CN112861375A - Method, system, equipment and medium for fine chemical analysis and collection of open-pit mine goaf - Google Patents
Method, system, equipment and medium for fine chemical analysis and collection of open-pit mine goaf Download PDFInfo
- Publication number
- CN112861375A CN112861375A CN202110254879.2A CN202110254879A CN112861375A CN 112861375 A CN112861375 A CN 112861375A CN 202110254879 A CN202110254879 A CN 202110254879A CN 112861375 A CN112861375 A CN 112861375A
- Authority
- CN
- China
- Prior art keywords
- goaf
- explosion
- area
- dimensional
- blast
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
- G01C11/04—Interpretation of pictures
- G01C11/30—Interpretation of pictures by triangulation
- G01C11/34—Aerial triangulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Computer Graphics (AREA)
- Software Systems (AREA)
- Multimedia (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Processing Or Creating Images (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a method, a system, equipment and a medium for fine assay collection of a goaf of a surface mine, wherein the method comprises the following steps: acquiring image information of an explosion area and the periphery of the goaf acquired by the unmanned aerial vehicle during the pre-explosion stage and the post-explosion stage; analyzing the image information of the blast area and the periphery of the goaf by an aerial triangulation analysis method, and converting the image information into three-dimensional dense point cloud data of the blast area of the goaf; processing three-dimensional dense point cloud data of an explosion area where the goaf is located to obtain a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located; and evaluating the blasting treatment effect of the goaf according to the pre-explosion and post-explosion three-dimensional models of the explosion area where the goaf is located, and simultaneously, based on the image information and the actual excavation and installation feedback conditions of the explosion area and the periphery where the goaf is located, ensuring the reliability of evaluating the blasting treatment effect of the goaf and realizing the fine acceptance check of the goaf of the surface mine. The method is beneficial to timely feedback analysis and later-stage design optimization, and has important significance for goaf standardized management.
Description
Technical Field
The invention relates to a method, a system, equipment and a medium for fine assay collection in a goaf of a surface mine, belonging to the field of surface mining.
Background
The method is characterized in that the early underground mines are caving-mined by an open stope method, more goafs and roadways are generated, and although most of the goafs are filled with waste rocks or are subjected to sealing treatment, more unprocessed goafs are left; and the mining and stealing phenomena of mine mining and mining at the early stage are difficult to control, so that blind goafs without mining design data exist in areas with high ore grade. In the later period, in order to improve the resource recovery rate and the safety production management level, a surface mining mode is adopted, so that the left goafs with data and without data bring great threat to the safety production of a stope. Aiming at the treatment of the goaf, the technologies such as a three-dimensional laser scanner, a comprehensive geophysical prospecting technology, a high-density electrical method, comprehensive detection and the like are applied to the precise detection aspect of the goaf, so that great help is provided for obtaining the position and relevant parameters of the hidden goaf, and the analysis of the potential hazard degree is facilitated; in the aspect of safety evaluation of goaf treatment, numerical simulation software such as FLAC3D, ANSYS and the like is used for analyzing safety treatment effect evaluation before and after goaf treatment, and theoretical support is provided for safety evaluation; in the aspect of engineering practice, the goaf filling rate and the volume of the left goaf are used as main evaluation indexes, corresponding parameters are obtained through formula calculation, data before and after goaf processing are contrastively analyzed, and the goaf filling effect after blasting is judged.
In the actual situation, the evaluation of the treatment effect of the goaf of the surface mine mainly adopts an empirical method, and the goaf collapse degree is analyzed by observing the macroscopic external appearance of the blasting pile, so as to judge whether the goaf is in a safe state; the experience method mainly depends on the field work experience of technical management personnel, has certain limitation, is difficult to realize refined evaluation and acceptance, and therefore, a more effective technical means needs to be introduced.
The unmanned aerial vehicle aerial survey technology is an advanced non-contact measurement means, has the remarkable advantages of good safety, high reliability, high efficiency and the like in the aspects of investigation and analysis of important potential safety hazards such as a goaf and the like, can truly reflect the three-dimensional information of the landform and the landform of a detected area, and is widely applied to the field of open-pit mining design and safety management. Through consulting relevant literature, the research on the goaf aspect of unmanned aerial vehicle aerial survey is relatively less, especially on the aspect of goaf treatment effect evaluation.
Disclosure of Invention
In view of the above, the invention provides a method, a system, equipment and a medium for collecting a goaf in a surface mine by fine chemical examination, which can obtain real three-dimensional data of the goaf before and after explosion by applying an unmanned aerial vehicle aerial survey technology, perform matching analysis of image model information and actual processing effect, further realize fine acceptance check of the goaf, contribute to timely feedback analysis and later design optimization, and have important significance for standardized management of the goaf.
The invention aims to provide a method for finely inspecting and accepting a gob of a surface mine.
The invention aims to provide a surface mine goaf fine acceptance inspection system.
It is a third object of the invention to provide a computer apparatus.
It is a fourth object of the present invention to provide a storage medium.
