A method and system for measuring stone based on ai artificial intelligence

Abstract

The application relates to a method and system for measuring rock minerals based on AI artificial intelligence, and relates to the field of hyperspectral remote sensing applications, and solves the problem that the existing division of the distribution area of rock minerals is relatively subjective and is prone to large division deviation, and the method comprises the following steps: obtaining spectral data of rock minerals to be classified and an obtained position; according to a preset corresponding relationship between rock mineral types and spectral data, the spectral data of the rock minerals to be classified and the obtained position, the type of the rock minerals to be classified and the obtained position are analyzed and determined; according to the type of the rock minerals obtained by the history of the obtained position and the type of the rock minerals to be classified analyzed this time, whether the type of the rock minerals to be classified analyzed this time falls into the type of the rock minerals obtained by the history of the obtained position is analyzed and determined. The application has the following effects: through the artificial intelligence measurement mode, the efficiency and accuracy of measuring the distribution area of rock minerals are improved.

Description

Technical Field

[0001] This invention relates to the field of hyperspectral remote sensing applications, and in particular to a method and system for measuring stone ore based on AI artificial intelligence. Background Technology

[0002] Currently, due to their unique chemical composition and physical structure, rocks and minerals possess unique diagnostic characteristic absorption bands. These characteristic bands have relatively stable wavelength positions and unique waveforms, and their characteristics include spectral absorption peak positions, absorption peak depths, absorption peak widths, and other characteristic parameters. Through these characteristics or combinations thereof, mineral identification can be achieved.

[0003] The current delineation of distribution areas for rocks and minerals requires human measurement and is based on experience.

[0004] Regarding the aforementioned technologies, the inventors have discovered the following drawbacks: existing classifications of rock and mineral distribution areas are rather subjective and prone to significant deviations. Summary of the Invention

[0005] In order to improve the efficiency and accuracy of measuring the distribution area of ​​rocks and minerals through artificial intelligence measurement, this application provides a method and system for measuring rocks and minerals based on artificial intelligence.

[0006] Firstly, this application provides a method for measuring stone ore based on AI artificial intelligence, employing the following technical solution:

[0007] A method for measuring stone ore based on AI includes:

[0008] Obtain the spectral data of the rocks and minerals to be classified and their locations;

[0009] Based on the pre-defined correspondence between rock and mineral types and spectral data, the obtained spectral data of the rocks and minerals to be classified, and their locations, the types and locations of the rocks and minerals to be classified are analyzed and determined.

[0010] Based on the types of rocks and minerals obtained from the historical location data, and the types of rocks and minerals to be classified determined in this analysis, it is determined whether all types of rocks and minerals to be classified in this analysis fall within the types of rocks and minerals obtained from the historical location data.

[0011] If yes, then analyze whether the number of the same type of rock minerals to be classified exceeds the preset number. If it exceeds the preset number, then plan the distribution area of ​​the same type of rock minerals to be classified based on the type of the same type of rock minerals and the obtained location, and send the distribution area of ​​the same type of rock minerals to the terminal held by the person in charge.

[0012] If not, then the rock mineral types that do not fall into the rock mineral types obtained in the history of the obtained location are marked, and the rock mineral types to be classified determined in this analysis are sent to the terminal held by the person in charge.

[0013] Optionally, the analysis and determination of the types of rocks and minerals to be classified and their locations include:

[0014] Based on the obtained spectral data of the rocks and minerals to be classified and the correspondence between the rock and mineral types and the spectral data, the types of rocks and minerals to be classified are queried.

[0015] If found, the type of rock or mineral to be classified is used as the type of rock or mineral to be classified, and the type and location of the rock or mineral to be classified are obtained.

[0016] If no results are found, the spectral data of the unclassified rock and mineral species will be sent as a notification to the terminal held by the person in charge.

[0017] Obtain the types of rocks and minerals to be classified corresponding to the spectral data fed back by the terminal held by the person in charge, and obtain the types of rocks and minerals to be classified and their locations.

[0018] Optionally, the type of rock and mineral to be classified corresponding to the spectral data fed back by the terminal held by the person in charge is obtained, and the type of rock and mineral to be classified and the location of the obtained data are also obtained, including:

[0019] Analyze whether the type of rock and mineral to be classified is received from the spectral data fed back by the terminal held by the person in charge within the preset time.

