating the mine ground surface fractures.
In one embodiment, the extracting of the relationship between the temperature of the crack in the thermal infrared image and the cumulative length of the crack and the relationship between the width of the crack and the cumulative length of the crack specifically includes:
dividing the thermal infrared image into M multiplied by N pixels, wherein the pixel coordinate of each pixel is the row and the column of the pixel in the thermal infrared image;
extracting a temperature value of each pixel from the thermal infrared image, and generating a temperature matrix containing M multiplied by N temperature matrix elements, wherein each temperature matrix element of the temperature matrix is a temperature value of a corresponding pixel coordinate in the thermal infrared image;
determining the pixel coordinates of the crack edge in the edge detection image in the thermal infrared image, reserving the temperature matrix elements corresponding to the pixel coordinates of the crack edge in the temperature matrix, and modifying the rest thermometer matrix elements into 0;
acquiring an included angle between each pixel row of the crack in the thermal infrared image and the vertical direction;
calculating the temperature of each pixel row of the crack in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the included angle between each pixel row of the crack in the thermal infrared image and the vertical direction;
and splicing and integrating the temperature of each pixel row of the crack, the width of each pixel row and the accumulated length of the crack in sequence to obtain the relationship between the crack temperature and the accumulated length of the crack and the relationship between the crack width and the accumulated length of the crack.
Specifically, the thermal infrared image is divided into M × N pixels, and the pixel coordinate of each pixel is the row and the column of the pixel in the thermal infrared image.
And then extracting the temperature value of each pixel from the thermal infrared image, generating a temperature matrix containing M multiplied by N temperature matrix elements, wherein the row number and the column number of each temperature matrix element in the temperature matrix correspond to the pixels in the thermal infrared image one by one, and accordingly extracting the temperature value of the corresponding pixel coordinate in the thermal infrared image into the temperature matrix.
The edge detection image is a gray image obtained by identifying the thermal infrared image by adopting an edge detection algorithm, so that each pixel in the edge detection image corresponds to each pixel in the thermal infrared image one to one, and each pixel in the edge detection image corresponds to each temperature matrix element in the middle of the temperature one to one. A computer may be used to manually erase extraneous non-crack edges in the edge-detected image and fill the crack interior region. The temperature information of the thermal infrared image can be extracted through Maxlm DL 5 software, and an M multiplied by N temperature matrix is derived. And then importing the temperature matrix of the processed edge detection image and the thermal infrared image into MATLAB software, positioning by using the pixel coordinates of the fracture edge, reserving elements corresponding to the fracture position in the temperature matrix, and modifying the rest elements into 0. And finally, acquiring an included angle between each pixel row of the crack in the thermal infrared image and the vertical direction, calculating the temperature of each pixel row of the crack in the thermal infrared image, the width of each pixel row and the cumulative length of the crack, and splicing and integrating the temperature of each pixel row of the crack, the width of each pixel row and the cumulative length of the crack in sequence to obtain the relationship between the temperature of the crack and the cumulative length of the crack and the relationship between the width of the crack and the cumulative length of the crack.
In the embodiment, each parameter of the fracture in the thermal infrared image is determined according to the corresponding relationship between the thermal infrared image and the edge detection image, so that the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length are obtained.
In one embodiment, the calculating the temperature of each pixel row of the crack in the thermal infrared image, the width of each pixel row, and the accumulated crack length based on the temperature matrix and the included angle of each pixel row of the crack in the thermal infrared image with the vertical direction specifically includes:
calculating the temperature of the crack in each pixel row in the thermal infrared image
Wherein T (i, j) is the temperature matrix element of the ith row and the jth column of the temperature matrix, NumiIs the number of non-zero temperature matrix elements, T, of the ith row in the temperature matrixiThe temperature of the ith pixel row of the crack in the thermal infrared image is obtained;
calculating the width of the crack in each pixel row in the thermal infrared image
Wherein n is the resolution of the thermal infrared image, WiPixel row i in the thermal infrared image for a crackThe width of (d);
calculating a cumulative crack length for a crack for each pixel row in the thermal red image
Wherein s is the line number of the pixel line of the crack starting end in the thermal infrared image, thetamIs the included angle L between the mth pixel row of the crack in the thermal infrared image and the vertical directioniThe accumulated length of the crack for the ith pixel row of the crack in the thermal infrared image.