The first purpose of the invention can be achieved by adopting the following technical scheme:
a method for conducting fine mining analysis on a goaf of a surface mine, comprising the following steps:
acquiring image information of an explosion area and the periphery of the goaf acquired by the unmanned aerial vehicle during the pre-explosion stage and the post-explosion stage;
analyzing the image information of the explosion area and the periphery of the goaf by an aerial triangulation analysis method, and converting the image information of the explosion area and the periphery of the goaf into three-dimensional dense point cloud data of the explosion area of the goaf;
processing three-dimensional dense point cloud data of an explosion area where the goaf is located to obtain a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located;
and evaluating the blasting treatment effect of the goaf according to the pre-explosion and post-explosion three-dimensional models of the explosion area where the goaf is located, and simultaneously, based on the image information and the actual excavation and installation feedback conditions of the explosion area and the periphery where the goaf is located, ensuring the reliability of evaluating the blasting treatment effect of the goaf and realizing the fine acceptance check of the goaf of the surface mine.
Further, before exploding and exploding the back stage, acquire the collecting space area place that unmanned aerial vehicle was taken photo by plane and explode district and peripheral image information before, still include:
and acquiring basic parameters of the gob detected by the drilling type three-dimensional laser scanner.
Further, the analyzing the image information of the explosion area and the periphery of the goaf by an aerial triangulation analysis method to convert the image information of the explosion area and the periphery of the goaf into three-dimensional dense point cloud data of the explosion area of the goaf specifically comprises:
carrying out automatic image matching analysis on the image information of the blast area where the goaf is located and the periphery of the goaf, and ensuring that the requirement of calculation of an aerial triangulation method is met;
importing coordinates of image control points and check points to perform primary puncturing, and ensuring that each image control point and check point punctures at least image information of explosion areas and peripheries of continuous three goafs;
performing first aerial triangulation analytical method calculation on the image information after the first pricking to obtain a first resolving image;
and performing secondary puncturing on the first resolved image, and performing secondary aerial triangulation analysis calculation on the first resolved image subjected to the secondary puncturing to obtain a second resolved image serving as three-dimensional dense point cloud data of the blast area where the goaf is located.
Further, the processing of the three-dimensional dense point cloud data of the blast area where the goaf is located to obtain the pre-blast and post-blast three-dimensional models of the blast area where the goaf is located specifically includes:
judging whether the three-dimensional dense point cloud data of the blast area where the goaf is located meet the requirement of model reconstruction;
if the three-dimensional dense point cloud data meet the requirement of model reconstruction, carrying out comprehensive analysis on error precision through a three-dimensional model precision error, an image control point error and a check point error, and judging whether the error precision meets the topographic map mapping precision requirement of a preset proportion;
and if the three-dimensional dense point cloud data meets the topographic map mapping accuracy requirement of a preset proportion, determining model blocks, selecting a coordinate system and a result type, and performing model reconstruction to generate a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located.
Further, the method performs comprehensive analysis of error precision through the three-dimensional model precision error, the image control point and the check point error, and judges whether the error precision meets the topographic map drawing precision requirement of a preset proportion, and specifically includes:
judging whether the three-dimensional dense point cloud data meet the aerial survey requirement or not according to the precision error of the three-dimensional model;
if the three-dimensional dense point cloud data meet the aerial survey requirement, taking image control points and check point coordinates obtained by aerial survey as coordinate measurement values, and comparing and analyzing the coordinate measurement values with real coordinate values;
and judging whether the error precision meets the topographic map drawing precision requirement of a preset proportion or not according to the comparison analysis result.
Further, the evaluating the blasting treatment effect of the goaf according to the pre-blasting and post-blasting three-dimensional models of the blasting area where the goaf is located specifically comprises:
guiding in range coordinates of the goaf based on the pre-explosion and post-explosion three-dimensional models of the goaf in the explosion area, extracting all elevation point information of the goaf before explosion and the goaf after explosion, and performing further processing to obtain elevation point information which accords with the actual situation, thereby obtaining the elevation point information change conditions of the goaf before explosion and the goaf after explosion;
and evaluating the blasting treatment effect of the goaf according to the information change conditions of the elevation points of the blast areas of the goaf before and after blasting.
Further, the blast treatment effect of the goaf is evaluated according to the information change conditions of the elevation points of the blast areas where the goaf before and after blasting is located, specifically:
and comprehensively evaluating the actual filling degree after explosion of the goaf according to the information change conditions of the elevation points of the blast areas of the goaf before and after explosion and by combining the loosening coefficient of the rock after explosion and the actual propelling distance of the blasting pile.
The second purpose of the invention can be achieved by adopting the following technical scheme:
a surface mine goaf acceptance inspection system that becomes more detailed, the system includes:
the acquisition unit is used for acquiring image information of an explosion area and the periphery of the explosion area of the goaf acquired by the unmanned aerial vehicle in aerial photography at the pre-explosion stage and the post-explosion stage;
the analysis unit is used for analyzing the image information of the blast area and the periphery of the goaf by an aerial triangulation analysis method and converting the image information of the blast area and the periphery of the goaf into three-dimensional dense point cloud data of the blast area of the goaf;
the processing unit is used for processing the three-dimensional dense point cloud data of the explosion area where the goaf is located to obtain a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located;
and the acceptance unit is used for evaluating the blasting treatment effect of the goaf according to the pre-explosion and post-explosion three-dimensional models of the explosion area where the goaf is located, and simultaneously, based on the image information and the actual digging and loading feedback condition of the explosion area and the periphery where the goaf is located, the reliability of evaluation of the blasting treatment effect of the goaf is ensured, and the refined acceptance of the goaf of the surface mine is realized.
