CN116151482B - Method, device, equipment and medium for predicting mining earthwork of open-pit mining area - Google Patents
Method, device, equipment and medium for predicting mining earthwork of open-pit mining area Download PDFInfo
- Publication number
- CN116151482B CN116151482B CN202310382278.9A CN202310382278A CN116151482B CN 116151482 B CN116151482 B CN 116151482B CN 202310382278 A CN202310382278 A CN 202310382278A CN 116151482 B CN116151482 B CN 116151482B
- Authority
- CN
- China
- Prior art keywords
- mining area
- earthwork
- open
- mined
- pit mining
- 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.)
- Active
Links
- 238000005065 mining Methods 0.000 title claims abstract description 286
- 238000000034 method Methods 0.000 title claims abstract description 38
- 230000003287 optical effect Effects 0.000 claims abstract description 31
- 238000000605 extraction Methods 0.000 claims abstract description 26
- 238000012876 topography Methods 0.000 claims description 10
- 238000009412 basement excavation Methods 0.000 claims description 4
- 229910052500 inorganic mineral Inorganic materials 0.000 description 12
- 239000011707 mineral Substances 0.000 description 12
- 238000012544 monitoring process Methods 0.000 description 12
- 238000005516 engineering process Methods 0.000 description 9
- 230000008859 change Effects 0.000 description 7
- 238000012937 correction Methods 0.000 description 7
- 230000000694 effects Effects 0.000 description 6
- 230000008569 process Effects 0.000 description 6
- 238000011160 research Methods 0.000 description 5
- 238000013473 artificial intelligence Methods 0.000 description 4
- 238000013135 deep learning Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 230000004927 fusion Effects 0.000 description 4
- 238000007781 pre-processing Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- 229910052751 metal Inorganic materials 0.000 description 3
- 239000002184 metal Substances 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000011439 discrete element method Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 238000009432 framing Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000001737 promoting effect Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- CWYNVVGOOAEACU-UHFFFAOYSA-N Fe2+ Chemical compound [Fe+2] CWYNVVGOOAEACU-UHFFFAOYSA-N 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000004566 building material Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000013136 deep learning model Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000007935 neutral effect Effects 0.000 description 1
- 229910000510 noble metal Inorganic materials 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 239000002910 solid waste Substances 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Marketing (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Life Sciences & Earth Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Operations Research (AREA)
- Agronomy & Crop Science (AREA)
- Animal Husbandry (AREA)
- Marine Sciences & Fisheries (AREA)
- Mining & Mineral Resources (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Entrepreneurship & Innovation (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The embodiment of the specification discloses a method, a device, equipment and a medium for predicting the exploitation earthwork of an open-pit mining area, comprising the following steps: acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range; inputting the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area; acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle; determining a working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range; determining Digital Elevation Model (DEM) data related to the terrain of the designated open-pit mining area according to the image data and the boundary range; and predicting the mining earthwork of the designated open-pit mining area according to the working vehicle and the DEM data.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a medium for predicting a mining earthwork of an open-pit mining area.
Background
The mineral resources in China are rich, and can be classified into energy mineral, ferrous metal mineral, nonferrous metal mineral, rare metal mineral, noble metal mineral, metallurgical auxiliary materials, chemical raw materials, special types, water vapor mineral, building materials, other mineral resources and the like according to different purposes of the mineral resources. Mineral resources are an important material basis for economic and social development.
The optical remote sensing satellite has incomparable advantages of real-time, rapid, macroscopic and large-area synchronous observation, has the characteristics of good objectivity and high timeliness in the aspects of acquiring the current situation and dynamic change information of regional mineral resources, can continuously observe the mineral resources in the same region for a long time, forms an integrated multidimensional information set of time and space, and provides rapid, global, objective and reliable fact basis for evaluating the mining activity condition of the strip mine for related enterprises.
Traditional evaluation of opencast mining activity is mainly based on daily management of mining areas, and depends on records of operations and management staff. The method has the advantages of low speed, large workload, high cost, no comparability and large influence by human factors.
Disclosure of Invention
One or more embodiments of the present disclosure provide a method, an apparatus, a device, and a medium for predicting a mining earthwork of an open-pit mining area, which are used to solve the technical problems set forth in the background art.
One or more embodiments of the present disclosure adopt the following technical solutions:
one or more embodiments of the present specification provide a method for predicting a mining earthwork of an open-pit mining area, including:
acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range;
inputting the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
determining a working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range;
determining Digital Elevation Model (DEM) data related to the terrain of the designated open-pit mining area according to the image data and the boundary range;
and predicting the mining earthwork of the designated open-pit mining area according to the working vehicle and the DEM data.