In this example, Ti、WiAnd LiThe calculation formula can calculate the width and the temperature corresponding to any position of the crack and the position coordinate along the crack, and can realize the correspondence of the width, the temperature and the position coordinate along the crack, thereby realizing the quantitative characterization of the crack temperature and the crack development form.
In one embodiment, the acquiring an included angle between each pixel row of the crack in the thermal infrared image and the vertical direction specifically includes:
the fracture is divided into a plurality of sections, and an included angle between each section of the fracture in the thermal infrared image and the vertical direction is obtained;
and the included angle of each pixel row of the crack in the thermal infrared image and the vertical direction is the included angle of the segment where the pixel row is located and the vertical direction.
In the embodiment, the fracture is divided into multiple segments, so that the included angle of each segment is used as the included angle of the pixel rows included in the segment, the calculation is simplified, and the efficiency is improved.
In one embodiment, before calculating the temperature of the crack in each pixel row in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the angle of the crack with the vertical direction in each pixel row in the thermal infrared image, the method further comprises:
and counting the number of non-zero temperature matrix elements of each row in the temperature matrix and storing the non-zero temperature matrix elements as a pixel number array comprising M array elements, wherein each array element in the pixel number array is the number of non-zero temperature matrix elements of the row corresponding to the array element in the temperature matrix.
In the embodiment, the number array of the pixel numbers is set, so that the number of elements of each row of the non-zero temperature matrix in the temperature matrix is extracted, and the calculation is simplified.
In one embodiment, before calculating the temperature of the crack in each pixel row in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the angle of the crack with the vertical direction in each pixel row in the thermal infrared image, the method further comprises:
determining a fracture pixel row of a pixel row covered by the fracture in the thermal infrared image, and deleting temperature matrix elements corresponding to other pixel rows except the fracture pixel row in a temperature matrix;
determining a first pixel row of a crack of pixel rows of a crack starting end in the thermal infrared image;
correcting the row number of the temperature matrix element corresponding to the fissure pixel row in the temperature matrix as follows: and subtracting the original row number of the temperature matrix element corresponding to the first pixel row of the crack from the original row number of the temperature matrix element, and then adding one.
In the embodiment, the temperature matrix is corrected, the coordinates of the fracture starting end and the fracture tail end are determined, i at the fracture starting end is 1, and i at the fracture tail end is imax, so that the calculation is simplified, and the efficiency is improved.
In one embodiment, before calculating the temperature of the crack in each pixel row in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the angle of the crack with the vertical direction in each pixel row in the thermal infrared image, the method further comprises:
determining pixels of a size reference object from the thermal infrared image, the size reference object being pre-arranged on the ground surface photographed by the drone;
acquiring the real size of a size reference object;
and determining the resolution n of the thermal infrared image according to the real size of the size reference object and the pixel of the size reference object.
In the embodiment, the resolution of the thermal infrared image is calculated by adopting the size reference object, so that the accurate crack width and the crack accumulated length are obtained.
In one embodiment, the determining whether the fracture opens the gob according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length specifically includes:
if the relationship of the fracture temperature relative to the fracture accumulated length is negatively correlated with the relationship of the fracture width relative to the fracture accumulated length, judging that the fracture conducts the gob;
and if the relationship of the fracture temperature relative to the fracture accumulated length is positively correlated with the relationship of the fracture width relative to the fracture accumulated length, judging that the fracture does not conduct the gob.