The third purpose of the invention can be achieved by adopting the following technical scheme:
a computer apparatus comprising a processor and a memory for storing a processor executable program, the processor implementing the surface mine gob refinement collection method described above when executing the program stored in the memory.
The fourth purpose of the invention can be achieved by adopting the following technical scheme:
a storage medium storing a program which, when executed by a processor, implements the surface mine gob refinement collection method described above.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention collects the image information of the blast area and the periphery of the goaf in the pre-blast and post-blast stages by applying the unmanned aerial vehicle aerial survey technology, analyzing the image information of the blast area and the periphery of the goaf by an aerial triangulation analysis method, converting the image information into three-dimensional dense point cloud data of the blast area of the goaf, the three-dimensional dense point cloud data is processed to obtain two-phase three-dimensional models of a blast area before blast and a blast area after blast of the goaf, evaluating the blasting treatment effect of the goaf according to the two-stage three-dimensional model before and after explosion of the blast zone where the goaf is located, meanwhile, based on the image information of the blast area where the goaf is located and the surrounding image information and the actual excavation and loading feedback condition, the blasting treatment effect evaluation reliability of the goaf is guaranteed, the goaf of the surface mine is subjected to fine acceptance check, timely feedback analysis and later design optimization are facilitated, and the method has important significance for goaf standardized management.
2. The unmanned aerial vehicle can be a multi-rotor small unmanned aerial vehicle, can safely, quickly and efficiently acquire high-precision three-dimensional model information of an area where a goaf is located before and after explosion by utilizing the characteristics of non-contact type, good flexibility, high precision, simplicity and convenience in operation, good safety and the like of the multi-rotor small unmanned aerial vehicle in accurate surveying and mapping in a low-altitude small area, and has the advantages of low cost, low manual labor intensity, high safety and reliability, and can update actual terrain change data of the area where the goaf is located in time.
3. The drilling type three-dimensional laser scanner with the 360-degree automatic rotation high-definition probe has the characteristics of high precision, high efficiency, high speed and the like, can safely and efficiently detect basic parameters of the hidden goaf, accurately acquires effective information of the goaf, and lays a foundation for making a goaf blasting design scheme.
4. According to the invention, the image information of the blast area of the goaf and the two stages of the surrounding before and after blast is subjected to aerial triangle analysis calculation and converted into three-dimensional dense point cloud data of the area of the goaf, so that the three-dimensional topographic information of the blast area of the goaf is really reduced, the image analysis and processing are efficient, the data integrity is good, the goaf is real and reliable, and the three-dimensional visualization effect is good.
5. According to the invention, the goaf and the blast zone are displayed simultaneously through the goaf range coordinates, and the goaf elevation point information before and after explosion is quickly generated by delineating the goaf boundary range line, so that the goaf three-dimensional visualization degree is high, and the authenticity is good.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
Fig. 1 is a simplified flowchart of a surface mine goaf fine assay collection method according to embodiment 1 of the present invention.
Fig. 2 is a detailed flowchart of the surface mine goaf fine assay collection method according to embodiment 1 of the present invention.
Fig. 3 is a block diagram of a surface mine goaf refinement acceptance system in embodiment 2 of the present invention.
Fig. 4 is a block diagram of a computer device according to embodiment 3 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the protection scope of the present invention.
Example 1:
as shown in fig. 1 and 2, the present embodiment provides a method for performing fine mining analysis on a gob of a surface mine, which includes the following steps:
s101, acquiring basic parameters of the goaf detected by the drilling type three-dimensional laser scanner.
This embodiment is through the accurate basic parameter who acquires the collecting space area of high accuracy collecting space area detection equipment, this high accuracy collecting space area detection equipment includes 360 degrees rotatory high definition probes of below, signal connection line, the detection image real-time display and control software that correspond etc, can adopt drilling formula three-dimensional laser scanner (like C-ALS type), transfer drilling formula three-dimensional laser scanner to in drilling, connect and show and control software, set up every circle of rotation angle and height of probe, drilling formula three-dimensional laser scanner has the precision height, it is efficient, characteristics such as fast, can detect the basic parameter in the blind collecting space area safely high-efficiently, including the span, height, the area, essential elements such as volume, the effective information in accurate collecting space area, establish the basis for formulating the blasting design scheme.
S102, acquiring image information of an explosion area and the periphery of the explosion area of the goaf acquired by the unmanned aerial vehicle in aerial photography at the pre-explosion stage and the post-explosion stage.
