Ore removal metering method and device of carry-scraper, electronic equipment and storage medium

Abstract

The invention provides an ore removal metering method and device of a carry-scraper, electronic equipment and a storage medium, and belongs to the field of mine production management.The method comprises the steps that three-dimensional scanning data of an ore heap is obtained; generating three-dimensional point cloud data according to the three-dimensional scanning data, performing de-noising preprocessing on the three-dimensional point cloud data to obtain de-noised point cloud data, performing point cloud volume calculation on the de-noised point cloud data to obtain ore heap volume data, and determining ore heap volume variation according to the ore heap volume data, and the ore removal amount of the carry-scraper is determined according to the ore heap volume variation and preset ore density data. According to the method, the ore removal amount of the carry-scraper is calculated in a manner of calculating the volume variation of the ore heap through three-dimensional scanning and point cloud volume, so that the influence of environmental factors and driver operation on ore removal metering can be effectively avoided, the metering accuracy is improved, and effective metering data is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of mine production management, and in particular to a method, device, electronic equipment and storage medium for measuring the output of a scraper. Background Art

[0002] Underground mining shovel loaders are one of the important equipment for underground mining operations. Realizing the automatic measurement of the ore output of mining shovel loaders is one of the core of intelligent shovel loaders. The automatic measurement of mining shovel loaders can provide important data support for mining management and play a key role in improving the efficiency and safety of the entire mining process.

[0003] The traditional method of underground mining loader outflow measurement is to install a weighing sensor on the bucket or frame of the loader and calculate the load by measuring the bucket load. However, due to the harsh working environment of underground mining loader, environmental factors such as high vibration and high temperature can easily cause sensor failure or unstable data. At the same time, factors such as the driver's proficiency and bucket posture will also affect the accuracy of measurement and the reliability of the system, making it impossible to obtain effective measurement data.

[0004] Therefore, the existing technology has the technical problem that the shovel loader's ore output measurement is easily affected by factors such as the environment and the driver's operation, resulting in inaccurate measurement and failure to obtain effective measurement data, which needs to be improved. Summary of the invention

[0005] In view of this, it is necessary to provide a method, device, electronic device and storage medium for measuring the output of a shovel loader, so as to solve the technical problem that the output of a shovel loader is easily affected by factors such as the environment and the driver's operation, resulting in inaccurate measurement and inability to obtain effective measurement data.

[0006] In order to solve the above technical problems, on the one hand, the present invention provides a method for measuring the output of a shovel loader, which is used to scan the ore pile during the shoveling operation of the shovel loader to determine the output of the ore of the shovel loader, comprising: Obtain 3D scanning data of the ore pile; Three-dimensional point cloud data is generated based on the three-dimensional scanning data, and denoising preprocessing is performed on the three-dimensional point cloud data to obtain denoised point cloud data. Point cloud volume calculation is performed on the denoised point cloud data to obtain ore pile volume data, and the ore pile volume change is determined based on the ore pile volume data. The ore output of the shovel loader is determined based on the ore pile volume change and preset ore density data.

[0007] In a possible implementation, obtaining three-dimensional scanning data of a ore pile includes: The ore pile is 3D scanned before and after the loader leaves the mine to obtain 3D scanning data.

[0008] In a possible implementation, generating three-dimensional point cloud data according to three-dimensional scanning data includes: The coordinate data of each scanning reflection point is determined according to the three-dimensional scanning data, and the three-dimensional point cloud data is generated according to the coordinate data of each scanning reflection point.

[0009] In a possible implementation, performing denoising preprocessing on the three-dimensional point cloud data to obtain denoised point cloud data includes: The three-dimensional point cloud data is subjected to noise point filtering and data filtering in turn to obtain denoised point cloud data.

[0010] In a possible implementation, performing point cloud volume calculation on the de-noised point cloud data to obtain the ore pile volume data includes: The denoised point cloud data is subjected to coordinate transformation, geometric feature extraction and target object segmentation in sequence to obtain point cloud geometric data; The volume data of the ore pile is obtained by calculating the volume of the point cloud geometric data based on the convex hull algorithm.

[0011] In a possible implementation, the ore pile volume data includes the ore pile volume data before and after the ore is discharged, determining the ore pile volume change amount according to the ore pile volume data, and determining the ore discharge amount of the shovel loader according to the ore pile volume change amount and preset ore density data, including: Determine the volume change of the ore pile according to the volume data of the ore pile before and after the ore pile is unearthed; The ore output of the loader is determined based on the volume change of the ore pile and the preset ore density data.