Specifically, if the fracture leads to the gob, for a certain accumulated length of the fracture, when the corresponding fracture width is increased, the fracture leads to the gob, so that air flows downwards, the temperature of the fracture corresponding to the accumulated length of the fracture is reduced, that is, the relationship between the fracture temperature and the accumulated length of the fracture is negatively correlated with the relationship between the fracture width and the accumulated length of the fracture, so that the fracture leading to the gob can be determined. And if the fracture does not conduct the gob, for the accumulated length of the fracture, when the fracture width is larger, the fracture grows deeper, and the heat inside the fracture is dissipated more, so that the temperature of the fracture corresponding to the accumulated length of the fracture rises, namely, the relationship between the temperature of the fracture and the accumulated length of the fracture is positively correlated with the relationship between the width of the fracture and the accumulated length of the fracture, and the gob is judged to be not conducted by the fracture.
The method for judging the fracture conduction goaf comprehensively considers the relationship between the fracture width and the fracture temperature, so that whether the mine mining surface fracture is conducted in the goaf or not is effectively identified.
In one embodiment:
the method is characterized in that the thermal infrared image of the earth's surface obtained by the unmanned aerial vehicle carrying the thermal infrared imaging device flying according to the designed air route and the designed altitude is acquired, and the method specifically comprises the following steps: acquiring a ground surface thermal infrared image obtained by an unmanned aerial vehicle carrying a thermal infrared imaging device in daytime and a ground surface thermal infrared image obtained in morning according to a designed air route and high-altitude flight, taking the ground surface thermal infrared image obtained in daytime as a daytime thermal infrared image, and taking the ground surface thermal infrared image obtained in morning as a morning thermal infrared image;
the judging whether the fracture is conducted with the goaf or not according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length specifically comprises the following steps:
if the relation of the fracture temperature on the fracture cumulative length calculated based on the white day thermal infrared image is negatively correlated with the relation of the fracture width on the fracture cumulative length, and the relation of the fracture temperature on the fracture cumulative length calculated based on the early morning thermal infrared image is not correlated with the relation of the fracture width on the fracture cumulative length, judging that the fracture conducts the goaf;
and if the relationship of the fracture temperature and the fracture cumulative length calculated based on the early morning thermal infrared image is positively correlated with the relationship of the fracture width and the fracture cumulative length, the fracture cannot be identified in the thermal infrared image of the earth surface obtained in daytime, and the fracture can be identified in the thermal infrared image of the earth surface obtained in morning, judging that the fracture does not conduct the goaf.
Specifically, the unmanned aerial vehicle equipped with the thermal infrared imaging device flies once in the midday time period of the day and in the lowest air temperature period in the day before the sunrise of the morning according to the paths shown in fig. 3, so that two sets of surface thermal infrared images are obtained. According to surface thermal infrared images and edge detection results in two environments of day and night, the surface cracks which can be identified in day and early morning are communicated with the goaf, important attention and timely landfill treatment need to be carried out, and the identified cracks are not communicated with the goaf only in the environment with low external temperature in early morning.
The embodiment adds two times of thermal infrared images in the daytime and in the morning, so that the defects that the cracks of the non-conducted goaf cannot be identified when the temperature in the daytime is higher are overcome, and whether the goaf is conducted or not can be distinguished through comparison, so that the risk of the cracks is evaluated, the cracks threatened by air leakage can be timely treated, and the method has positive significance for avoiding spontaneous ignition of residual coal in the goaf.
As shown in fig. 2, a method for identifying a mine mining surface-conducted goaf crack based on unmanned aerial vehicle infrared in the best embodiment of the present invention includes:
step S201, determining a monitoring range, an unmanned aerial vehicle navigational height, a course overlapping degree and a course according to the mine and the working face.
Specifically, the geographical position of a mine and the position of a working face body are investigated on the spot, the positions and boundaries of the mine and the working face on the ground surface are determined, a proper monitoring range, the flight height and coverage range of the unmanned aerial vehicle and the course overlapping degree are determined, and finally the flight path of the unmanned aerial vehicle is determined;
and S202, using an unmanned aerial vehicle to carry a heat-carrying infrared imaging device to fly according to a designed air route and a designed altitude, and acquiring a surface heat infrared image.