The unmanned aerial vehicle of this embodiment adopts small-size many rotor unmanned aerial vehicle, and small-size many rotor unmanned aerial vehicle can be four rotors, six rotors, eight rotors carry on the many rotor unmanned aerial vehicle of five camera lenses, also can be other types unmanned aerial vehicle that can realize five camera lenses aerial photograph, and small-size many rotor unmanned aerial vehicle takes photo by plane including the selection and the affirmation of taking a picture of control point and checkpoint, unmanned aerial vehicle field survey planning and implement this three process of field survey, and the concrete description is as follows:
(1) selecting and confirming the image control points and the check points: and (3) according to the size of the explosion area range of the goaf and the step distribution condition of the open stope, making a point placement plan of image control points and check points, ensuring the control requirements of elevation precision and plane precision, and performing point placement by adopting handheld RTK (real-time kinematic) to make a note of the point, thereby facilitating the identification of the puncture point at the later stage.
(2) Unmanned aerial vehicle field aerial survey planning: selecting a five-way flight mode according to the explosion area range, ensuring that the overlapping rate is higher than 80 percent, adjusting camera parameters according to weather conditions, and selecting a shutter to be preferred; and then generating an aerial survey plan, and needing to check again to ensure that the aerial survey plan is reasonable and feasible.
(3) Carrying out field operation aerial survey: and calling a specified aerial survey plan, and implementing the aerial survey plan according to the flight instruction. And if one rack cannot be completed, calling a plan in flight after the battery is replaced, continuing to carry out aerial survey according to the flight instruction until the operation task is completely completed, and acquiring all terrain and landform information of the explosion area.
In the embodiment, the small multi-rotor unmanned aerial vehicle in the steps (1) to (3) is subjected to aerial photography, and the image information of the explosion area and the periphery of the goaf in the two stages (two stages) before and after explosion can be obtained.
S103, analyzing the image information of the blast area and the periphery of the goaf by an aerial triangulation analysis method, and converting the image information of the blast area and the periphery of the goaf into three-dimensional dense point cloud data of the blast area of the goaf.
Specifically, the step S103 is an image matching and air-to-air computing process, which is implemented by professional aerial survey processing software (such as Smart 3D software and tangjiang wisdom diagram software), and includes: importing image information of an explosion area where the goaf is located and the periphery into professional aerial survey processing software, and firstly carrying out image matching analysis to ensure that the requirement of calculation by an aerial triangulation analytical method is met; then, importing coordinates of image control points and check points to carry out primary puncturing, ensuring that each image control point and each check point puncture at least image information of explosion areas and peripheries of continuous three goafs, and carrying out primary aerial triangle analysis method calculation on the image information after the primary puncturing to obtain a first calculation image; and performing secondary puncturing on the first resolved image, and performing secondary aerial triangulation analysis calculation on the first resolved image subjected to the secondary puncturing to obtain a second resolved image serving as three-dimensional dense point cloud data of the blast area where the goaf is located.
And S104, processing the three-dimensional dense point cloud data of the explosion area where the goaf is located to obtain a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located.
Specifically, the step S103 is an error analysis and model reconstruction process, which includes: checking the three-dimensional dense point cloud data of the blast area where the goaf is located through a quality report generated by air-three calculation and calculation, and judging whether the three-dimensional dense point cloud data of the blast area where the goaf is located meet the requirement of model reconstruction; if the three-dimensional dense point cloud data meet the requirement of model reconstruction, carrying out comprehensive analysis on error precision through a three-dimensional model precision error, an image control point error and a check point error, and judging whether the error precision meets the topographic map precision requirement of a preset proportion (1: 500); if not, returning to the step (1) in the step S102, and executing the subsequent steps until the topographic map drawing precision requirement with the preset proportion is met; if the three-dimensional model is satisfied, determining a model cutting block (divided into a plurality of block sections), selecting a coordinate system and obtaining a result type, and on the basis, performing model reconstruction to generate a pre-explosion three-dimensional model and a post-explosion three-dimensional model of an explosion area of the goaf, wherein the three-dimensional models comprise DOM, DSM, DEM and the like, and the pre-explosion three-dimensional model of the explosion area of the goaf and the post-explosion three-dimensional model of the explosion area of the goaf are two-stage three-dimensional models.
Further, through three-dimensional model precision error, image control point and check point error, carry out error accuracy integrated analysis, judge whether the error accuracy satisfies the topographic map picture accuracy requirement of preset proportion, specifically include:
A. and judging whether the three-dimensional dense point cloud data meets the aerial survey requirement or not according to the precision error of the three-dimensional model.
B. And if the three-dimensional dense point cloud data meet the aerial survey requirement, taking the image control point and the check point coordinates obtained by aerial survey as coordinate measurement values, and comparing and analyzing the coordinate measurement values with the real coordinate values.
C. And judging whether the error precision meets the topographic map drawing precision requirement of a preset proportion or not according to the comparison analysis result.
And S105, evaluating the blasting treatment effect of the goaf according to the pre-explosion and post-explosion three-dimensional models of the explosion area where the goaf is located, and meanwhile, based on the image information and the actual digging and loading feedback conditions of the explosion area and the periphery where the goaf is located, ensuring the reliability of evaluating the blasting treatment effect of the goaf and realizing the fine acceptance check of the goaf of the surface mine.