[0012] In a possible implementation, the method further includes: Generate ore output analysis statistics based on the ore output of the loader, and build a shovel operation strategy based on the ore output analysis statistics; Among them, mining analysis statistics include total statistics, average mining statistics, fluctuation analysis, comparative analysis and correlation analysis.

[0013] On the other hand, the present invention also provides a scraper ore-discharging metering device, comprising: A 3D scanning unit for the ore pile, used to obtain 3D scanning data of the ore pile; The ore output calculation unit is used to generate three-dimensional point cloud data based on the three-dimensional scanning data, perform denoising preprocessing on the three-dimensional point cloud data to obtain denoised point cloud data, perform point cloud volume calculation on the denoised point cloud data to obtain ore pile volume data, determine the ore pile volume change based on the ore pile volume data, and determine the ore output of the shovel loader based on the ore pile volume change and preset ore density data.

[0014] On the other hand, the present invention also provides an electronic device, including a memory and a processor, wherein: Memory for storing computer programs; The processor is coupled to the memory and is used to execute the computer program to implement the steps in the above-mentioned method for measuring the output of the loader.

[0015] On the other hand, the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the above-mentioned method for measuring the output of a shovel loader are implemented.

[0016] The beneficial effects of the present invention are as follows: the method for measuring the output of a shovel loader provided by the present invention first obtains three-dimensional scanning data of the ore pile; then generates three-dimensional point cloud data based on the three-dimensional scanning data, performs denoising preprocessing on the three-dimensional point cloud data to obtain denoised point cloud data, performs point cloud volume calculation on the denoised point cloud data to obtain ore pile volume data, determines the volume change of the ore pile based on the ore pile volume data, and determines the output of the shovel loader based on the volume change of the ore pile and preset ore density data. The present invention calculates the output of the shovel loader by calculating the volume change of the ore pile through three-dimensional scanning and point cloud volume calculation, which can effectively avoid the influence of environmental factors and driver operation on the output measurement, improve the accuracy of measurement, and obtain effective measurement data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for measuring ore output from a scraper provided by the present invention; Figure 2 A schematic diagram of a process of calculating point cloud volume according to an embodiment of the present invention; Figure 3 A schematic diagram of a process for calculating the ore output of a scraper according to an embodiment of the present invention; Figure 4 A schematic structural diagram of an embodiment of a shovel loader ore discharge metering device provided by the present invention; Figure 5 A schematic structural diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0020] In the description of the embodiments of the present invention, unless otherwise specified, "multiple" means two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" may mean: A exists alone, A and B exist at the same time, and B exists alone.

[0021] The descriptions of "first", "second", etc. involved in the embodiments of the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the technical features defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0022] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0023] The present invention provides a method, device, electronic equipment and storage medium for measuring ore output of a scraper, which are described below respectively.

[0024] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for measuring the ore output of a shovel loader provided by the present invention is shown in FIG. Figure 1 As shown in the figure, the ore-discharging metering method for scraper loader includes: S101, obtaining three-dimensional scanning data of the ore pile; S102, generating three-dimensional point cloud data according to the three-dimensional scanning data, performing denoising preprocessing on the three-dimensional point cloud data to obtain denoised point cloud data, performing point cloud volume calculation on the denoised point cloud data to obtain ore pile volume data, determining a volume change of the ore pile according to the ore pile volume data, and determining the ore output of the shovel loader according to the volume change of the ore pile and preset ore density data.

[0025] Specifically, the method for measuring the output of a shovel loader provided by the present invention first obtains three-dimensional scanning data of the ore pile; then generates three-dimensional point cloud data based on the three-dimensional scanning data, performs denoising preprocessing on the three-dimensional point cloud data to obtain denoised point cloud data, performs point cloud volume calculation on the denoised point cloud data to obtain ore pile volume data, determines the volume change of the ore pile based on the ore pile volume data, and determines the output of the shovel loader based on the volume change of the ore pile and preset ore density data. The present invention calculates the output of the shovel loader by calculating the volume change of the ore pile through three-dimensional scanning and point cloud volume calculation, which can effectively avoid the influence of environmental factors and driver operation on the output measurement, improve the accuracy of measurement, and obtain effective measurement data.

[0026] In some embodiments of the present invention, obtaining three-dimensional scanning data of a ore pile includes: The ore pile is 3D scanned before and after the loader leaves the mine to obtain 3D scanning data.