The unmanned aerial vehicle flies according to the designed air route and the designed altitude to obtain the surface thermal infrared image. As shown in fig. 3, the unmanned aerial vehicle route is preferably a "bow" route 33, the route 33 covering the mine or work surface boundary line 31 and being within the monitoring area boundary line 32.
Specifically, the mine boundary refers to a mine mining boundary and is composed of a plurality of line segments on the ground surface and contrasting the inner edge of a coal pillar of the mine boundary. The working face boundary line is a rectangular area boundary line formed by four line segments on the ground surface, which are opposite to the coal face cutting hole, the transportation gate way, the return air gate way and the current position of the working face. And the monitoring area boundary line is a rectangular area boundary line which is formed by expanding the working surface boundary line by 100m towards the rear of the eye-cutting and expanding the working surface boundary line by 50m towards the outer sides of the transportation crossheading, the return air crossheading and the current position of the working surface.
Specifically, aerial photography is respectively carried out in the daytime with higher temperature and in the morning with lower temperature, and thermal infrared images in the two environments of the daytime and the morning are acquired.
And S203, identifying and extracting the ground surface fractures in the thermal infrared image by using an edge detection algorithm.
Specifically, the edge detection algorithm is based on a cellular automaton. After format conversion and image preprocessing are carried out on the thermal infrared image, edge detection based on a cellular automaton is carried out on the image in the day and night by using MATLAB software, a threshold value is continuously adjusted to enable the crack to be completely extracted, and irrelevant non-crack edges are filtered out as far as possible.
And step S204, extracting temperature information in the thermal infrared image and the width and the length of the ground fracture.
Specifically, the temperature information of the thermal infrared image includes soil temperature, vegetation temperature and crack temperature.
Specifically, the extraction method of the soil temperature and the vegetation temperature comprises the following steps:
and importing the thermal infrared image into Maxlm DL 5 software, respectively arranging a certain number of measuring points in a soil area and a vegetation area, reading the temperature value of a pixel where each measuring point is located, and respectively calculating the average temperature value of the measuring points in the soil area and the vegetation area as the soil temperature and the vegetation temperature.
Specifically, the temperature information of the thermal infrared image comprises soil temperature, vegetation temperature and crack temperature, wherein the soil temperature is an average value of a certain amount of pixel point temperatures in a soil region in the thermal infrared image, and the vegetation temperature is an average value of a certain amount of pixel point temperatures in a vegetation region;
specifically, the temperature, the width and the length of the crack can be respectively expressed as follows:
wherein i is the number of pixel rows counted from the starting end of the crack; numiThe number of the ith row of pixels from the starting end of the crack; theta is the angle between the crack and the vertical direction, which varies with different positions of the crackiThe included angle between the pixel of the ith row starting from the starting end of the crack and the vertical direction is shown; n is the centimeter resolution of the thermal infrared image, and the unit is pixel/cm; t (i, j) is the temperature value of the ith pixel from the starting end of the crack and the jth pixel from the left edge pixel of the crack, and the unit is; t isiIs a self-crackThe temperature of the starting end starting at the ith row is measured in units of ℃; wiThe width of the ith row from the starting end of the crack is expressed in cm; l isiThe cumulative length from the start of the crack to the ith row position is given in m. The accumulated length is the accumulated length of the crack from the crack starting end to the ith row, and the i is the number of pixel rows counted from the crack starting end, so that the statistics can be directly counted from the 1 st row of the crack starting end to the ith row. Meanwhile, since the cumulative length unit is meter (m) and the resolution n unit is pixel/centimeter (pixel/cm), the adjustment unit is multiplied by 100.