Specifically, the step S105 includes two processes of extraction and processing of three-dimensional model data before and after goaf explosion and refined evaluation of goaf treatment effect, which are specifically described as follows:
(1) extracting and processing three-dimensional model data before and after explosion in the goaf: the method comprises the steps of leading in pre-explosion and post-explosion three-dimensional models of an explosion area where a goaf is located into professional processing software (such as southern Idata software) with good compatibility and high integration degree, leading in goaf coordinates measured by a drilling type three-dimensional laser scanner to serve as a goaf actual range line, accurately reflecting the goaf in the pre-explosion and post-explosion three-dimensional models of the explosion area, automatically extracting all elevation point information of the explosion area where the goaf is located before and after explosion by utilizing in-plane extraction or on-line extraction of elevation point functions, carrying out further processing, obtaining elevation point information according with the actual site, really reducing the influence of explosion on the change of the spatial form of the goaf, and obtaining the change conditions of the elevation point information of the explosion area where the goaf before and after explosion are located.
(2) And (3) finely evaluating the treatment effect of the goaf: comprehensively evaluating the actual filling degree after blasting of the goaf according to the information change conditions of the elevation points of the blast areas of the goaf before and after blasting and by combining the loosening coefficient of the rock after blasting and the actual propelling distance of the blasting pile, wherein the actual filling degree after blasting of the goaf is the blasting treatment effect of the goaf; meanwhile, based on image information (including multi-angle pictures, recorded blasting videos and the like) of the blast area and the periphery of the goaf and actual digging and loading feedback conditions of the field excavator, blasting treatment effect evaluation reliability of the goaf is guaranteed in many ways, fine acceptance of the goaf of the surface mine is realized, and timely feedback analysis and later-stage design optimization are facilitated.
It should be noted that although the method operations of the above-described embodiments are depicted in the drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results. Rather, the depicted steps may change the order of execution. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
Example 2:
as shown in fig. 3, the present embodiment provides a surface mine goaf refinement acceptance system, which includes a first obtaining unit 301, a second obtaining unit 302, a parsing unit 303, a processing unit 304, and an acceptance unit 305, where the specific functions of each unit are as follows:
the first obtaining unit 301 obtains basic parameters of the gob detected by the three-dimensional laser scanner with drill holes.
The second obtaining unit 302 is configured to obtain image information of an explosion area and surrounding areas of the goaf acquired by the unmanned aerial vehicle during pre-explosion and post-explosion stages.
The analysis unit 303 is configured to analyze the image information of the blast area and the periphery of the gob by an aerial triangulation analysis method, and convert the image information of the blast area and the periphery of the gob into three-dimensional dense point cloud data of the blast area of the gob.
And the processing unit 304 is configured to process the three-dimensional dense point cloud data of the explosion area where the goaf is located, so as to obtain a pre-explosion and post-explosion three-dimensional model of the explosion area where the goaf is located.
And the acceptance unit 305 is used for evaluating the blasting treatment effect of the goaf according to the pre-explosion and post-explosion three-dimensional models of the explosion area where the goaf is located, and meanwhile, based on the image information and the actual excavation and loading feedback conditions of the explosion area and the periphery where the goaf is located, the reliability of the evaluation of the blasting treatment effect of the goaf is ensured, and the fine acceptance of the goaf of the surface mine is realized.
The specific implementation of each unit in this embodiment may refer to embodiment 1, which is not described herein any more; it should be noted that the system provided in this embodiment is only illustrated by the division of the functional units, and in practical applications, the above functions may be distributed by different functional units according to needs, that is, the internal structure is divided into different functional modules to complete all or part of the functions described above.
Example 3:
the present embodiment provides a computer device, which may be a computer, as shown in fig. 4, and includes a processor 402, a memory, an input device 403, a display 404, and a network interface 405 connected by a system bus 401, where the processor is used to provide computing and control capabilities, the memory includes a nonvolatile storage medium 406 and an internal memory 407, the nonvolatile storage medium 406 stores an operating system, a computer program, and a database, the internal memory 407 provides an environment for the operating system and the computer program in the nonvolatile storage medium to run, and when the processor 402 executes the computer program stored in the memory, the open pit mine goaf refinement acceptance method of embodiment 1 is implemented as follows:
acquiring image information of an explosion area and the periphery of the goaf acquired by the unmanned aerial vehicle during the pre-explosion stage and the post-explosion stage;
analyzing the image information of the explosion area and the periphery of the goaf by an aerial triangulation analysis method, and converting the image information of the explosion area and the periphery of the goaf into three-dimensional dense point cloud data of the explosion area of the goaf;
processing three-dimensional dense point cloud data of an explosion area where the goaf is located to obtain a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located;
and evaluating the blasting treatment effect of the goaf according to the pre-explosion and post-explosion three-dimensional models of the explosion area where the goaf is located, and simultaneously, based on the image information and the actual excavation and installation feedback conditions of the explosion area and the periphery where the goaf is located, ensuring the reliability of evaluating the blasting treatment effect of the goaf and realizing the fine acceptance check of the goaf of the surface mine.