[0027] Specifically, in order to avoid the influence of the environment and the driver's operation on the measurement accuracy, the embodiment determines the volume change of the ore pile before and after the shovel loader leaves the mine by scanning, so as to determine the ore output of the shovel loader.

[0028] In the process of scanning the ore pile, the embodiment first emits laser pulses to the ore pile through the laser in the laser radar device. These laser pulses have specific wavelengths and energy. When the laser pulses are irradiated to the target object, part of the light will be reflected. The receiver in the laser radar device receives the reflected light and converts the optical signal into an electrical signal to obtain three-dimensional scanning data.

[0029] In some embodiments of the present invention, generating three-dimensional point cloud data according to three-dimensional scanning data includes: The coordinate data of each scanning reflection point is determined according to the three-dimensional scanning data, and the three-dimensional point cloud data is generated according to the coordinate data of each scanning reflection point.

[0030] Specifically, after receiving the 3D scanning data, the embodiment determines the distance between the target object and the laser radar according to the time difference between the laser pulse emission and the received reflected light in the 3D scanning data, and the distance can be calculated according to the time difference and the speed of light. At the same time, the laser radar can measure target objects at different angles by changing the emission direction of the laser, and measure and record the angle of laser emission and the angle of received reflected light.

[0031] The embodiment then processes the measured distance and angle information, and combines the position and attitude information of the laser radar to determine the three-dimensional coordinates of each reflection point on the target object. Then, as the laser radar continuously emits pulses and receives reflected light, more and more points on the target object are measured, and three-dimensional point cloud data is generated based on the three-dimensional coordinates of each reflection point.

[0032] In some embodiments of the present invention, performing denoising preprocessing on three-dimensional point cloud data to obtain denoised point cloud data includes: The three-dimensional point cloud data is subjected to noise point filtering and data filtering in turn to obtain denoised point cloud data.

[0033] Specifically, in the denoising preprocessing, due to various interference factors in the environment, such as dust, water vapor, and electromagnetic interference, there will be some noise points in the collected point cloud data, and the noise points need to be filtered out first. In the noise point filtering, the embodiment calculates the average distance between each point in the point cloud and several adjacent points. If the average distance exceeds a preset distance threshold, the point is considered to be an isolated noise point and is removed.

[0034] In addition, in order to make the point cloud data smoother and more accurate, data filtering is also required. Data filtering can remove high-frequency noise and retain useful low-frequency information. In the embodiment, various methods such as Gaussian filtering and median filtering can be used for data filtering. Gaussian filtering makes the point cloud data smoother by weighted averaging each point and the points around it. Median filtering replaces the value of each point with the median of the points within a certain range around it, which can effectively remove noise.

[0035] In some embodiments of the present invention, Figure 2 FIG. 1 is a flow chart of point cloud volume calculation according to an embodiment of the present invention. Figure 2 As shown in the figure, the denoised point cloud data is subjected to point cloud volume calculation to obtain the ore pile volume data, including: S201, performing coordinate transformation, geometric feature extraction and target object segmentation on the denoised point cloud data in sequence to obtain point cloud geometric data; S202, performing volume calculation on the point cloud geometric data based on a convex hull algorithm to obtain ore pile volume data.

[0036] Specifically, in the process of completing denoising and calculating the point cloud volume, since the denoised point cloud data at this time is data in the laser radar's own coordinate system, in order to integrate these point cloud data with other devices and maps, they need to be converted to a unified world coordinate system. The embodiment obtains the position and posture of the laser radar at this time through the sensor, and converts the denoised point cloud data from the laser radar coordinate system to the world coordinate system according to the coordinate conversion formula.

[0037] It should be noted that the above is only a data collection method of one embodiment of the present invention. In other embodiments, according to actual application requirements, other sensors may be used, such as cameras or GPS, or laser radars set on other devices. The data collected by other sensors also need to be converted to the world coordinate system so that data from different sources can be analyzed in the same coordinate system.

[0038] Then the embodiment needs to extract geometric features from the point cloud data, including plane extraction and edge extraction. Plane extraction takes into account that in an underground mine environment, there may be many plane structures, such as the walls and ground of the tunnel, so these planes can be identified through plane extraction. In the embodiment, the plane extraction algorithm adopts RANSAC (RANdom SAmpleConsensus, random sampling consistency algorithm), which assumes a plane by randomly selecting some points, and then calculates the distance from other points to this plane, and continuously iterates and optimizes until the best plane model is found. Edge extraction is to extract and identify the boundaries of objects, which is very important for identifying the shape and position of objects. The embodiment extracts edge points from point cloud data through an edge detection algorithm. The edge detection algorithm calculates the normal vector of each point, and then determines whether it is an edge point based on the change of the normal vector. Points with large changes in the normal vector are usually located at the edge of the object.

[0039] Then, according to the result of feature extraction, the embodiment uses a clustering algorithm to classify points with close distances into the same category, so that target objects with different point cloud data can be separated. For example, ore piles and pillars in the tunnel can be separated from the surrounding walls and ground.

[0040] For the segmented target objects, the geometric size and volume are automatically calculated according to the built-in algorithm. For relatively shaped objects, such as a pile of ore stacked into a cuboid, the volume calculation formula is used for calculation. For irregularly shaped objects, the embodiment uses a convex hull algorithm to calculate the point cloud data. In the convex hull algorithm, the convex hull refers to the smallest convex polygon containing all points. The approximate size of the target object can be obtained by calculating the size of the convex hull. The Graham scanning method is used to calculate the convex hull in the embodiment.

[0041] In some embodiments of the present invention, the ore pile volume data includes the ore pile volume data before mining and the ore pile volume data after mining. Figure 3 FIG. 1 is a flow chart of calculating the ore output of a shovel loader according to an embodiment of the present invention. Figure 3 As shown, the volume change of the ore pile is determined according to the ore pile volume data, and the ore output of the loader is determined according to the ore pile volume change and the preset ore density data, including: S301, determining a volume change of the ore pile according to the volume data of the ore pile before and after the ore pile is unearthed; S302, determining the ore output of the shovel loader according to the volume change of the ore pile and the preset ore density data.

[0042] Specifically, the embodiment obtains the volume of the ore pile before and after shoveling out of the mine through three-dimensional scanning and point cloud volume calculation, and can subtract the volume change of the ore pile before and after the operation, and then the volume change is combined with the preset ore density data obtained by pre-sampling and testing the ore pile to determine the weight of the ore discharged by the shovel loader. , the formula is:

[0043] in, To preset the ore density, is the volume of the ore pile after mining, It is the volume of the ore pile before mining.

[0044] In some embodiments of the present invention, the method for measuring the ore output of a scraper further includes: Generate ore output analysis statistics based on the ore output of the loader, and build a shovel operation strategy based on the ore output analysis statistics; Among them, mining analysis statistics include total statistics, average mining statistics, fluctuation analysis, comparative analysis and correlation analysis.

[0045] Specifically, in order to improve the efficiency of shoveling operations, the shovel loader ore output measurement method in the embodiment also analyzes and counts the shovel loader ore output, including total output statistics, average output statistics, fluctuation analysis, comparative analysis and correlation analysis, and constructs a shoveling operation strategy based on the results of the statistical analysis.

[0046] The total amount statistics is to calculate the total ore output in a certain period of time, which is obtained by accumulating the ore output per bucket of all records. This total amount data can help managers quickly understand the overall production scale in the period. For example, the total ore output of all shovels at various ore output locations in a month can be counted to evaluate whether the production progress of that month meets expectations.

[0047] The average output is calculated by calculating the average output per bucket of different shovels, different ore-discharging locations, and the entire mine. The average output can reflect the production efficiency level of different equipment and regions. For a specific shovel, the sum of the output of all its ore-discharging records is divided by the number of ore-discharging times to get the average output per bucket of the shovel. The same method can be used to calculate the average output of different ore-discharging locations. By comparing these average values, it is possible to find out which shovels and ore-discharging locations are more or less efficient, providing data support for shovel operation planning.

[0048] Fluctuation analysis is the analysis of the fluctuation of ore output over time. You can draw a line graph of ore output over time to observe whether there are obvious seasonal changes, cyclical changes or random fluctuations in ore output. For example, if you find that ore output has dropped significantly in a certain season, you may need to further investigate the reasons, such as whether weather conditions, equipment maintenance and other factors have affected production.

[0049] Comparative analysis is divided into comparison between shovels and comparison between mining locations. Comparison between shovels compares the output, working time, efficiency and other indicators of different shovels. A bar chart or table can be made to intuitively show the performance differences of each shovel. For example, compare the average output per bucket and working time of different types of shovels to evaluate which type of shovel performs better in production. At the same time, the failure rate and maintenance cost of different shovels can be analyzed to comprehensively consider and select the optimal shovel combination. Comparison between mining locations analyzes factors such as the output, ore quality, and mining difficulty of different mining locations. By comparing the output and quality of each location, resource-rich areas can be determined and the mining layout can be optimized. For example, for locations with large output and good ore quality, mining efforts can be increased; for locations with small output or high mining difficulty, you can consider reducing investment or looking for alternatives.