An apparatus for predicting a mining earthwork of an open-pit mining area according to one or more embodiments of the present specification includes:
the image data acquisition unit acquires image data of a specified open-air mining area through an optical remote sensing satellite in a preset time range;
the boundary range determining unit inputs the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
determining sample library data, and acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
a work vehicle determining unit that determines a work vehicle of the designated open pit mining area based on the image data, the sample library data, and the boundary range;
a DEM data determining unit for determining digital elevation model DEM data related to the terrain of the designated open pit mining area according to the image data and the boundary range;
and the exploitation earthwork prediction unit predicts the exploitation earthwork of the appointed open-pit mining area according to the working vehicle and the DEM data.
One or more embodiments of the present specification provide a mining earth volume prediction apparatus for an open-pit mining area, including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range;
inputting the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
determining a working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range;
determining Digital Elevation Model (DEM) data related to the terrain of the designated open-pit mining area according to the image data and the boundary range;
and predicting the mining earthwork of the designated open-pit mining area according to the working vehicle and the DEM data.
One or more embodiments of the present specification provide a non-volatile computer storage medium storing computer-executable instructions configured to:
acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range;
inputting the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
determining a working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range;
determining Digital Elevation Model (DEM) data related to the terrain of the designated open-pit mining area according to the image data and the boundary range;
and predicting the mining earthwork of the designated open-pit mining area according to the working vehicle and the DEM data.
The above-mentioned at least one technical scheme that this description embodiment adopted can reach following beneficial effect:
according to the embodiment of the specification, the problem that the mining state of an open-air mining area enterprise cannot be timely and effectively obtained can be solved, and data support can be provided for obtaining the mining condition and the mining amount information of the open-air mining area in a large range and timely knowing the development condition of social economy by remote sensing monitoring of the data of the operation vehicles and the earthwork amount data in the open-air mining area.
Drawings
In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some of the embodiments described in the present description, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a flow diagram of a method for predicting the amount of mined earth in a mining area according to one or more embodiments of the present disclosure;
FIG. 2 is a schematic structural view of a mining earth volume prediction apparatus for an open pit mining area according to one or more embodiments of the present disclosure;
fig. 3 is a schematic structural view of a mining earth volume prediction apparatus for an open pit mining area according to one or more embodiments of the present disclosure.
Detailed Description
The embodiment of the specification provides a method, a device, equipment and a medium for predicting the exploitation earthwork of an open-pit mining area.
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present disclosure.
FIG. 1 is a schematic flow diagram of a method for predicting a mining earthwork of an open-pit mining area, which may be performed by an open-pit mining area mining earthwork prediction system, in accordance with one or more embodiments of the present disclosure. Some input parameters or intermediate results in the flow allow for manual intervention adjustments to help improve accuracy.
The method flow steps of the embodiment of the present specification are as follows:
s102, acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range.
In the embodiment of the specification, in a preset time range, an optical remote sensing satellite with resolution better than 1 meter can be used for monitoring a specified open-air mining area, so that image data of different time points can be obtained. In addition, image data at different points in time may also be preprocessed.
The preprocessing can be to perform preprocessing such as orthographic correction, atmospheric correction, fusion, registration, mosaic, clipping and the like on the image data at different time points to form a high-precision orthographic image.
And S104, inputting the image data into a pre-trained strip mine boundary extraction model to obtain a boundary range corresponding to the appointed strip mine.
In the embodiment of the specification, the open-air mining area boundary extraction model can adopt an artificial intelligence technology, and particularly can be trained by adopting a full convolution neural network in a TensorFlow deep learning framework according to the characteristics of remote sensing images of the open-air mining area.
It should be noted that the boundary ranges may provide basis data for the determination of the work vehicles in the subsequent strip mine and the determination of the amount of mined earth in the strip mine.
S106, acquiring sample library data of the predetermined working vehicle and the non-working vehicle.
In the embodiments of the present description, sample library data for work vehicles and non-work vehicles may be created based on different characteristics of the work vehicles and non-work vehicles within a given strip mine.
S108, determining the working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range.
In the embodiment of the specification, the information of the working vehicle and the non-working vehicle in the range of the open-air mining area can be identified by utilizing the YOLOv5 model, the non-working vehicle is removed, and the model parameters are continuously adjusted, so that the capability of efficiently and accurately identifying the working vehicle and the non-working vehicle is met. In addition, in order to improve the accuracy of identifying the working vehicles in the range of the designated open-pit mining area, the manually revised working vehicles which are missed and misplaced can be carried out, so that the vector data of the working vehicles in the boundary range can be obtained, and the attribute information can be filled in.