Specifically, the temperature, length and width of the crack are extracted:
firstly, determining the resolution N, the pixel row number M and the pixel column number N of an image according to the thermal infrared image and a size reference object.
Manually erasing irrelevant non-crack edges in the edge detection image by using a computer, and filling the internal area of the crack;
thirdly, extracting temperature information of the thermal infrared image through Maxlm DL 5 software, and deriving an MxN temperature matrix;
fourthly, importing the temperature matrix of the processed edge detection image and the thermal infrared image into MATLAB software, positioning by using the pixel coordinates of the fracture edge, reserving elements corresponding to the fracture position in the temperature matrix, and modifying the rest elements into 0;
fifthly, using MATLAB software to count the number of non-zero elements in each row in the temperature matrix and storing the number of non-zero elements in each row as a one-dimensional array consisting of M elements, wherein the number of the ith element Num of Num in the one-dimensional arrayiThe number of non-zero elements corresponding to the ith row of the temperature matrix;
sixthly, correcting the temperature matrix and the one-dimensional array Num after MATLAB processing by combining Maxlm DL 5 software, determining coordinates of the starting end and the tail end of the crack, enabling i at the starting end of the crack to be 1 and i at the tail end of the crack to be imax, determining the value of imax and the temperature T (i, j) of each pixel point of the crack, wherein imax is the total number of lines covered by the crack in the thermal infrared image;
seventhly, measuring the fracture and the thermal infrared image in a segmented mannerAnd the longitudinal acute included angles are recorded as i1, i2, i3 and … ik of the segmentation points of each segment of the crack, and the included angles of the segments are recorded as theta'1-i1，θ’i1-i2，…θ’ik-imax；
The eighth step, when i is more than or equal to 1 and less than or equal to i1, theta1＝θ2＝…＝θi1＝θ’1-i1According to T (i, j) and NumiAccording to Ti，Wi，LiThe temperature, the width and the accumulated length of each pixel row of the first section of the crack are calculated by the formula;
when i is greater than i1 and less than or equal to i2, thetai1+1＝θi1+2＝…＝θi2＝θ’i1-i2According to T (i, j) and NumiAccording to Ti，Wi，LiThe temperature, the width and the accumulated length of each pixel row of the second section of the crack are calculated by the formula;
…
when ik is more than i and less than or equal to imax, thetaik+1＝θik+2＝…＝θimax＝θ’ik-imaxAccording to T (i, j) and NumiAccording to Ti，Wi，LiThe temperature, the width and the accumulated length of each pixel row of the k +1 th subsection of the crack are calculated by the formula;
and step ten, splicing and integrating the temperature, the width and the accumulated length of each section of the crack in sequence.
And step S204, judging whether the ground surface fracture is communicated with a goaf or not.
Specifically, according to thermal infrared images and edge detection results in two environments of day and night, the ground surface cracks which can be identified in day and in morning are conducted to the goaf, and the cracks which are identified only in the environment with low external temperature in morning are not conducted to the goaf.
(1) The unmanned aerial vehicle is used for carrying the heat-carrying infrared imaging device to fly according to a preset air route, the earth surface heat infrared image is obtained, and the degree of automation is high.
(2) The method has the advantages that the edge detection algorithm is used for identifying and extracting the cracks in the thermal infrared image, the temperature information of the thermal infrared image and the width and the length of the cracks are analyzed, whether the cracks are conducted in the goaf or not is judged, the cracks in the mining area can be rapidly and efficiently distinguished, the operation is simple, and the working efficiency is high.