Further, before exploding and exploding the back stage, acquire the collecting space area that unmanned aerial vehicle aerial photograph gathered and explode district and peripheral image information before, still include:
and acquiring basic parameters of the gob detected by the drilling type three-dimensional laser scanner.
Example 4:
the present embodiment provides a storage medium, which is a computer-readable storage medium, and stores a computer program, and when the computer program is executed by a processor, the method for the strip mine goaf fine acceptance check of embodiment 1 is implemented as follows:
acquiring image information of an explosion area and the periphery of the goaf acquired by the unmanned aerial vehicle during the pre-explosion stage and the post-explosion stage;
analyzing the image information of the explosion area and the periphery of the goaf by an aerial triangulation analysis method, and converting the image information of the explosion area and the periphery of the goaf into three-dimensional dense point cloud data of the explosion area of the goaf;
processing three-dimensional dense point cloud data of an explosion area where the goaf is located to obtain a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located;
and evaluating the blasting treatment effect of the goaf according to the pre-explosion and post-explosion three-dimensional models of the explosion area where the goaf is located, and simultaneously, based on the image information and the actual excavation and installation feedback conditions of the explosion area and the periphery where the goaf is located, ensuring the reliability of evaluating the blasting treatment effect of the goaf and realizing the fine acceptance check of the goaf of the surface mine.
Further, before exploding and exploding the back stage, acquire the collecting space area that unmanned aerial vehicle aerial photograph gathered and explode district and peripheral image information before, still include:
and acquiring basic parameters of the gob detected by the drilling type three-dimensional laser scanner.
It should be noted that the computer readable storage medium of the present embodiment may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In conclusion, the invention collects the image information of the blast area and the periphery of the goaf in the pre-blast stage and the post-blast stage by applying the unmanned aerial vehicle aerial survey technology, analyzing the image information of the blast area and the periphery of the goaf by an aerial triangulation analysis method, converting the image information into three-dimensional dense point cloud data of the blast area of the goaf, the three-dimensional dense point cloud data is processed to obtain a three-dimensional model before explosion and a three-dimensional model after explosion of an explosion area where the goaf is located, evaluating the blasting treatment effect of the goaf according to the three-dimensional models of the blast area before and after blast of the goaf, meanwhile, based on the image information of the blast area where the goaf is located and the surrounding image information and the actual excavation and loading feedback condition, the blasting treatment effect evaluation reliability of the goaf is guaranteed, the goaf of the surface mine is subjected to fine acceptance check, timely feedback analysis and later design optimization are facilitated, and the method has important significance for goaf standardized management.
The above description is only for the preferred embodiments of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art can substitute or change the technical solution and the inventive concept of the present invention within the scope of the present invention.
Claims (10)
1. A method for finely inspecting and accepting a gob of a surface mine is characterized by comprising the following steps:
acquiring image information of an explosion area and the periphery of the goaf acquired by the unmanned aerial vehicle during the pre-explosion stage and the post-explosion stage;
analyzing the image information of the explosion area and the periphery of the goaf by an aerial triangulation analysis method, and converting the image information of the explosion area and the periphery of the goaf into three-dimensional dense point cloud data of the explosion area of the goaf;
processing three-dimensional dense point cloud data of an explosion area where the goaf is located to obtain a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located;
and evaluating the blasting treatment effect of the goaf according to the pre-explosion and post-explosion three-dimensional models of the explosion area where the goaf is located, and simultaneously, based on the image information and the actual excavation and installation feedback conditions of the explosion area and the periphery where the goaf is located, ensuring the reliability of evaluating the blasting treatment effect of the goaf and realizing the fine acceptance check of the goaf of the surface mine.
2. The method for conducting fine analysis and collection on a goaf of a surface mine according to claim 1, wherein before acquiring the image information of the goaf in the blast area and the periphery acquired by the unmanned aerial vehicle in the pre-blast stage and the post-blast stage, the method further comprises:
and acquiring basic parameters of the gob detected by the drilling type three-dimensional laser scanner.
3. The method for conducting fine analysis on the goaf of the surface mine according to any one of claims 1 to 2, wherein the analyzing the image information of the blast area and the periphery of the goaf by the aerial triangulation method to convert the image information of the blast area and the periphery of the goaf into three-dimensional dense point cloud data of the blast area of the goaf specifically comprises:
carrying out automatic image matching analysis on the image information of the blast area where the goaf is located and the periphery of the goaf, and ensuring that the requirement of calculation of an aerial triangulation method is met;
importing coordinates of image control points and check points to perform primary puncturing, and ensuring that each image control point and check point punctures at least image information of explosion areas and peripheries of continuous three goafs;
performing first aerial triangulation analytical method calculation on the image information after the first pricking to obtain a first resolving image;
and performing secondary puncturing on the first resolved image, and performing secondary aerial triangulation analysis calculation on the first resolved image subjected to the secondary puncturing to obtain a second resolved image serving as three-dimensional dense point cloud data of the blast area where the goaf is located.