[0020] If yes, then continue with the following steps;

[0021] If not, then a communication group will be created based on the contact information of the pre-set rock and mineral type identification experts, and the spectral data of the rock and mineral types that cannot be identified will be sent to the group.

[0022] Obtain the types of rocks and minerals to be classified corresponding to the spectral data fed back by the preset rock and mineral type identification experts, and use them as the types of rocks and minerals to be classified in this case.

[0023] Optionally, sending the distribution area of ​​the same type of rock mineral to be classified to the terminal held by the person in charge includes:

[0024] Obtain the types of rocks and minerals in the target category set by the person in charge;

[0025] Analyze the distribution areas of multiple types of rocks and minerals to be classified;

[0026] If so, before sending the distribution area of ​​the same type of rock mineral to be classified to the terminal held by the person in charge, the information of the distribution area of ​​the target type of rock mineral set by the person in charge will be sorted before the distribution area of ​​the other types of rock mineral to be classified.

[0027] If not, the distribution area of ​​the same type of rock mineral to be classified will be sent to the terminal held by the person in charge.

[0028] Optionally, it also includes a step that occurs after obtaining the types of rocks and minerals for the target classification set by the person in charge and before analyzing whether there are distribution areas of multiple types of rocks and minerals to be classified, as follows:

[0029] Based on the correspondence between the types of rock and minerals classified according to the target set by the person in charge and the accuracy of their distribution area, analyze the accuracy of the distribution area.

[0030] Based on the correspondence between the accuracy of the distribution location area, the range of the distribution location area, and the preset number of the same type of rock minerals to be classified, the preset number of the same type of rock minerals to be classified is determined.

[0031] If the number of rock minerals of the same type to be classified is less than the preset number of rock minerals of the same type to be classified, then the subsequent steps are stopped, and the missing number of rock minerals of the same type to be classified is calculated and sent to the terminal held by the person in charge.

[0032] If the number of rock minerals of the same type to be classified is greater than or equal to the preset number of rock minerals of the same type to be classified, then continue with the subsequent steps.

[0033] Optionally, the types of rocks and minerals to be acquired for the target classification set by the person in charge include:

[0034] Check if the person in charge has set a target classification for rock and mineral types;

[0035] If so, the type of rock and mineral in the target classification set by the person in charge shall be used as the type of rock and mineral in the target classification set by the person in charge.

[0036] If not, then based on the target category of rocks and minerals set by the person in charge in the past, find the type of target category of rocks and minerals that has been set the most times, and use it as the type of target category of rocks and minerals set by the person in charge.

[0037] Optionally, this also includes a step following the analysis of the distribution areas of multiple types of rock minerals to be classified, as follows:

[0038] Analyze whether there is any overlap in the distribution areas of multiple rock and mineral species to be classified;

[0039] If so, the terrains where overlap occurs are obtained, and the probability of existing in the same terrain is analyzed and determined based on the pre-defined correspondence between the types of different rock minerals and the probability of existing in the same terrain.

[0040] If the probability of existing in the same terrain exceeds the first preset probability, then continue with the subsequent steps;

[0041] If the probability of existing in the same terrain is less than or equal to the first preset probability and exceeds the second preset probability, then retain the distribution area of ​​different rocks and minerals and make a deletion prompt mark, and send it to the terminal held by the person in charge;

[0042] Obtain the distribution area of ​​different rocks and minerals as reported by the terminal held by the person in charge;

[0043] If the probability of existing in the same terrain is less than or equal to the second preset probability, then the distribution areas of the remaining rock minerals are removed from the rock minerals with larger distribution areas, and these are used as the distribution areas of the corresponding rock minerals to be classified.

[0044] Secondly, this application provides a system for measuring stone ore based on AI artificial intelligence, which adopts the following technical solution:

[0045] A method system for measuring stone ore based on AI artificial intelligence includes a memory, a processor, and a program stored in the memory and executable on the processor. When the program is loaded and executed by the processor, it implements the method for measuring stone ore based on AI artificial intelligence as described in the first aspect. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the overall process of a method for measuring stone ore based on AI, according to an embodiment of this application.

[0047] Figure 2 This is a schematic diagram illustrating the specific process of analyzing and determining the types of rocks and minerals to be classified and their locations, according to another embodiment of this application.