As an example, cracks were monitored in the surface of a western mine using an unmanned aerial vehicle with a thermal infrared imaging device and were photographed at 11:00 am and 5:00 am, respectively. Edge detection was performed on the thermal infrared images at 11:00 am and 5:00 am, respectively. The method comprises the first step of determining the resolution of an image according to a thermal infrared image and a size reference object, the second step of artificially erasing irrelevant non-fracture edges in an edge detection image by using a computer, filling the internal area of a fracture, extracting temperature information of the thermal infrared image through Maxlm DL 5 software, deriving an MxN fourth step, importing the temperature matrixes of the processed edge detection image and the thermal infrared image into MATLAB software, positioning by using the pixel coordinates of the fracture edge, reserving elements corresponding to the fracture position in the temperature matrixes, and finally obtaining a thermal infrared image 42 of a visible light image 41, 11:00 and a thermal infrared image 43 and 11 of 5:00 of the ground surface fracture shown in figure 4: edge detection fig. 44 of 00, and edge detection fig. 45 of 5: 00. The results of the temperature, width and length extraction of the fracture are shown in FIGS. 5a-5c, where FIG. 5a is the result of the fracture at 11:00 am 1 and FIG. 5b is the result of the fracture at 5 am 1:00, FIG. 5c shows the results of the 2 am 5:00 fissure extraction. The result of extracting data from the temperature information of sand (soil) and vegetation is shown in fig. 6.
According to the results, the fracture 1 can be identified at 11:00 am and 5:00 am to communicate the ground surface fracture of the goaf. 11:00 am, the position with large crack width and low temperature. In the early morning, the temperature of the crack does not obviously change along with the width at 5: 00; the crack 2 can be identified only at 5:00 in the morning, and the goaf is not communicated at the position with larger crack width and higher temperature at which the crack 2 is not communicated.
Fig. 7 is a schematic diagram of a hardware structure of an electronic device according to the present invention, which includes:
at least one processor 701; and the number of the first and second groups,
a memory 702 communicatively coupled to at least one of the processors 701; wherein the content of the first and second substances,
the memory 702 stores instructions executable by at least one of the processors to enable the at least one of the processors to perform the mine mining surface-conduction goaf fracture identification method as previously described.
In fig. 7, one processor 701 is taken as an example.
The electronic device may further include: an input device 703 and a display device 704.
The processor 701, the memory 702, the input device 703 and the display device 704 may be connected by a bus or other means, and are illustrated as being connected by a bus.
The memory 702, which is a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the method for identifying a goaf fracture in a mine mining surface conduction mode in an embodiment of the present application, for example, the method flow illustrated in fig. 1. The processor 701 executes various functional applications and data processing by operating the nonvolatile software programs, instructions and modules stored in the memory 702, so as to implement the mine exploitation surface conduction goaf fracture identification method in the above embodiment.
The memory 702 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the stored data area may store data created from use of the mine mining surface conduction goaf fracture identification method, and the like. Further, the memory 702 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 702 may optionally include memory remotely located from the processor 701, and such remote memory may be connected via a network to a device that performs the mine mining surface-conduction goaf fracture identification method. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 703 may receive input user clicks and generate signal inputs related to user settings and functional controls of the mine mining surface conduction goaf fracture identification method. Display device 704 may include a display screen or the like.
The one or more modules stored in the memory 702, when executed by the one or more processors 701, perform the mine mining surface-conduction goaf fracture identification method of any of the method embodiments described above.
The mine exploitation ground surface conduction goaf crack identification method based on the unmanned aerial vehicle infrared can nondestructively acquire ground surface crack thermal infrared images, realize rapid identification of ground surface cracks, and effectively judge whether the ground surface cracks above the mine exploitation goaf are conducted or not. Meanwhile, whether the ground surface fracture is communicated with the goaf or not is judged according to the identification results of the ground surface fracture in the high-temperature environment and the low-temperature environment, and the criterion is simple. The method is simple and convenient to operate, has small workload, and has positive significance for quickly identifying and timely treating the mine ground surface fractures.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A mine mining surface conduction goaf crack identification method is characterized by comprising the following steps:
acquiring a ground surface thermal infrared image obtained by flying an unmanned aerial vehicle carrying thermal infrared imaging device according to a designed air route and a designed altitude;
identifying the cracks in the thermal infrared image by adopting an edge detection algorithm, and extracting to generate an edge detection image;
extracting the relationship between the fracture temperature in the thermal infrared image and the accumulated length of the fracture and the relationship between the fracture width and the accumulated length of the fracture;
and judging whether the fracture is communicated with the gob according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length.