S110, determining digital elevation model DEM data related to the terrain of the designated open pit mining area according to the image data and the boundary range.
In the embodiment of the present disclosure, image data acquired by an optical remote sensing satellite may be subjected to processes such as inputting a stereopair, defining ground control, defining a connection point, setting an output parameter, outputting a DEM, checking the DEM, and editing the DEM to form DEM data. DEM (Digital Elevation Model ) is a physical floor model that implements a digital simulation of the floor topography (i.e., a digital representation of the topography surface morphology) with limited topography elevation data, which may be represented as a set of ordered arrays of values.
In this embodiment of the present disclosure, the DEM data may include first DEM data corresponding to an initial time and second DEM data corresponding to a final time within the preset time range, for example, the preset time range is 3 months to 5 months, the first DEM data may be DEM data corresponding to 3 months and 1 day, and the second DEM data may be DEM data corresponding to 5 months and 31 days.
In the embodiment of the present specification, when determining the digital elevation model DEM data related to the topography of the designated open-pit mining area according to the image data and the boundary range, sample image data of a preset time range of the designated open-pit mining area in the image data may be determined according to the boundary range; and obtaining the first DEM data and the second DEM data related to the terrain according to the sample image data.
S112, predicting the mining earthwork of the designated open-pit mining area according to the working vehicle and the DEM data.
In the embodiment of the present disclosure, a terrain difference result of the specified open pit mining area may be obtained according to the first DEM data and the second DEM data; and predicting the first mining earthwork of the designated open-pit mining area according to the terrain difference result.
Further, in the embodiment of the present disclosure, when predicting the first mined earthwork of the specified open-pit mining area according to the terrain difference result, the area of the excavated area and the area of the filled area may be determined according to the terrain difference result; and predicting the first mining earth volume according to the difference result of the area of the excavated area and the topography.
Further, in the embodiment of the present disclosure, when predicting the first mined earthwork according to the difference result between the area of the excavated area and the terrain, the first mined earthwork may be predicted according to a preset formula, where: the preset formula is: terrain differential result x excavated area = amount of mined earth.
In the embodiment of the specification, when predicting the second extraction earthwork of the designated open-pit mining area according to the working vehicle, the working time and type of the working vehicle can be determined within a preset time range;
and predicting the second mining earth volume of the designated open-pit mining area according to the working time and the type of the working vehicle, for example, the preset time range is 3 months and 1 day, the designated open-pit mining area comprises a working vehicle A, a working vehicle B and a working vehicle C, the working vehicle A and the working vehicle C are of a type a, the working vehicle B is of a type B, the mining earth volume of the type a is C/hour, the mining earth volume of the type B is d/hour, the working time of the working vehicle A is 5 hours, the working time of the working vehicle B is 7 hours, and the working time of the working vehicle C is 10 hours, so that the second mining earth volume of the designated open-pit mining area can be predicted according to the data.
In the embodiment of the present disclosure, the mined earthwork of the specified open-air mining area may be predicted according to the first mined earthwork and the second mined earthwork obtained above, and in the process of predicting the mined earthwork of the specified open-air mining area, a difference value between the first mined earthwork and the second mined earthwork may be determined; if the difference is lower than a preset threshold, the first extracted earthwork amount can be set as the extracted earthwork amount of the specified open-air mining area, and the process can show that the first extracted earthwork amount is checked through the second extracted earthwork amount, so that the predicted extracted earthwork amount of the specified open-air mining area is more accurate. Meanwhile, if the difference value is lower than a preset threshold value, the second mining earth volume can be set as the mining earth volume of the appointed open-air mining area, and the process can be used for verifying the second mining earth volume through the first mining earth volume, so that the predicted mining earth volume of the appointed open-air mining area is more accurate.
It should be noted that, the embodiment of the present disclosure may also be applied to open-pit mining activity remote sensing monitoring, where the open-pit mining activity remote sensing monitoring may include three contents of extraction of a mining area boundary range, identification and positioning of an operation vehicle in the mining area, and measurement and calculation of mining area mining earthwork. At present, domestic and foreign scholars have obtained a large number of research results in mining area earth surface element type identification and classification and mining area geological environment monitoring, but the research on the mining activity of an open-air mining area is less, the mining activity of different mining areas is evaluated through high-resolution optical satellite remote sensing data, the mining area boundary range is determined based on a deep learning and manual revising method, evaluation indexes comprise the number of working vehicles in the mining area and the change of mining earth volume in the mining area, the mining state of the mining area and the main mining area in the mining area can be judged according to the number of the working vehicles in the mining area, and the mining yield can be indirectly evaluated according to the type of the working vehicles; the mining earthwork quantity in the mining area is monitored through the optical satellite remote sensing data with high resolution in multiple periods, data and technical support are provided for grasping mining state and estimating mining quantity of the mining area, and scientific basis is provided for promoting effective protection and reasonable utilization of national mine resource reserves.