[0050] The correlation analysis is divided into the correlation analysis between the output and time and the correlation analysis between the output and the shovel number and the location of the output. The correlation analysis between the output and time can find out whether there is a difference in the output in a specific time period. For example, if the output is lower on weekends, the personnel arrangement or equipment maintenance plan can be adjusted to ensure efficient generation on weekdays. The correlation analysis between the output and the shovel number and the location of the output can analyze which shovels perform better at which locations, so as to facilitate more reasonable task allocation.

[0051] The final embodiment combines various analysis results to obtain mining analysis statistics, generates data tables, charts or graphs, and uses them to adjust and generate more reasonable shoveling operation strategies.

[0052] In summary, the method for measuring the output of a shovel loader provided by the present invention first obtains the three-dimensional scanning data of the ore pile; then generates three-dimensional point cloud data based on the three-dimensional scanning data, performs denoising preprocessing on the three-dimensional point cloud data to obtain denoised point cloud data, performs point cloud volume calculation on the denoised point cloud data to obtain ore pile volume data, determines the volume change of the ore pile based on the ore pile volume data, and determines the output of the shovel loader based on the volume change of the ore pile and preset ore density data. The present invention calculates the output of the shovel loader by calculating the volume change of the ore pile through three-dimensional scanning and point cloud volume, which can effectively avoid the influence of environmental factors and driver operation on the output measurement, improve the accuracy of measurement, and obtain effective measurement data.

[0053] In order to better implement the method for measuring the ore output of a shovel loader in the embodiment of the present invention, based on the method for measuring the ore output of a shovel loader, correspondingly, Figure 4 As shown, the present invention also provides a scraper ore-discharging metering device, and the scraper ore-discharging metering device 400 comprises: The ore pile three-dimensional scanning unit 401 is used to obtain three-dimensional scanning data of the ore pile; The ore output calculation unit 402 is used to generate three-dimensional point cloud data based on the three-dimensional scanning data, perform denoising preprocessing on the three-dimensional point cloud data to obtain denoised point cloud data, perform point cloud volume calculation on the denoised point cloud data to obtain ore pile volume data, determine the ore pile volume change based on the ore pile volume data, and determine the ore output of the shovel loader based on the ore pile volume change and preset ore density data.

[0054] The shovel loader ore-discharging metering device 400 provided in the above embodiment can implement the technical solution described in the above embodiment of the shovel loader ore-discharging metering method. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above embodiment of the shovel loader ore-discharging metering method, which will not be repeated here.

[0055] like Figure 5 As shown, the present invention also provides an electronic device 500. The electronic device 500 includes a processor 501, a memory 502 and a display 503. Figure 5 Only some components of the electronic device 500 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0056] In some embodiments, the processor 501 may be a central processing unit (CPU), a microprocessor or other data processing chip, which is used to run the program code or process data stored in the memory 502, such as the shovel loader mining metering method of the present invention.

[0057] In some embodiments, the processor 501 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, the processor 501 may be local or remote. In some embodiments, the processor 501 may be implemented in a cloud platform. In one embodiment, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-cloud, etc., or any combination thereof.

[0058] In some embodiments, the memory 502 may be an internal storage unit of the electronic device 500, such as a hard disk or memory of the electronic device 500. In other embodiments, the memory 502 may also be an external storage device of the electronic device 500, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 500.

[0059] Furthermore, the memory 502 may include both an internal storage unit of the electronic device 500 and an external storage device. The memory 502 is used to store application software installed in the electronic device 500 and various data.

[0060] In some embodiments, the display 503 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 503 is used to display information of the electronic device 500 and to display a visual user interface. The components 501-503 of the electronic device 500 communicate with each other through a system bus.

[0061] In one embodiment, when the processor 501 executes the loader mining metering program in the memory 502, the following steps may be implemented: Obtain 3D scanning data of the ore pile; Three-dimensional point cloud data is generated based on the three-dimensional scanning data, and denoising preprocessing is performed on the three-dimensional point cloud data to obtain denoised point cloud data. Point cloud volume calculation is performed on the denoised point cloud data to obtain ore pile volume data, and the ore pile volume change is determined based on the ore pile volume data. The ore output of the shovel loader is determined based on the ore pile volume change and preset ore density data.