[0048] Figure 3 This is a schematic diagram of another embodiment of the present application, illustrating the process of obtaining the type of rock and mineral to be classified corresponding to the spectral data fed back by the terminal held by the person in charge, and obtaining the type and location of the rock and mineral to be classified.

[0049] Figure 4 This is a schematic diagram of another embodiment of the present application showing the distribution area of ​​the same type of rock mineral to be classified to the terminal held by the person in charge.

[0050] Figure 5 This is a flowchart illustrating another embodiment of the present application, which is a step after obtaining the types of target-classified rocks and minerals set by the person in charge and before analyzing whether there are distribution areas of multiple types of rocks and minerals to be classified.

[0051] Figure 6 This is a schematic diagram of the process for obtaining the types of target-classified rocks and minerals set by the person in charge of another embodiment of this application.

[0052] Figure 7 This is a flowchart illustrating another embodiment of the present application, representing a step following the analysis of the distribution location regions of multiple types of rock minerals to be classified. Implementation

[0053] The present application will be further described in detail below with reference to the accompanying drawings.

[0054] Reference Figure 1 This application discloses a method for measuring ore based on AI, comprising:

[0055] Step S100: Obtain the spectral data of the rock minerals to be classified and their locations.

[0056] The spectral data of the rocks and minerals to be classified can be obtained by scanning with a hyperspectral scanner. The specific steps include: cleaning the surface of the core sample to be classified, placing it in the sample placement position of the core hyperspectral scanner, turning on the core hyperspectral scanner to scan the core sample to be classified, and obtaining the spectral data of the sample to be classified in the range of 400nm to 1600nm. This operation is repeated until all the rock samples to be classified have been scanned. The obtained positions of the rocks and minerals to be classified can be entered one by one during the scanning process.

[0057] Step S200: Based on the preset correspondence between rock and mineral types and spectral data, the obtained spectral data of the rock and mineral to be classified and the obtained location, analyze and determine the type and location of the rock and mineral to be classified.

[0058] The analysis and determination of the types of rocks and minerals to be classified and their locations are as follows: using the spectral data of the rocks and minerals to be classified as the query object, the types of rocks and minerals are searched from a pre-set database that stores the correspondence between rock and mineral types and spectral data, and combined with the locations obtained, the types of rocks and minerals to be classified and their locations are effectively analyzed and determined.

[0059] Step S300: Based on the rock and mineral types obtained from the historical location data and the types of rock and minerals to be classified determined in this analysis, determine whether all types of rock and minerals to be classified in this analysis fall within the rock and mineral types obtained from the historical location data. If yes, proceed to step S400; if no, proceed to step S500.

[0060] The types of rocks and minerals obtained from the acquired location history can be retrieved from a pre-set database containing such types of rocks and minerals.

[0061] Step S400: Analyze whether the number of rock minerals of the same type exceeds the preset number. If it does, then plan the distribution area of ​​the same type of rock mineral based on the type of rock mineral and the obtained location, and send the distribution area of ​​the same type of rock mineral to the terminal held by the person in charge.

[0062] The minimum number of devices is 3, and more can be added as needed. The terminal held by the person in charge can be a mobile phone, computer, or other communicable terminal.

[0063] Step S500: Mark the rock mineral types that do not fall into the rock mineral types acquired in the history of the acquired location, and send the rock mineral types to be classified in this analysis to the terminal held by the person in charge.

[0064] exist Figure 1 In step S200, when the types of rocks and minerals to be classified cannot be obtained through a query, further analysis is required. See below for details. Figure 2 The illustrated embodiments are described in detail.

[0065] Reference Figure 2 The analysis and determination of the types of rocks and minerals to be classified and their locations include:

[0066] Step S210: Based on the obtained spectral data of the rocks and minerals to be classified and the correspondence between the rock and mineral types and the spectral data, query the types of rocks and minerals to be classified.

[0067] Step S220: If found, the type of rock mineral to be classified is used as the type of rock mineral to be classified, and the type and location of the rock mineral to be classified are obtained.

[0068] In step S230, if no results are found, the spectral data of the unidentified rock and mineral species to be classified will be sent as a notification to the terminal held by the person in charge.