The method for predicting the mining earthwork of the open-pit mining area according to the embodiment of the present disclosure may specifically include the following steps:
and firstly, monitoring a mining area by utilizing a high-precision optical remote sensing satellite, and preprocessing each image data.
The high-precision optical satellite has good selection quality, clear images and no cloud and fog coverage in mining areas, and the resolution is better than 1 meter.
And carrying out orthographic correction, image fusion, image mosaic, registration and other processing on the high-resolution optical remote sensing satellite data, and carrying out framing clipping to form a high-resolution orthographic image of the open-pit mining area.
And secondly, extracting the range data of the open-pit mining area by using an artificial intelligence technology based on the high-resolution optical remote sensing orthophoto map of the open-pit mining area, and providing basic data for determining the operation vehicles in the mining area and calculating the mining area exploitation amount.
Step 201, analyzing interpretation marks of open-air mining areas of multi-source high-precision optical remote sensing images and establishing a sample library
According to the data of different resolutions and different satellite image sources (domestic high-resolution first, domestic high-resolution second, domestic high-resolution sixth and domestic high-resolution seventh), different types of mining areas, such as a typical open-air mining area, an open-air mining area with water bodies, an open-air mining area with buildings and an open-air mining area with solid wastes, are selected, remote sensing image open-air mining area interpretation marks of different mining area types are established, and a manual visual interpretation method is adopted to collect and establish a multi-source remote sensing image open-air mining area sample library according to the training sample requirements of a deep learning model.
Step 202, selecting an open-pit mining area boundary intelligent extraction model and evaluating precision
According to the characteristics of the remote sensing images of the open-pit mining areas, a full convolution neural network in a TensorFlow deep learning framework is utilized to design an open-pit mining area boundary extraction model of the remote sensing images, and parameter tuning research is carried out to evaluate the accuracy of the open-pit mining area boundary intelligent extraction model.
Step 203, manual revising of open pit boundaries
In order to improve the boundary precision of the open-pit mining area range, the mining area with missed extraction, wrong extraction and errors in the boundary is manually revised to obtain the mining area range vector data.
And thirdly, identifying the operation vehicle in the open pit by utilizing a small target detection technology based on the high-resolution optical remote sensing orthophoto data and the open pit range vector data acquired in the second step.
Step 301, construction of sample library of working vehicle and non-working vehicle
Based on different characteristics of the work vehicle and the non-work vehicle in the orthophoto data mining area, a work vehicle and a non-work vehicle sample library is established.
Step 302, selecting a vehicle target recognition model and adjusting parameters
And (3) superposing the orthophoto data and the open-air mining area range vector data obtained in the step (II), identifying the information of the operation vehicle and the non-operation vehicle in the open-air mining area range by using a YOLOv5 model, removing the non-operation vehicle, and continuously adjusting model parameters to ensure that the capacity of efficiently and accurately identifying the operation vehicle and the non-operation vehicle is met.
Step 303, work vehicle manual revision
In order to improve the accuracy of the identification of the working vehicles in the open-pit mining area, the manually revised working vehicles which are missed and misplaced are carried out, so that the vector data of the working vehicles in the mining area are obtained, and the attribute information is filled.
And fourthly, obtaining DEM data by using high-score seventh data, and obtaining the mining earthwork volume by multiplying the terrain difference result by the area of the change area.
And 401, utilizing the two-phase optical satellite remote sensing data with stereo pairs to form DEM product data through the processes of inputting the stereo pairs, defining ground control, defining connection points, setting output parameters, outputting the DEM, checking the DEM, editing the DEM and the like.
And step 402, carrying out spatial correction on the DEM data of the other period by taking the latest period as a reference, wherein the correction error is smaller than 1-2 pixels.
Step 403, calculating the change between two DEMs by using the "3D analysis tool\grid calculation\subtraction" function in ARCGIS software.
And 404, drawing the range of the change area according to the terrain difference result, and determining the areas of the excavation area and the filling area. The mining earth volume in the mining area is calculated by using the 'topography difference result multiplied by the area of the excavated area = mining earth volume'.
It should be noted that, the embodiment of the specification can solve the problem that the mining state of the open-air mining area enterprises can not be timely and effectively obtained, and the remote sensing monitoring of the data of the operation vehicles and the earthwork data in the open-air mining area can provide data support for obtaining the mining condition and the mining amount information of the open-air mining area in a large scale and timely knowing the development condition of the society and economy.
Meanwhile, the embodiment of the specification utilizes the front edge technology deep learning technology to identify the range of the open-pit mining area, and combines manual revision, so that the remote sensing monitoring working efficiency and precision of the open-pit mining area can be greatly improved.
In addition, the embodiment of the specification provides a reliable basis for promoting effective protection and reasonable utilization of mine resource reserves by remote sensing monitoring of the working vehicles and earthwork in the open-pit mining areas, and also provides a new objective and neutral heterogeneous data for related mining area enterprises and related enterprises to master mining area exploitation conditions.
The following description will take multi-period high-resolution remote sensing satellite data of an open-pit mining area a as an example, and describes a method for predicting the earth volume of mining of the open-pit mining area provided in the embodiment of the present description:
the method comprises the steps of carrying out orthographic correction, image fusion, image mosaic, image registration and the like on high-resolution seventh optical remote sensing satellite data, and carrying out framing cutting to form a high-resolution orthographic image map of the open-air mining area A.
And step two, extracting the range data of the open air mining area by using an artificial intelligence technology and an artificial revising method based on the high-resolution optical remote sensing orthophotomap of the open air mining area A.
The method is based on high-resolution optical satellite image data of the seventh high-resolution optical satellite, the range of the A strip mining area is extracted by utilizing an artificial intelligence technology, the accuracy reaches about 78%, and although the accuracy is not particularly high, the method can provide a position reference for rapid monitoring of the mining area in a large range and provide reference data for developing the aspects of working vehicles, exploitation quantity, ecological restoration of mines and the like in the mining area. In order to improve the boundary precision of the open-pit area range, the open-pit area range vector data is obtained by manually revising the mining areas with missed extraction, wrong extraction and errors in the boundary.
And thirdly, identifying the operation vehicle in the open pit based on the high-resolution optical remote sensing orthophoto data and the open pit range vector data acquired in the second step.
The method comprises the steps of preprocessing the high-resolution seventh model to form orthographic image data in the mining area through orthographic correction, fusion, cutting and the like, identifying information of operation vehicles and non-operation vehicles in the mining area through a small target detection technology YOLOv5 model, eliminating the non-operation vehicles to obtain the operation vehicle data in the mining area, manually revising the operation vehicles in the mining area by utilizing a visual interpretation method to ensure automatic extraction accuracy, filling in an attribute table, and finally monitoring that 15 operation vehicles exist in the mining area in 2021 in 1 month and 15 days, wherein the mining area is in an excavation stage. And the accuracy verification is carried out by contacting mining area enterprises to consult historical ledger data, the accuracy reaches 98%, and the total number of the working vehicles is less than 1.
And fourthly, monitoring the amount of the exploited earthwork in the mining area through two-stage high-resolution optical stereopair satellite remote sensing data.
Firstly, an open-pit mining area of research A is selected as a topography change quantitative extraction research area, and 1m resolution DEM obtained by three-dimensional relative extraction of a high-resolution seven satellite in 2021 month 1 and 1m resolution DEM obtained by the high-resolution seven satellite in 2022 month 3 are adopted for comparison analysis. Secondly, taking the data of the seventh high score of 3 months in 2022 as a reference, adopting a manual selection of an invariable target with obvious topographic features as a control point, and correcting the data of 1 months in 2021 by using a least square method. Again, the two-phase DEM-to-DEM variation was calculated after two-phase data registration using the "3D analysis tool \grid calculation\subtraction" function in the ARCGIS software. And then, drawing the range of the change area according to the terrain difference result, and determining the areas of the excavation area and the filling area. Finally, using the terrain differential result x the area of the excavated area = the amount of earth mined, it can be seen that the amount of earth mined in the mining area from 1 month in 2021 to 3 months in 2022 reaches 458.34 ten thousand cubic meters, i.e. 458.34 ten thousand cubic meters of material is removed from the mining area.
Corresponding to the above embodiments, fig. 2 is a schematic structural diagram of a mining earth volume prediction apparatus for an open pit mining area according to one or more embodiments of the present disclosure, where the apparatus includes:
an image data acquisition unit 202 for acquiring image data of a specified open-air mining area through an optical remote sensing satellite within a preset time range;
a boundary range determining unit 204, configured to input the image data into a pre-trained strip mine boundary extraction model, to obtain a boundary range corresponding to the specified strip mine;
sample library data determination 206, obtaining sample library data of predetermined work vehicles and non-work vehicles;
a work vehicle determining unit 208 that determines a work vehicle of the designated open pit mining area based on the image data, the sample library data, and the boundary range;
a DEM data determining unit 210 for determining digital elevation model DEM data related to the topography of the designated open pit mining area according to the image data and the boundary range;
and a mined-earth volume prediction unit 212 for predicting the amount of mined earth in the specified open-pit mining area based on the work vehicle and the DEM data.
Corresponding to the above embodiments, fig. 3 is a schematic structural diagram of a mining earth volume prediction apparatus for an open-pit mining area according to one or more embodiments of the present disclosure, including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range;
inputting the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
determining a working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range;
determining Digital Elevation Model (DEM) data related to the terrain of the designated open-pit mining area according to the image data and the boundary range;
and predicting the mining earthwork of the designated open-pit mining area according to the working vehicle and the DEM data.
Corresponding to the above embodiments, one or more embodiments of the present specification provide a non-volatile computer storage medium storing computer executable instructions configured to:
acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range;
inputting the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
determining a working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range;
determining Digital Elevation Model (DEM) data related to the terrain of the designated open-pit mining area according to the image data and the boundary range;
and predicting the mining earthwork of the designated open-pit mining area according to the working vehicle and the DEM data.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing is merely one or more embodiments of the present description and is not intended to limit the present description. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, or the like, which is within the spirit and principles of one or more embodiments of the present description, is intended to be included within the scope of the claims of the present description.
Claims (7)
1. A method of predicting the amount of mined earthwork in an open-pit mining area, the method comprising:
acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range;
inputting the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
determining a working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range;
determining Digital Elevation Model (DEM) data related to the terrain of the designated open pit mining area according to the image data and the boundary range, wherein the DEM data comprises first DEM data corresponding to initial time and second DEM data corresponding to final time in the preset time range;
the determining digital elevation model DEM data related to the terrain of the designated open pit mining area according to the image data and the boundary range comprises the following steps:
determining sample image data of a preset time range of a designated open pit area in the image data according to the boundary range;
obtaining the first DEM data and the second DEM data related to the terrain according to the sample image data;
predicting the amount of mined earthwork of the designated open-pit mining area according to the working vehicle and the DEM data;
the predicting the amount of mined earthwork of the designated open-pit mining area according to the working vehicle and the DEM data comprises:
obtaining a terrain difference result of the designated open-pit mining area according to the first DEM data and the second DEM data;
predicting a first mined earthwork volume of the designated open-pit mining area according to the terrain difference result;
predicting a second mined-out earth volume of the designated open-pit mining area based on the work vehicle;
predicting the mined earthwork of the designated open-pit mining area according to the first mined earthwork and the second mined earthwork;
the predicting the mined earthwork of the designated open-pit mining area according to the first mined earthwork and the second mined earthwork comprises:
determining a difference between the first mined earthwork and the second mined earthwork;
and if the difference value is lower than a preset threshold value, setting the first extracted earthwork quantity as the extracted earthwork quantity of the appointed open-pit mining area.
2. The method of claim 1, wherein predicting a first amount of mined earth for the designated open-pit mining area based on the terrain differential result comprises:
determining the area of the excavation area according to the terrain difference result;
and predicting the first mining earth volume according to the difference result of the area of the excavated area and the topography.
3. The method of claim 2, wherein predicting the first amount of mined earth based on the difference in the excavated area and the topography comprises:
predicting the first mined earthwork according to a preset formula, wherein:
the preset formula is as follows: terrain differential result x excavated area = amount of mined earth.
4. The method of claim 1, wherein predicting a second amount of mined earth for the designated open-pit mining area based on the work vehicle comprises:
determining the operation time and type of the operation vehicle in a preset time range;
and predicting the second mining earthwork of the designated open-pit mining area according to the working time and the type of the working vehicle.
5. A mining earth volume prediction apparatus for an open-pit mining area, the apparatus comprising:
the image data acquisition unit acquires image data of a specified open-air mining area through an optical remote sensing satellite in a preset time range;
the boundary range determining unit inputs the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
determining sample library data, and acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
a work vehicle determining unit that determines a work vehicle of the designated open pit mining area based on the image data, the sample library data, and the boundary range;
the DEM data determining unit is used for determining Digital Elevation Model (DEM) data related to the terrain of the designated open-pit mining area according to the image data and the boundary range, wherein the DEM data comprises first DEM data corresponding to initial time and second DEM data corresponding to final time in the preset time range; the determining digital elevation model DEM data related to the terrain of the designated open pit mining area according to the image data and the boundary range comprises the following steps: determining sample image data of a preset time range of a designated open pit area in the image data according to the boundary range; obtaining the first DEM data and the second DEM data related to the terrain according to the sample image data;
a mining earth volume prediction unit for predicting the mining earth volume of the designated open-pit mining area according to the working vehicle and the DEM data; the predicting the amount of mined earthwork of the designated open-pit mining area according to the working vehicle and the DEM data comprises: obtaining a terrain difference result of the designated open-pit mining area according to the first DEM data and the second DEM data; predicting a first mined earthwork volume of the designated open-pit mining area according to the terrain difference result; predicting a second mined-out earth volume of the designated open-pit mining area based on the work vehicle; predicting the mined earthwork of the designated open-pit mining area according to the first mined earthwork and the second mined earthwork; the predicting the mined earthwork of the designated open-pit mining area according to the first mined earthwork and the second mined earthwork comprises: determining a difference between the first mined earthwork and the second mined earthwork; and if the difference value is lower than a preset threshold value, setting the first extracted earthwork quantity as the extracted earthwork quantity of the appointed open-pit mining area.
6. A mining earthwork prediction apparatus for an open-pit mining area, comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range;
inputting the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
determining a working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range;
determining Digital Elevation Model (DEM) data related to the terrain of the designated open pit mining area according to the image data and the boundary range, wherein the DEM data comprises first DEM data corresponding to initial time and second DEM data corresponding to final time in the preset time range;
the determining digital elevation model DEM data related to the terrain of the designated open pit mining area according to the image data and the boundary range comprises the following steps:
determining sample image data of a preset time range of a designated open pit area in the image data according to the boundary range;
obtaining the first DEM data and the second DEM data related to the terrain according to the sample image data;
predicting the amount of mined earthwork of the designated open-pit mining area according to the working vehicle and the DEM data;
the predicting the amount of mined earthwork of the designated open-pit mining area according to the working vehicle and the DEM data comprises:
obtaining a terrain difference result of the designated open-pit mining area according to the first DEM data and the second DEM data;
predicting a first mined earthwork volume of the designated open-pit mining area according to the terrain difference result;
predicting a second mined-out earth volume of the designated open-pit mining area based on the work vehicle;
predicting the mined earthwork of the designated open-pit mining area according to the first mined earthwork and the second mined earthwork;
the predicting the mined earthwork of the designated open-pit mining area according to the first mined earthwork and the second mined earthwork comprises:
determining a difference between the first mined earthwork and the second mined earthwork;
and if the difference value is lower than a preset threshold value, setting the first extracted earthwork quantity as the extracted earthwork quantity of the appointed open-pit mining area.
7. A non-transitory computer storage medium storing computer-executable instructions configured to:
acquiring image data of a specified open-pit mining area through an optical remote sensing satellite within a preset time range;
inputting the image data into a pre-trained open-air mining area boundary extraction model to obtain a boundary range corresponding to the appointed open-air mining area;
acquiring sample library data of a predetermined working vehicle and a predetermined non-working vehicle;
determining a working vehicle of the designated open-pit mining area according to the image data, the sample library data and the boundary range;
determining Digital Elevation Model (DEM) data related to the terrain of the designated open pit mining area according to the image data and the boundary range, wherein the DEM data comprises first DEM data corresponding to initial time and second DEM data corresponding to final time in the preset time range;
the determining digital elevation model DEM data related to the terrain of the designated open pit mining area according to the image data and the boundary range comprises the following steps:
determining sample image data of a preset time range of a designated open pit area in the image data according to the boundary range;
obtaining the first DEM data and the second DEM data related to the terrain according to the sample image data;
predicting the amount of mined earthwork of the designated open-pit mining area according to the working vehicle and the DEM data;
the predicting the amount of mined earthwork of the designated open-pit mining area according to the working vehicle and the DEM data comprises:
obtaining a terrain difference result of the designated open-pit mining area according to the first DEM data and the second DEM data;
predicting a first mined earthwork volume of the designated open-pit mining area according to the terrain difference result;
predicting a second mined-out earth volume of the designated open-pit mining area based on the work vehicle;
predicting the mined earthwork of the designated open-pit mining area according to the first mined earthwork and the second mined earthwork;
the predicting the mined earthwork of the designated open-pit mining area according to the first mined earthwork and the second mined earthwork comprises:
determining a difference between the first mined earthwork and the second mined earthwork;
and if the difference value is lower than a preset threshold value, setting the first extracted earthwork quantity as the extracted earthwork quantity of the appointed open-pit mining area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310382278.9A CN116151482B (en) | 2023-04-12 | 2023-04-12 | Method, device, equipment and medium for predicting mining earthwork of open-pit mining area |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310382278.9A CN116151482B (en) | 2023-04-12 | 2023-04-12 | Method, device, equipment and medium for predicting mining earthwork of open-pit mining area |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116151482A CN116151482A (en) | 2023-05-23 |
| CN116151482B true CN116151482B (en) | 2023-08-01 |
Family
ID=86341002
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310382278.9A Active CN116151482B (en) | 2023-04-12 | 2023-04-12 | Method, device, equipment and medium for predicting mining earthwork of open-pit mining area |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116151482B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117392337B (en) * | 2023-10-11 | 2024-04-05 | 中色地科矿产勘查股份有限公司 | Digital mineral exploration method based on AI |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2186984C1 (en) * | 2001-01-25 | 2002-08-10 | Открытое акционерное общество "Уральский научно-исследовательский и проектный институт медной промышленности "Унипромедь" | Method of extraction of beyond-contour mineral reserves under opencast bottom and in its flanks |
| CN104533528B (en) * | 2015-01-23 | 2016-06-29 | 中国有色金属长沙勘察设计研究院有限公司 | Adopt the fine mining system of surface mine and the mining methods of GNSS technology |
| CN112683171B (en) * | 2020-12-31 | 2023-04-14 | 数字港湾科技(湖北)有限公司 | Method and device for measuring and calculating earthwork amount |
| CN114219771A (en) * | 2021-11-29 | 2022-03-22 | 中国矿业大学(北京) | Method and device for excavating earth volume in mine pit |
-
2023
- 2023-04-12 CN CN202310382278.9A patent/CN116151482B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN116151482A (en) | 2023-05-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111623722B (en) | Multi-sensor-based slope deformation three-dimensional monitoring system and method | |
| CN110726677B (en) | Polluted site remote sensing detection and space hot area identification system and method | |
| CN102434210B (en) | Method and system for monitoring underground engineering portrait information and monitoring information safely | |
| CN116151482B (en) | Method, device, equipment and medium for predicting mining earthwork of open-pit mining area | |
| CN102184423B (en) | Full-automatic method for precisely extracting regional impervious surface remote sensing information | |
| CN115730684A (en) | Air quality detection system based on LSTM-CNN model | |
| CN111754084B (en) | Method and system for assessing land reclamation potential of rural construction land | |
| CN105467100B (en) | County's region soil based on remote sensing and GIS corrodes space-time dynamic monitoring method | |
| CN102253423A (en) | Proper water supply position intelligent recognition technology based on multi-source hydrogeology survey information | |
| CN113720639A (en) | Method for investigation, supplement and sampling of polluted site | |
| Labant et al. | Geodetic determining of stockpile volume of mineral excavated in open pit mine | |
| Blachowski et al. | Deformation information system for facilitating studies of mining-ground deformations, development, and applications | |
| Palamara et al. | An evaluation of airborne laser scan data for coalmine subsidence mapping | |
| CN116045903A (en) | Coal mining area ground deformation identification and evaluation method | |
| AU2018446326B2 (en) | Real-time correlation of sensed position data with terrestrial features | |
| CN115526544A (en) | Green mine construction planning method and system based on multi-type data | |
| CN110717618A (en) | Submarine hydrothermal sulfide resource evaluation and prediction method based on multi-index comprehensive elements | |
| Chand et al. | Internal Mine Dump Slope Stability and Failure Zone Identification using 3D Modelling | |
| Chandrasekar et al. | Computer application on evaluating beach sediment erosion and accretion from profile survey data | |
| Champagne et al. | Waste Settlement Measurements Using Unmanned Aerial Vehicles at a Municipal Solid Waste Landfill in Michigan | |
| CN114241299A (en) | Method and system for detecting garbage density of block chain water area based on genetic algorithm | |
| Fischer et al. | Monitoring of environmental changes caused by hard-coal mining | |
| McGaughey | 4D data management and modelling in the assessment of deep underground mining hazard | |
| Bartsch et al. | Soil information system as part of a municipal environmental information system | |
| Zhang et al. | Analysis on Dynamic Changes of Roliai Laterite Nickel Mine from 2013 to 2020 |
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 |