2. The method for identifying the fractures of the mine mining ground surface conduction goaf according to claim 1, wherein the extracting of the relationship between the fracture temperature and the fracture width in the thermal infrared image specifically comprises:
dividing the thermal infrared image into M multiplied by N pixels, wherein the pixel coordinate of each pixel is the row and the column of the pixel in the thermal infrared image;
extracting a temperature value of each pixel from the thermal infrared image, and generating a temperature matrix containing M multiplied by N temperature matrix elements, wherein each temperature matrix element of the temperature matrix is a temperature value of a corresponding pixel coordinate in the thermal infrared image;
determining the pixel coordinates of the crack edge in the edge detection image in the thermal infrared image, reserving the temperature matrix elements corresponding to the pixel coordinates of the crack edge in the temperature matrix, and modifying the rest thermometer matrix elements into 0;
acquiring an included angle between each pixel row of the crack in the thermal infrared image and the vertical direction;
calculating the temperature of each pixel row of the crack in the thermal infrared image, the width of each pixel row and the accumulated crack length based on the temperature matrix and the included angle between each pixel row of the crack in the thermal infrared image and the vertical direction;
and splicing and integrating the temperature of each pixel row of the crack, the width of each pixel row and the accumulated length of the crack in sequence to obtain the relationship between the crack temperature and the accumulated length of the crack and the relationship between the crack width and the accumulated length of the crack.
3. The method for identifying the mine mining ground surface conduction goaf fracture as claimed in claim 2, wherein the calculating the temperature of each pixel row, the width of each pixel row and the fracture cumulative length of the fracture in the thermal infrared image based on the temperature matrix and the included angle of each pixel row of the fracture in the thermal infrared image with the vertical direction specifically comprises:
calculating the temperature of the crack in each pixel row in the thermal infrared image
Wherein T (i, j) is the temperature matrix element of the ith row and the jth column of the temperature matrix, NumiIs the number of non-zero temperature matrix elements, T, of the ith row in the temperature matrixiThe temperature of the ith pixel row of the crack in the thermal infrared image is obtained;
calculating the width of the crack in each pixel row in the thermal infrared image
Wherein n is the resolution of the thermal infrared image, WiThe width of the ith pixel row of the crack in the thermal infrared image;
calculating a cumulative crack length for a crack for each pixel row in the thermal red image
Wherein s is the line number of the pixel line of the crack starting end in the thermal infrared image, thetamIs the included angle L between the mth pixel row of the crack in the thermal infrared image and the vertical directioniThe accumulated length of the crack for the ith pixel row of the crack in the thermal infrared image.
4. The method for identifying the mine mining ground surface conduction goaf crack as claimed in claim 2, wherein said obtaining an included angle between each pixel row of the crack in the thermal infrared image and a vertical direction specifically comprises:
the fracture is divided into a plurality of sections, and an included angle between each section of the fracture in the thermal infrared image and the vertical direction is obtained;
and the included angle of each pixel row of the crack in the thermal infrared image and the vertical direction is the included angle of the segment where the pixel row is located and the vertical direction.
5. The method of claim 2, wherein calculating the temperature of the fracture at each pixel row in the thermal infrared image, the width of each pixel row, and the cumulative length of the fracture before calculating the temperature of the fracture at each pixel row in the thermal infrared image based on the temperature matrix and the angle of the fracture at each pixel row in the thermal infrared image from the vertical direction further comprises:
and counting the number of non-zero temperature matrix elements of each row in the temperature matrix and storing the non-zero temperature matrix elements as a pixel number array comprising M array elements, wherein each array element in the pixel number array is the number of non-zero temperature matrix elements of the row corresponding to the array element in the temperature matrix.
6. The method of claim 2, wherein calculating the temperature of the fracture at each pixel row in the thermal infrared image, the width of each pixel row, and the cumulative length of the fracture before calculating the temperature of the fracture at each pixel row in the thermal infrared image based on the temperature matrix and the angle of the fracture at each pixel row in the thermal infrared image from the vertical direction further comprises:
determining a fracture pixel row of a pixel row covered by the fracture in the thermal infrared image, and deleting temperature matrix elements corresponding to other pixel rows except the fracture pixel row in a temperature matrix;
determining a first pixel row of a crack of pixel rows of a crack starting end in the thermal infrared image;
correcting the row number of the temperature matrix element corresponding to the fissure pixel row in the temperature matrix as follows: and subtracting the original row number of the temperature matrix element corresponding to the first pixel row of the crack from the original row number of the temperature matrix element, and then adding one.
7. The method of claim 2, wherein calculating the temperature of the fracture at each pixel row in the thermal infrared image, the width of each pixel row, and the cumulative length of the fracture before calculating the temperature of the fracture at each pixel row in the thermal infrared image based on the temperature matrix and the angle of the fracture at each pixel row in the thermal infrared image from the vertical direction further comprises:
determining pixels of a size reference object from the thermal infrared image, the size reference object being pre-arranged on the ground surface photographed by the drone;
acquiring the real size of a size reference object;
and determining the resolution n of the thermal infrared image according to the real size of the size reference object and the pixel of the size reference object.
8. The method for identifying the fractures of the mine mining ground surface conduction goaf, according to the claim 1, wherein the judging whether the fractures conduct the goaf or not according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length specifically comprises the following steps:
if the relationship of the fracture temperature relative to the fracture accumulated length is negatively correlated with the relationship of the fracture width relative to the fracture accumulated length, judging that the fracture conducts the gob;
and if the relationship of the fracture temperature relative to the fracture accumulated length is positively correlated with the relationship of the fracture width relative to the fracture accumulated length, judging that the fracture does not conduct the gob.
9. The method for identifying the mine mining ground surface conduction goaf crack as claimed in claim 1, wherein:
the method is characterized in that the thermal infrared image of the earth's surface obtained by the unmanned aerial vehicle carrying the thermal infrared imaging device flying according to the designed air route and the designed altitude is acquired, and the method specifically comprises the following steps: acquiring a ground surface thermal infrared image obtained by an unmanned aerial vehicle carrying a thermal infrared imaging device in daytime and a ground surface thermal infrared image obtained in morning according to a designed air route and high-altitude flight, taking the ground surface thermal infrared image obtained in daytime as a daytime thermal infrared image, and taking the ground surface thermal infrared image obtained in morning as a morning thermal infrared image;
the judging whether the fracture is conducted with the goaf or not according to the relationship between the fracture temperature and the fracture cumulative length and the relationship between the fracture width and the fracture cumulative length specifically comprises the following steps:
if the relation of the fracture temperature on the fracture cumulative length calculated based on the white day thermal infrared image is negatively correlated with the relation of the fracture width on the fracture cumulative length, and the relation of the fracture temperature on the fracture cumulative length calculated based on the early morning thermal infrared image is not correlated with the relation of the fracture width on the fracture cumulative length, judging that the fracture conducts the goaf;
and if the relationship of the fracture temperature and the fracture cumulative length calculated based on the early morning thermal infrared image is positively correlated with the relationship of the fracture width and the fracture cumulative length, the fracture cannot be identified in the thermal infrared image of the earth surface obtained in daytime, and the fracture can be identified in the thermal infrared image of the earth surface obtained in morning, judging that the fracture does not conduct the goaf.
10. An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to at least one of the processors; wherein the content of the first and second substances,
the memory stores instructions executable by at least one of the processors to enable the at least one processor to perform the mine mining surface-conduction goaf fracture identification method of any of claims 1 to 9.
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