[0069] Step S240: Obtain the type of rock and mineral to be classified corresponding to the spectral data fed back by the terminal held by the person in charge, and obtain the type of rock and mineral to be classified and its location.

[0070] exist Figure 2 In step S240, further consideration is given to how to effectively determine the type and location of the rock minerals to be classified when the person in charge fails to respond in a timely manner or cannot make an accurate determination. See below for details. Figure 3 The illustrated embodiments are described in detail.

[0071] Reference Figure 3 The system obtains the types of rocks and minerals to be classified corresponding to the spectral data fed back by the terminal held by the person in charge, and obtains the types of rocks and minerals to be classified and their locations, including:

[0072] Step S241: Analyze whether the type of rock and mineral to be classified is received from the spectral data fed back by the terminal held by the person in charge within a preset time. If yes, proceed to step S242; if no, proceed to step S243.

[0073] Step S242, continue with the following steps.

[0074] Step S243: Based on the pre-set contact information of rock and mineral type identification experts, a communication group is created, and the spectral data of rock and mineral types that cannot be identified are sent to the group.

[0075] The contact information of the preset rock and mineral type identification experts can be obtained by querying a preset database that stores the contact information of the preset rock and mineral type identification experts.

[0076] Step S244: Obtain the types of rock minerals to be classified corresponding to the spectral data fed back by the preset rock mineral type identification experts, and use them as the types of rock minerals to be classified this time.

[0077] exist Figure 1 In step S400, considering that the person in charge has their own target rock and mineral category in this batch of classified rocks and minerals, further analysis is required. See details below. Figure 4 The illustrated embodiments are described in detail.

[0078] Reference Figure 4 Sending the distribution area of ​​the same type of rock and mineral to be classified to the terminal held by the person in charge includes:

[0079] Step S410: Obtain the types of target-classified rocks and minerals set by the person in charge.

[0080] Step S420: Analyze whether there are distribution areas for multiple types of rocks and minerals to be classified. If yes, proceed to step S430; if no, proceed to step S440.

[0081] Step S430: Before sending the distribution location area of ​​the same type of rock mineral to be classified to the terminal held by the person in charge, sort the information of the distribution location area of ​​the target type of rock mineral set by the person in charge before the distribution location area of ​​the other types of rock mineral to be classified.

[0082] Step S440: Send the distribution area of ​​the same type of rock mineral to be classified to the terminal held by the person in charge.

[0083] exist Figure 4 Between steps S410 and S420, it is necessary to further consider that different responsible persons in different locations have different accuracy requirements, and the number of rock minerals to be classified also varies depending on the accuracy requirements. Therefore, further analysis is required. Please refer to [link / reference needed] for details. Figure 5 The illustrated embodiments are described in detail.

[0084] Reference Figure 5 A method for measuring rock minerals based on AI also includes steps following the acquisition of the types of rock minerals in the target classification set by the person in charge and before analyzing the distribution areas of multiple types of rock minerals to be classified, as follows:

[0085] Step S4a0: Analyze the accuracy of the distribution area based on the correspondence between the types of target-classified rocks and minerals and the accuracy of their distribution areas as set by the pre-defined person in charge.

[0086] The analysis of the accuracy of the distribution location area is as follows: taking the types of rock and minerals of the target classification set by the person in charge as the query object, the accuracy of the distribution location area is obtained by querying from the database that stores the correspondence between the types of rock and minerals of the target classification set by the person in charge and the accuracy of the distribution location area.

[0087] Step S4b0: Based on the correspondence between the accuracy of the distribution location area, the range of the distribution location area, and the preset number of rock minerals of the same type to be classified, analyze and determine the preset number of rock minerals of the same type to be classified.

[0088] The preset number of rock minerals of the same type to be classified is determined as follows: First, the range within which the area of ​​the distribution location falls is analyzed and determined. Then, using the range and the accuracy of the distribution location as common query objects, the preset number of rock minerals of the same type to be classified is obtained by querying a database that stores the correspondence between the accuracy of the distribution location, the range within which the area of ​​the distribution location falls, and the preset number of rock minerals of the same type to be classified.

[0089] In step S4c0, if the number of rock minerals of the same type to be classified is less than the preset number of rock minerals of the same type to be classified, then stop the subsequent steps, calculate the missing number of rock minerals of the same type to be classified, and send it to the terminal held by the person in charge.

[0090] In step S4d0, if the number of rock minerals of the same type to be classified is greater than or equal to the preset number of rock minerals of the same type to be classified, then continue with the subsequent steps.

[0091] exist Figure 4 In step S410, the possibility of the person in charge not setting a target classification for rocks and minerals is further considered. In this case, further analysis is required, as detailed below. Figure 6 The illustrated embodiments are described in detail.

[0092] Reference Figure 6 The types of rocks and minerals identified by the person in charge include:

[0093] Step S411: Check if the person in charge has set the target classification of rock and mineral types. If yes, proceed to step S412; if no, proceed to step S413.

[0094] Step S412: The types of rock and minerals in the target classification set by the person in charge are used as the types of rock and minerals in the target classification set by the person in charge.

[0095] Step S413: Based on the target classification of rocks and minerals set by the person in charge in the past, find the type of target classification of rocks and minerals that has been set the most times, and use it as the type of target classification of rocks and minerals set by the person in charge.

[0096] exist Figure 4 In step S420, the overlapping distribution areas are further considered. In this case, how to effectively determine the distribution area of ​​the rock minerals to be classified requires further analysis. See [link / reference] for details. Figure 7 The illustrated embodiments are described in detail.

[0097] Reference Figure 7A method for measuring rock minerals based on AI also includes a step following the analysis of the distribution areas of multiple types of rock minerals to be classified, as follows:

[0098] Step SA00: Analyze whether there is any overlap in the distribution areas of multiple rock mineral species to be classified.

[0099] Step SB00: Obtain the terrains where overlap occurs, and analyze and determine the probability of them existing in the same terrain based on the pre-defined correspondence between the types of different rock minerals and the probability of them existing in the same terrain.

[0100] Step SC00: If the probability of existing in the same terrain exceeds the first preset probability, then continue with the subsequent steps.

[0101] Step SD00: If the probability of existing in the same terrain is less than or equal to the first preset probability and exceeds the second preset probability, then retain the distribution area of ​​different rock minerals and make a deletion prompt mark, and send it to the terminal held by the person in charge.

[0102] Step SE00: Obtain the distribution area of ​​different rocks and minerals as reported by the terminal held by the person in charge.

[0103] Step SF00: If the probability of existing in the same terrain is less than or equal to the second preset probability, then delete the distribution areas of the remaining rock minerals from the rock minerals with larger distribution areas, and use them as the distribution areas of the corresponding rock minerals to be classified.

[0104] Based on the same inventive concept, embodiments of the present invention provide a system for measuring stone ore based on AI, including a memory and a processor, wherein the memory stores information that can run on the processor to implement, as described above. Figures 1 to 7 The procedure for any method.

[0105] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for measuring stone based on AI artificial intelligence, characterized by, include: Obtain the spectral data of the rocks and minerals to be classified and their locations; Based on the pre-defined correspondence between rock and mineral types and spectral data, the obtained spectral data of the rocks and minerals to be classified, and their locations, the types and locations of the rocks and minerals to be classified are analyzed and determined. Based on the types of rocks and minerals obtained from the historical location data, and the types of rocks and minerals to be classified determined in this analysis, it is determined whether all types of rocks and minerals to be classified in this analysis fall within the types of rocks and minerals obtained from the historical location data. If yes, then analyze whether the number of the same type of rock minerals to be classified exceeds the preset number. If it exceeds the preset number, then plan the distribution area of ​​the same type of rock minerals to be classified based on the type of the same type of rock minerals and the obtained location, and send the distribution area of ​​the same type of rock minerals to the terminal held by the person in charge. If not, then mark the rock and mineral types that do not fall into the rock and mineral types obtained in the history of the obtained location, and send the rock and mineral types to be classified in this analysis to the terminal held by the person in charge. Sending the distribution area of ​​the same type of rock and mineral to be classified to the terminal held by the person in charge includes: Obtain the types of rocks and minerals in the target category set by the person in charge; Analyze the distribution areas of multiple types of rocks and minerals to be classified; If so, before sending the distribution area of ​​the same type of rock mineral to be classified to the terminal held by the person in charge, the information of the distribution area of ​​the target type of rock mineral set by the person in charge will be sorted before the distribution area of ​​the other types of rock mineral to be classified. If not, the distribution area of ​​the same type of rock mineral to be classified will be sent to the terminal held by the person in charge. It also includes steps that occur after obtaining the types of rocks and minerals for the target classification set by the person in charge and before analyzing whether there are distribution areas of multiple types of rocks and minerals to be classified, as follows: Based on the pre-defined correspondence between the types of rock and minerals classified according to the target set by the person in charge and the accuracy of their distribution areas, analyze the accuracy of the distribution areas. Based on the correspondence between the accuracy of the distribution location area, the range of the distribution location area, and the preset number of the same type of rock minerals to be classified, the preset number of the same type of rock minerals to be classified is determined. If the number of rock minerals of the same type to be classified is less than the preset number of rock minerals of the same type to be classified, then the subsequent steps are stopped, and the missing number of rock minerals of the same type to be classified is calculated and sent to the terminal held by the person in charge. If the number of rock minerals of the same type to be classified is greater than or equal to the preset number of rock minerals of the same type to be classified, then continue with the subsequent steps; It also includes a step following the analysis of the distribution regions of multiple types of rocks and minerals to be classified, as follows: Analyze whether there is any overlap in the distribution areas of multiple rock and mineral species to be classified; If so, the terrains where overlap occurs are obtained, and the probability of existing in the same terrain is analyzed and determined based on the pre-defined correspondence between the types of different rock minerals and the probability of existing in the same terrain. If the probability of them existing in the same terrain exceeds the first preset probability, then continue with the subsequent steps; If the probability of existing in the same terrain is less than or equal to the first preset probability and exceeds the second preset probability, then retain the distribution area of ​​different rocks and minerals and make a deletion prompt mark, and send it to the terminal held by the person in charge; Obtain the distribution area of ​​different rocks and minerals as reported by the terminal held by the person in charge; If the probability of existing in the same terrain is less than or equal to the second preset probability, then the distribution areas of the remaining rock minerals are removed from the rock minerals with larger distribution areas, and these are used as the distribution areas of the corresponding rock minerals to be classified.

2. The method for measuring stone based on AI artificial intelligence according to claim 1, characterized in that, The analysis and determination of the types of rocks and minerals to be classified and their locations include: Based on the obtained spectral data of the rocks and minerals to be classified and the correspondence between the rock and mineral types and the spectral data, the types of rocks and minerals to be classified are queried. If found, the type of rock or mineral to be classified is used as the type of rock or mineral to be classified, and the type and location of the rock or mineral to be classified are obtained. If no results are found, the spectral data of the unclassified rock and mineral species will be sent as a notification to the terminal held by the person in charge. Obtain the types of rocks and minerals to be classified corresponding to the spectral data fed back by the terminal held by the person in charge, and obtain the types of rocks and minerals to be classified and their locations.

3. The method for measuring stone based on AI artificial intelligence according to claim 2, characterized in that, Obtain the types of rocks and minerals to be classified corresponding to the spectral data fed back by the terminal held by the person in charge, and obtain the types of rocks and minerals to be classified and their locations, including: Analyze whether the type of rock and mineral to be classified is received from the spectral data fed back by the terminal held by the person in charge within the preset time. If yes, then continue with the following steps; If not, then a communication group will be created based on the contact information of the pre-set rock and mineral type identification experts, and the spectral data of the rock and mineral types that cannot be identified will be sent to the group. Obtain the types of rocks and minerals to be classified corresponding to the spectral data fed back by the preset rock and mineral type identification experts, and use them as the types of rocks and minerals to be classified in this case.

4. The method for measuring stone based on AI artificial intelligence according to claim 1, characterized in that, The types of rocks and minerals to be acquired according to the target classification set by the person in charge include: Check whether the person in charge has set a target classification for rock and mineral types; If so, the type of rock and mineral in the target classification set by the person in charge shall be used as the type of rock and mineral in the target classification set by the person in charge. If not, then based on the target category of rocks and minerals set by the person in charge in the past, find the type of target category of rocks and minerals that has been set the most times, and use it as the type of target category of rocks and minerals set by the person in charge.

5. A system for measuring stone based on AI artificial intelligence, characterized by: It includes a memory, a processor, and a program stored in the memory and executable on the processor, which, when loaded and executed by the processor, implements the method for measuring stone ore based on any one of claims 1 to 4.

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