[0062] It should be understood that: when the processor 501 executes the shovel loader ore metering program in the memory 502, in addition to the above functions, other functions can also be implemented. For details, please refer to the description of the corresponding method embodiment above.

[0063] Furthermore, the embodiment of the present invention does not specifically limit the type of the electronic device 500 mentioned, and the electronic device 500 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, etc. Exemplary embodiments of portable electronic devices include but are not limited to portable electronic devices equipped with IOS, Android, Microsoft or other operating systems. The above-mentioned portable electronic devices may also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 500 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0064] Accordingly, an embodiment of the present application also provides a computer-readable storage medium, which is used to store computer-readable programs or instructions. When the program or instructions are executed by a processor, it can implement the steps or functions of the shovel loader mining metering method provided in the above-mentioned method embodiments.

[0065] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the computer program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0066] The above is a detailed introduction to the shovel loader ore metering method, device, electronic device and storage medium provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for measuring the output of a shovel loader, characterized in that: Used to scan the ore pile during the loader shoveling operation to determine the ore output of the loader, including: Acquiring three-dimensional scanning data of the ore pile; Generate three-dimensional point cloud data based on the three-dimensional scanning data, perform denoising preprocessing on the three-dimensional point cloud data to obtain denoised point cloud data, perform point cloud volume calculation on the denoised point cloud data to obtain ore pile volume data, determine the ore pile volume change based on the ore pile volume data, and determine the ore output of the shovel loader based on the ore pile volume change and preset ore density data.

2. The method for measuring the ore output of a shovel loader according to claim 1, characterized in that: The obtaining of three-dimensional scanning data of the ore pile comprises: The ore pile is three-dimensionally scanned before and after the shovel loader leaves the mine to obtain three-dimensional scanning data.

3. The method for measuring the ore output of a shovel loader according to claim 1, characterized in that: The generating three-dimensional point cloud data according to the three-dimensional scanning data comprises: The coordinate data of each scanning reflection point is determined according to the three-dimensional scanning data, and the three-dimensional point cloud data is generated according to the coordinate data of each scanning reflection point.

4. The method for measuring the ore output of a shovel loader according to claim 1, characterized in that: The denoising preprocessing of the three-dimensional point cloud data to obtain denoised point cloud data includes: Noise point filtering and data filtering are performed on the three-dimensional point cloud data in sequence to obtain denoised point cloud data.

5. The method for measuring the ore output of a shovel loader according to claim 1, characterized in that: The step of performing point cloud volume calculation on the de-noised point cloud data to obtain the ore pile volume data includes: The denoised point cloud data is sequentially subjected to coordinate transformation, geometric feature extraction and target object segmentation to obtain point cloud geometric data; The volume data of the ore pile is obtained by performing volume calculation on the point cloud geometric data based on a convex hull algorithm.

6. The method for measuring the ore output of a shovel loader according to claim 1, characterized in that: The ore pile volume data includes the ore pile volume data before and after the ore is discharged, and the determining of the ore pile volume change according to the ore pile volume data, and the determining of the ore discharge amount of the shovel loader according to the ore pile volume change and preset ore density data, includes: Determine the volume change of the ore pile according to the volume data of the ore pile before the ore is unearthed and the volume data of the ore pile after the ore is unearthed; The ore output of the shovel loader is determined according to the volume change of the ore pile and the preset ore density data.

7. The method for measuring the ore output of a loader according to claim 1, characterized in that: The method further comprises: Generate ore output analysis statistics according to the ore output of the loader, and construct a shovel operation strategy according to the ore output analysis statistics; The mining analysis statistics include total statistics, average mining statistics, fluctuation analysis, comparative analysis and correlation analysis.

8. A shovel loader ore metering device, characterized in that: include: A 3D scanning unit for an ore pile, used for acquiring 3D scanning data of the ore pile; The ore output calculation unit is used to generate three-dimensional point cloud data based on the three-dimensional scanning data, perform denoising preprocessing on the three-dimensional point cloud data to obtain denoised point cloud data, perform point cloud volume calculation on the denoised point cloud data to obtain ore pile volume data, determine the ore pile volume change according to the ore pile volume data, and determine the ore output of the shovel loader according to the ore pile volume change and preset ore density data.

9. An electronic device, characterized in that: comprising a memory and a processor, wherein: The memory is used to store computer programs; The processor, coupled to the memory, is used to execute a computer program to implement the steps in the method for measuring ore output of a shovel loader as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method for measuring ore output of a shovel loader as described in any one of claims 1 to 7 are implemented.

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