4. The method for conducting fine analysis on a goaf of a surface mine according to any one of claims 1 to 2, wherein the processing of the three-dimensional dense point cloud data of the blast area where the goaf is located to obtain the pre-blast and post-blast three-dimensional models of the blast area where the goaf is located specifically comprises:
judging whether the three-dimensional dense point cloud data of the blast area where the goaf is located meet the requirement of model reconstruction;
if the three-dimensional dense point cloud data meet the requirement of model reconstruction, carrying out comprehensive analysis on error precision through a three-dimensional model precision error, an image control point error and a check point error, and judging whether the error precision meets the topographic map mapping precision requirement of a preset proportion;
and if the three-dimensional dense point cloud data meets the topographic map mapping accuracy requirement of a preset proportion, determining model blocks, selecting a coordinate system and a result type, and performing model reconstruction to generate a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located.
5. The method for conducting fine analysis on the goaf of the surface mine according to claim 4, wherein the comprehensive analysis on the error precision is conducted through the three-dimensional model precision error, the image control point error and the check point error, and whether the error precision meets the topographic map accuracy requirement of a preset proportion is judged, and the method specifically comprises the following steps:
judging whether the three-dimensional dense point cloud data meet the aerial survey requirement or not according to the precision error of the three-dimensional model;
if the three-dimensional dense point cloud data meet the aerial survey requirement, taking image control points and check point coordinates obtained by aerial survey as coordinate measurement values, and comparing and analyzing the coordinate measurement values with real coordinate values;
and judging whether the error precision meets the topographic map drawing precision requirement of a preset proportion or not according to the comparison analysis result.
6. The method for conducting fine analysis on the goaf of the surface mine according to any one of claims 1 to 2, wherein the evaluating the blasting effect of the goaf according to the three-dimensional models of the pre-blasting area and the post-blasting area of the goaf specifically comprises:
guiding in range coordinates of the goaf based on the pre-explosion and post-explosion three-dimensional models of the goaf in the explosion area, extracting all elevation point information of the goaf before explosion and the goaf after explosion, and performing further processing to obtain elevation point information which accords with the actual situation, thereby obtaining the elevation point information change conditions of the goaf before explosion and the goaf after explosion;
and evaluating the blasting treatment effect of the goaf according to the information change conditions of the elevation points of the blast areas of the goaf before and after blasting.
7. The method for conducting fine analysis and collection in a goaf of a surface mine according to claim 6, wherein the blast treatment effect of the goaf is evaluated according to the information change of the elevation points of the blast zones of the goaf before and after blasting, and specifically comprises the following steps:
and comprehensively evaluating the actual filling degree after explosion of the goaf according to the information change conditions of the elevation points of the blast areas of the goaf before and after explosion and by combining the loosening coefficient of the rock after explosion and the actual propelling distance of the blasting pile.
8. The utility model provides a surface mine collecting space area acceptance inspection system that becomes more meticulous which characterized in that, the system includes:
the acquisition unit is used for acquiring image information of an explosion area and the periphery of the explosion area of the goaf acquired by the unmanned aerial vehicle in aerial photography at the pre-explosion stage and the post-explosion stage;
the analysis unit is used for analyzing the image information of the blast area and the periphery of the goaf by an aerial triangulation analysis method and converting the image information of the blast area and the periphery of the goaf into three-dimensional dense point cloud data of the blast area of the goaf;
the processing unit is used for processing the three-dimensional dense point cloud data of the explosion area where the goaf is located to obtain a pre-explosion three-dimensional model and a post-explosion three-dimensional model of the explosion area where the goaf is located;
and the acceptance unit is used for evaluating the blasting treatment effect of the goaf according to the pre-explosion and post-explosion three-dimensional models of the explosion area where the goaf is located, and simultaneously, based on the image information and the actual digging and loading feedback condition of the explosion area and the periphery where the goaf is located, the reliability of evaluation of the blasting treatment effect of the goaf is ensured, and the refined acceptance of the goaf of the surface mine is realized.
9. A computer apparatus comprising a processor and a memory for storing a program executable by the processor, wherein the processor, when executing the program stored in the memory, implements the surface mine gob refinement collection method of any one of claims 1 to 7.
10. A storage medium storing a program, wherein the program, when executed by a processor, implements the surface mine gob refinement collection method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110254879.2A CN112861375B (en) | 2021-03-09 | 2021-03-09 | Fine acceptance method, system, equipment and medium for goaf of surface mine |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110254879.2A CN112861375B (en) | 2021-03-09 | 2021-03-09 | Fine acceptance method, system, equipment and medium for goaf of surface mine |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112861375A true CN112861375A (en) | 2021-05-28 |
| CN112861375B CN112861375B (en) | 2023-10-20 |
Family
ID=75994798
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110254879.2A Active CN112861375B (en) | 2021-03-09 | 2021-03-09 | Fine acceptance method, system, equipment and medium for goaf of surface mine |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112861375B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116753907A (en) * | 2023-08-18 | 2023-09-15 | 中国电建集团昆明勘测设计研究院有限公司 | Method, device, equipment and storage medium for detecting underground deep cavity |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104240133A (en) * | 2014-09-02 | 2014-12-24 | 广东宏大爆破股份有限公司 | Acceptance inspection method of mine goaf caving and blasting treatment effect in conversion from underground mining to opencast mining |
| CN106968673A (en) * | 2017-02-27 | 2017-07-21 | 中铁十九局集团有限公司 | metal surface mine goaf treatment method |
| US20200102825A1 (en) * | 2018-09-27 | 2020-04-02 | Taiyuan University Of Technology | Physical simulation test method for detecting position of ponding goaf in excavation |
-
2021
- 2021-03-09 CN CN202110254879.2A patent/CN112861375B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104240133A (en) * | 2014-09-02 | 2014-12-24 | 广东宏大爆破股份有限公司 | Acceptance inspection method of mine goaf caving and blasting treatment effect in conversion from underground mining to opencast mining |
| CN106968673A (en) * | 2017-02-27 | 2017-07-21 | 中铁十九局集团有限公司 | metal surface mine goaf treatment method |
| US20200102825A1 (en) * | 2018-09-27 | 2020-04-02 | Taiyuan University Of Technology | Physical simulation test method for detecting position of ponding goaf in excavation |
Non-Patent Citations (7)
| Title |
|---|
| 周科平 等: "复杂充填体下矿体开采安全顶板厚度非线性预测方法", 中南大学学报(自然科学版), vol. 36, no. 06, pages 1094 - 1096 * |
| 张兵兵 等: "基于无人机航测技术的多类型矿石堆场两期储量分析", 《中国矿业》 * |
| 张兵兵 等: "基于无人机航测技术的多类型矿石堆场两期储量分析", 《中国矿业》, vol. 30, no. 2, 28 February 2021 (2021-02-28), pages 80 - 83 * |
| 李新宁等: "Smart3D在空三解算及模型生产方面的探讨", 《新疆有色金属》 * |
| 李新宁等: "Smart3D在空三解算及模型生产方面的探讨", 《新疆有色金属》, no. 01, 15 February 2020 (2020-02-15), pages 48 - 49 * |
| 谭金石等: "多旋翼无人机在露天矿区测绘中的应用", 《矿山测量》 * |
| 谭金石等: "多旋翼无人机在露天矿区测绘中的应用", 《矿山测量》, no. 03, 15 June 2020 (2020-06-15), pages 101 - 103 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116753907A (en) * | 2023-08-18 | 2023-09-15 | 中国电建集团昆明勘测设计研究院有限公司 | Method, device, equipment and storage medium for detecting underground deep cavity |
| CN116753907B (en) * | 2023-08-18 | 2023-11-10 | 中国电建集团昆明勘测设计研究院有限公司 | Method, device, equipment and storage medium for detecting underground deep cavity |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112861375B (en) | 2023-10-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102798412B (en) | Method for evaluating construction quality of tunnel drilling and blasting based on three-dimensional laser scanning | |
| WO2023185734A1 (en) | Mine digital model construction method based on three-dimensional point cloud database | |
| CN111441330A (en) | Foundation pit monitoring system and method based on BIM + GIS | |
| Albarelli et al. | Identification of potential rockfall sources using UAV-derived point cloud | |
| CN113362469B (en) | Shield tunnel construction early warning method integrating city building information and stratum structure | |
| CN111191307B (en) | Earthwork virtual construction method based on BIM+GIS technology | |
| Luo et al. | Cavity 3D modeling and correlative techniques based on cavity monitoring | |
| Jarosz et al. | Open stope cavity monitoring for the control of dilution and ore loss | |
| Feng et al. | A survey of 3D laser scanning techniques for application to rock mechanics and rock engineering | |
| CN110544313A (en) | shovel loading equipment, shovel loading guiding method, device, equipment and storage medium thereof | |
| CN111986321B (en) | Three-dimensional geological modeling method, device, equipment and storage medium | |
| CN211123324U (en) | BIM + GIS-based advanced geological forecast information system for tunnel construction | |
| CN114459656A (en) | Three-dimensional identification method and device for disturbance stress evolution process of underground cavern surrounding rock | |
| KR101104466B1 (en) | System and method for surveying tunnel using digital image | |
| CN112861375B (en) | Fine acceptance method, system, equipment and medium for goaf of surface mine | |
| Benton et al. | Photogrammetry in underground mining ground control—Lucky Friday mine case study | |
| CN105651202A (en) | Three-dimensional scanning method and device used for measuring volume of mine | |
| CN112785706B (en) | Method, system, equipment and medium for dynamically analyzing reserves of multi-type ore storage yard | |
| CN109557284B (en) | Tunnel surrounding rock level intelligent rapid determination system and method | |
| Hong et al. | Virtual reality (VR)–based intelligent tunneling information system | |
| Medinac | Advances in pit wall mapping and slope assessment using unmanned aerial vehicle technology | |
| Nguyen et al. | Application of Unmanned Aerial Vehicles for Surveying and Mapping in Mines: A Review | |
| Warneke et al. | Use of a 3-D scanning laser to quantify drift geometry and overbreak due to blast damage in underground manned entries | |
| Yuan et al. | Joint investigation and 3D visual evaluation of rock mass quality | |
| Donovan et al. | The application of three-dimensional imaging to rock discontinuity characterization |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |