Uranium mine detection equipment control method and system based on cloud platform

Abstract

The invention discloses a uranium mine detection equipment control method and system based on a cloud platform, and relates to the technical field of mineral resource detection. The method comprises the following steps: constructing a uranium mine detection equipment network, and obtaining detection data; transmitting the detection data to a cloud platform for cleaning and preprocessing to obtain preprocessed data after noise data and abnormal data are removed; performing multi-source data fusion analysis on the preprocessed data, and determining uranium mine key parameters and a uranium mine prediction area; performing equipment control judgment based on the uranium mine key parameters, outputting a corresponding control instruction, and feeding back the control instruction to the corresponding equipment; wherein the process of equipment control judgment is as follows: when the uranium ore grade and the radon gas concentration exceed set threshold values, a control instruction for increasing corresponding equipment parameters is output; and when the environmental parameters exceed a set threshold value, outputting a control instruction for starting an execution mechanism. The uranium mine detection efficiency and accuracy can be improved, and the detection cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of mineral resource exploration technology, and in particular to a cloud platform-based control method and system for uranium ore exploration equipment. Background Technology

[0002] Uranium, a key strategic resource for the nuclear industry, requires efficient and accurate detection for ensuring national energy security and the sustainable development of the nuclear industry. Traditional uranium detection methods rely primarily on manual on-site operation and localized data processing, resulting in low detection efficiency, poor data real-time performance, and difficulties in large-scale collaborative detection. With the rapid development of technologies such as the Internet of Things, cloud computing, and big data, remote control and data management based on cloud platforms have become effective solutions to these problems. However, currently, there is no mature cloud-based control method for uranium detection equipment, which fails to fully leverage the advantages of cloud platforms in data processing, storage, and sharing, thus limiting the development of uranium detection technology. Summary of the Invention

[0003] The purpose of this invention is to provide a cloud platform-based control method and system for uranium ore detection equipment, aiming to solve or improve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, the present invention provides the following solution:

[0005] A control method for uranium ore detection equipment based on a cloud platform, comprising:

[0006] A network of uranium ore detection equipment is constructed to acquire detection data; the network consists of an electron accelerator, a photon detector, a neutron detector, an activated carbon detector, a sensor array, and an actuator.

[0007] The probe data is transmitted to a cloud platform for cleaning and preprocessing to obtain preprocessed data after removing noise and abnormal data.

[0008] Multi-source data fusion analysis is performed on the preprocessed data to determine key parameters of uranium ore and uranium ore prediction areas; the key parameters of uranium ore include uranium ore grade, radon concentration and environmental parameters;

[0009] Based on the key parameters of the uranium mine, equipment control decisions are made, corresponding control commands are output, and the control commands are fed back to the corresponding equipment; wherein, the equipment control decision process is as follows:

[0010] When the uranium ore grade and radon concentration exceed the set threshold, a control command to increase the corresponding equipment parameters is output; when the environmental parameters exceed the set threshold, a control command to start the actuator is output.

[0011] Optionally, the sensor group includes, but is not limited to, temperature sensors, humidity sensors, and gas sensors; the actuator includes ventilation equipment and dust suppression equipment.

[0012] Optionally, the uranium ore detection equipment network and the cloud platform communicate bidirectionally via wireless communication technology.

[0013] Optionally, before using the uranium ore detection equipment network for detection, the method further includes: initializing and connecting each component device, specifically: performing a device self-test on each component device, starting the device when there are no errors in all devices, and establishing a connection with the cloud platform through wireless communication technology.

[0014] Optionally, the process of acquiring detection data by networking the uranium ore detection equipment specifically includes:

[0015] An electron accelerator is controlled to emit an electron beam toward uranium ore in a target area at a fixed beam emission period. The emission energy of the electron beam is 5.6 MeV-10.55 MeV. Simultaneously, a photon detector is controlled to detect the scattered photons generated by the electron beam excitation of uranium ore in a cumulative mode within the response time after the electron beam emission, generating a first count rate. In response to the cumulative delay time after the electron beam emission, a neutron detector is controlled to detect the fission neutrons generated by the electron beam excitation of uranium ore in a pulse mode, generating a second count rate.

[0016] Set up measurement points in the target area, place an activated carbon adsorber on the ground at each measurement point, dig a circular pit and bury an activated carbon detector, and periodically remove the activated carbon detectors on the ground and underground at each measurement point to measure the radon concentration values ​​on the ground and underground.

[0017] The sensor array is used to collect and detect environmental parameters at the site in real time.

[0018] Optionally, the step of performing multi-source data fusion analysis on the preprocessed data to determine key uranium ore parameters and uranium ore prediction areas specifically includes:

[0019] Based on the first count rate collected by the photon detector and the second count rate collected by the neutron detector, the grade information of uranium ore is determined by a preset algorithm; the preset algorithm is an algorithm that establishes a relationship model between the count rate and the grade of uranium ore based on the physical characteristics of uranium fission neutron production cross section, etc.

[0020] The radon concentration values ​​collected by the activated carbon detector were analyzed, and combined with geological exploration data and historical data, the predicted area of ​​uranium mineralization was determined.

[0021] Analyze the parameters collected by the sensor array to determine the environmental parameters that affect the safety of the on-site environment.

[0022] Optionally, it also includes: constructing a corresponding visualization diagram based on the key parameters of the uranium ore; the visualization diagram includes a uranium ore grade distribution diagram, a radon concentration distribution diagram, and environmental parameter change curves.

[0023] This invention also provides a cloud-based control system for uranium ore detection equipment, comprising:

[0024] The data acquisition unit is used to construct a network of uranium ore detection equipment and acquire detection data; the equipment network consists of an electron accelerator, a photon detector, a neutron detector, an activated carbon detector, a sensor group, and an actuator.

[0025] The data preprocessing unit is used to transmit the probe data to the cloud platform for cleaning and preprocessing to obtain preprocessed data after removing noise and abnormal data.

[0026] The data analysis unit is used to perform multi-source data fusion analysis on the preprocessed data to determine key parameters of uranium ore and uranium ore prediction areas; the key parameters of uranium ore include uranium ore grade, radon concentration and environmental parameters;

[0027] The equipment instruction output unit is used to make equipment control judgments based on the key parameters of the uranium ore, output corresponding control instructions, and feed the control instructions back to the corresponding equipment. The equipment control judgment process is as follows: when the uranium ore grade and radon concentration exceed the set threshold, the unit outputs a control instruction to increase the corresponding equipment parameters; when the environmental parameters exceed the set threshold, the unit outputs a control instruction to start the actuator.

[0028] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0029] This invention discloses a cloud-based control method and system for uranium ore detection equipment. The method includes: constructing a network of uranium ore detection equipment and acquiring detection data; transmitting the detection data to a cloud platform for cleaning and preprocessing to obtain preprocessed data after removing noise and abnormal data; performing multi-source data fusion analysis on the preprocessed data to determine key uranium ore parameters and predicted uranium ore areas; and making equipment control judgments based on the key uranium ore parameters, outputting corresponding control commands, and feeding the control commands back to the corresponding equipment. The equipment control judgment process is as follows: when the uranium ore grade and radon concentration exceed a set threshold, a control command to increase the corresponding equipment parameters is output; when environmental parameters exceed a set threshold, a control command to start the actuator is output. This invention enables remote control of uranium ore detection equipment, real-time data acquisition and analysis, and visualization of detection results through a cloud platform, improving the efficiency and accuracy of uranium ore detection and reducing detection costs. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. 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 effort.

[0031] Figure 1 This is a flowchart illustrating the control method for uranium ore detection equipment in this embodiment. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] The purpose of this invention is to provide a cloud platform-based control method and system for uranium ore detection equipment, aiming to solve or improve at least one of the above-mentioned technical problems.

[0034] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0035] As a first aspect, the present invention provides, as follows Figure 1 The method for controlling a cloud-based uranium ore detection device, as shown, includes:

[0036] Step 100: Construct a network of uranium ore detection equipment and acquire detection data; the equipment network consists of an electron accelerator, a photon detector, a neutron detector, an activated carbon detector, a sensor array, and actuators. The sensor array includes, but is not limited to, temperature sensors, humidity sensors, and gas sensors; the actuators include ventilation equipment and dust suppression equipment.

[0037] Step 200: The detected data is transmitted to the cloud platform for cleaning and preprocessing to obtain preprocessed data after removing noise and abnormal data. The uranium ore detection equipment network communicates bidirectionally with the cloud platform via wireless communication technology.

[0038] Step 300: Perform multi-source data fusion analysis on the preprocessed data to determine key parameters of uranium ore and uranium ore prediction areas; the key parameters of uranium ore include uranium ore grade, radon concentration and environmental parameters.

[0039] Step 400: Based on the key parameters of the uranium ore, perform equipment control judgment, output corresponding control commands, and feed the control commands back to the corresponding equipment; wherein, the equipment control judgment process is as follows: when the uranium ore grade and radon concentration exceed the set threshold, output a control command to increase the corresponding equipment parameters; when the environmental parameters exceed the set threshold, output a control command to start the actuator.

[0040] As a specific implementation method, before using the uranium ore detection equipment network for detection, the method further includes: initializing and connecting each component device, specifically: performing a device self-test on each component device, starting the device when there are no errors in all devices, and establishing a connection with the cloud platform through wireless communication technology (such as Wi-Fi, 4G / 5G, etc.) to ensure normal bidirectional communication between the device network and the cloud platform.

[0041] As a specific implementation method, step 100, the process of acquiring detection data using the uranium ore detection equipment network, specifically includes:

[0042] An electron accelerator is controlled to emit an electron beam toward the uranium ore in the target area at a fixed beam emission period (e.g., 4ms-100ms). The emission energy of the electron beam is 5.6MeV-10.55MeV. Simultaneously, a photon detector is controlled to detect the scattered photons generated by the uranium ore excited by the electron beam in cumulative mode within the response time (less than 5μs) after the electron beam emission, generating a first count rate. In response to the cumulative delay time (0.1ms-2ms) after the electron beam emission, a neutron detector is controlled to detect the fission neutrons generated by the uranium ore excited by the electron beam in pulse mode, generating a second count rate.

[0043] Measurement points were set up in the target area. An activated carbon adsorber was placed on the ground at each measurement point. At the same time, a circular pit with a diameter of 30 cm and a depth of 50 cm was dug and an activated carbon detector was buried. The activated carbon detectors on the ground and underground at each measurement point were periodically removed to measure the radon concentration values ​​on the ground and underground. The environmental parameters of the detection site were collected in real time using a sensor array.

[0044] As one specific implementation method, step 200 specifically includes:

[0045] The detection data (first count rate, second count rate, radon concentration value, environmental parameters, etc.) obtained in step 100 are transmitted to the cloud platform in real time using wireless communication technology.

[0046] In the cloud platform, data cleaning algorithms are used to remove noisy and outlier data from the probe data. For example, for data collected by a temperature sensor, if the difference between a data point and its neighboring data points exceeds a set reasonable range (e.g., more than three times the standard deviation of the average), the data point is considered outlier and removed. The cleaned data is then preprocessed, such as through data normalization and smoothing, to improve data quality and usability, resulting in preprocessed data.

[0047] As one specific implementation method, step 300 specifically includes:

[0048] Based on the first count rate collected by the photon detector and the second count rate collected by the neutron detector, the grade information of uranium ore is determined through a preset algorithm. The preset algorithm is an algorithm that establishes a relationship model between the count rate and the uranium ore grade based on the physical properties of uranium, such as the neutron production cross-section during fission. For example, a mathematical model is fitted using a large amount of experimental data, with the first and second count rates as input variables, and the uranium ore grade value is output.

[0049] The radon concentration values ​​collected by activated carbon detectors are analyzed, and combined with geological exploration data (such as stratigraphic structure and rock type) and historical data (previous uranium deposit exploration data in this or similar areas), data mining and machine learning algorithms (such as decision trees and neural networks) are used to determine the predicted areas of uranium mineralization. For example, if the radon concentration value in a certain area is consistently higher than that in the surrounding areas, and geological exploration data shows that the stratigraphic structure of the area is conducive to uranium formation, then this area is identified as a predicted area for uranium mineralization.

[0050] The parameters (temperature, humidity, gas concentration, etc.) collected by the sensor array are analyzed to determine the environmental parameters that affect the safety of the site. For example, when the gas sensor detects that the concentration of a certain harmful gas (such as radon, carbon dioxide, etc.) exceeds the safety threshold, the gas concentration is taken as the environmental parameter affecting the safety of the site.

[0051] Furthermore, for the key uranium ore parameters in step 300, the following additional steps are taken: Based on the determined key uranium ore parameters (uranium ore grade, radon concentration, and environmental parameters), construct corresponding visualization maps. For example, use Geographic Information System (GIS) technology to create a uranium ore grade distribution map, marking areas with different grades with different colors; create a radon concentration distribution map to visually display the distribution of radon in the target area; and create environmental parameter change curves to reflect the real-time trends of environmental parameters over time.

[0052] As one specific implementation method, step 400 specifically includes:

[0053] When the uranium ore grade and radon concentration exceed the set thresholds, control commands are output to increase the corresponding equipment parameters. For example, if the uranium ore grade is higher than the set economic mining grade threshold and the radon concentration is higher than the safety threshold, control commands are output to increase the output beam energy or frequency of the electron accelerator to improve detection accuracy; at the same time, control commands are output to increase the detection sensitivity of the photon detector and neutron detector.

[0054] When environmental parameters exceed set thresholds, a control command to start the actuator is output. For example, when the temperature sensor detects that the temperature is too high or the gas sensor detects that the concentration of harmful gases is too high, a control command to start the ventilation equipment is output; when the humidity sensor detects that the humidity is too high, a control command to start the dust suppression equipment is output.

[0055] The output control commands are fed back to the corresponding equipment (electron accelerator, photon detector, neutron detector, ventilation equipment, dust suppression equipment, etc.) via wireless communication technology, thereby enabling remote control of the equipment.

[0056] Based on the above technical solution, the following embodiments are provided.

[0057] The target area was defined as a mountainous region of 1 square kilometer with complex geological conditions and multiple strata that may contain uranium deposits. To accurately detect the location and grade of uranium ore and ensure environmental safety at the detection site, the aforementioned cloud-based uranium ore detection equipment control method was adopted.

[0058] The specific implementation process includes:

[0059] Step 100:

[0060] In the target area, a network of uranium ore detection equipment was constructed using the method described above, and each device was initialized and connected. After self-testing, all devices reported no errors and successfully established a connection with the cloud platform.

[0061] The electron accelerator is controlled to emit an 8 MeV electron beam towards the uranium ore in the target area at a beam emission period of 15 ms. The photon detector detects scattered photons in cumulative mode within a 5 μs response time after the electron beam emission, generating the first count rate; the neutron detector detects fission neutrons in pulse mode after a 1 ms delay after the electron beam emission, generating the second count rate.

[0062] A measuring point was set up every 100 meters in the target area, for a total of 100 measuring points. An activated carbon adsorber was placed on the ground at each measuring point, and a circular pit was dug to bury the activated carbon detector. The activated carbon detector was removed every 24 hours to measure the radon concentration values ​​at the ground and underground.

[0063] The sensor array collects environmental parameters such as temperature, humidity, and gas concentration at the detection site in real time and transmits them to the control unit of the equipment network.

[0064] Step 200:

[0065] The detection data is transmitted to the cloud platform in real time using wireless communication technology.

[0066] In the cloud platform, data cleaning algorithms are used to remove noisy and outlier data, such as removing abnormally high-temperature data points caused by equipment malfunctions in temperature sensors. The cleaned data is then normalized to obtain preprocessed data.

[0067] Step 300:

[0068] Based on the first and second count rates, the grade information of uranium ore is determined using a pre-defined relational model algorithm. Calculations show that the uranium ore grade in some areas is between 0.1‰ and 0.5‰.

[0069] Analyzing the radon concentration values ​​collected by the activated carbon detector, and combining them with geological exploration data and historical data, a decision tree algorithm was used to determine the predicted area for uranium mineralization. A stratigraphic region in the central part of the target area was found to have a high radon concentration and geological conditions favorable for uranium formation; therefore, this region was determined to be the predicted area for uranium mineralization.

[0070] Analysis of the environmental parameters collected by the sensor array revealed that the concentration of harmful gases in some areas exceeded the safety threshold, and these gas concentrations were identified as environmental parameters affecting on-site environmental safety.

[0071] GIS technology was used to construct uranium ore grade distribution maps, radon concentration distribution maps, and environmental parameter change curves, which were then visualized on the monitoring interface of the cloud platform.

[0072] Step 400:

[0073] When the uranium ore grade in a certain area is detected to be higher than 0.3‰ and the radon concentration is higher than the safety threshold, control commands are output to increase the output energy of the electron accelerator to 9MeV and increase the detection sensitivity of the photon detector and neutron detector.

[0074] When the sensor array detects that the concentration of harmful gases in a certain area exceeds the safety threshold, it outputs a control command to start the ventilation equipment; when it detects that the humidity is too high, it outputs a control command to start the dust suppression equipment.

[0075] Control commands are fed back to the corresponding equipment via wireless communication technology, enabling remote control of the equipment and ensuring the smooth progress of uranium ore exploration and the safety of the on-site environment.

[0076] As a second aspect, the present invention also provides a cloud-based uranium ore detection equipment control system for executing the control method described above, comprising:

[0077] The data acquisition unit is used to construct a network of uranium ore detection equipment and acquire detection data; the equipment network consists of an electron accelerator, a photon detector, a neutron detector, an activated carbon detector, a sensor group, and an actuator.

[0078] The data preprocessing unit is used to transmit the probe data to the cloud platform for cleaning and preprocessing to obtain preprocessed data after removing noise and abnormal data.

[0079] The data analysis unit is used to perform multi-source data fusion analysis on the preprocessed data to determine key parameters of uranium ore and uranium ore prediction areas; the key parameters of uranium ore include uranium ore grade, radon concentration and environmental parameters.

[0080] The equipment instruction output unit is used to make equipment control judgments based on the key parameters of the uranium ore, output corresponding control instructions, and feed the control instructions back to the corresponding equipment. The equipment control judgment process is as follows: when the uranium ore grade and radon concentration exceed the set threshold, the unit outputs a control instruction to increase the corresponding equipment parameters; when the environmental parameters exceed the set threshold, the unit outputs a control instruction to start the actuator.

[0081] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0082] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A control method for uranium ore detection equipment based on a cloud platform, characterized in that, include: A network of uranium ore detection equipment is constructed to acquire detection data; the network consists of an electron accelerator, a photon detector, a neutron detector, an activated carbon detector, a sensor array, and an actuator. The probe data is transmitted to a cloud platform for cleaning and preprocessing to obtain preprocessed data after removing noise and abnormal data. Multi-source data fusion analysis is performed on the preprocessed data to determine key parameters of uranium ore and uranium ore prediction areas; the key parameters of uranium ore include uranium ore grade, radon concentration and environmental parameters; Based on the key parameters of the uranium mine, equipment control decisions are made, corresponding control commands are output, and the control commands are fed back to the corresponding equipment; wherein, the equipment control decision process is as follows: When the uranium ore grade and radon concentration exceed the set threshold, a control command to increase the corresponding equipment parameters is output; when the environmental parameters exceed the set threshold, a control command to start the actuator is output.

2. The control method for uranium ore detection equipment based on a cloud platform according to claim 1, characterized in that, The sensor group includes, but is not limited to, temperature sensors, humidity sensors, and gas sensors; the actuators include ventilation equipment and dust suppression equipment.

3. The control method for uranium ore detection equipment based on a cloud platform according to claim 1, characterized in that, The uranium ore detection equipment network communicates bidirectionally with the cloud platform via wireless communication technology.

4. The control method for uranium ore detection equipment based on a cloud platform according to claim 1, characterized in that, Before using the uranium ore detection equipment network for detection, the process also includes: initializing and connecting each component device, specifically: performing a device self-test on each component device, starting the device when there are no errors, and establishing a connection with the cloud platform through wireless communication technology.

5. The control method for uranium ore detection equipment based on a cloud platform according to claim 1, characterized in that, The process of acquiring detection data by networking the aforementioned uranium ore detection equipment specifically includes: An electron accelerator is controlled to emit an electron beam toward uranium ore in a target area at a fixed beam emission period. The emission energy of the electron beam is 5.6 MeV-10.55 MeV. Simultaneously, a photon detector is controlled to detect the scattered photons generated by the electron beam excitation of uranium ore in a cumulative mode within the response time after the electron beam emission, generating a first count rate. In response to the cumulative delay time after the electron beam emission, a neutron detector is controlled to detect the fission neutrons generated by the electron beam excitation of uranium ore in a pulse mode, generating a second count rate. Set up measurement points in the target area, place an activated carbon adsorber on the ground at each measurement point, dig a circular pit and bury an activated carbon detector, and periodically remove the activated carbon detectors on the ground and underground at each measurement point to measure the radon concentration values ​​on the ground and underground. The sensor array is used to collect and detect environmental parameters at the site in real time.

6. The control method for uranium ore detection equipment based on a cloud platform according to claim 5, characterized in that, The step of performing multi-source data fusion analysis on the preprocessed data to determine key parameters of uranium ore and uranium ore prediction areas specifically includes: Based on the first count rate collected by the photon detector and the second count rate collected by the neutron detector, the grade information of uranium ore is determined by a preset algorithm; the preset algorithm is an algorithm that establishes a relationship model between the count rate and the grade of uranium ore based on the physical characteristics of uranium fission neutron production cross section, etc. The radon concentration values ​​collected by the activated carbon detector were analyzed, and combined with geological exploration data and historical data, the predicted area of ​​uranium mineralization was determined. Analyze the parameters collected by the sensor array to determine the environmental parameters that affect the safety of the on-site environment.

7. The control method for uranium ore detection equipment based on a cloud platform according to claim 1, characterized in that, Also includes: A corresponding visualization diagram is constructed based on the key parameters of the uranium ore; the visualization diagram includes a uranium ore grade distribution diagram, a radon concentration distribution diagram, and environmental parameter change curves.

8. A cloud-based control system for uranium ore detection equipment, characterized in that, include: The data acquisition unit is used to construct a network of uranium ore detection equipment and acquire detection data; the equipment network consists of an electron accelerator, a photon detector, a neutron detector, an activated carbon detector, a sensor group, and an actuator. The data preprocessing unit is used to transmit the probe data to the cloud platform for cleaning and preprocessing to obtain preprocessed data after removing noise and abnormal data. The data analysis unit is used to perform multi-source data fusion analysis on the preprocessed data to determine key parameters of uranium ore and uranium ore prediction areas; the key parameters of uranium ore include uranium ore grade, radon concentration and environmental parameters; The equipment instruction output unit is used to make equipment control judgments based on the key parameters of the uranium ore, output corresponding control instructions, and feed the control instructions back to the corresponding equipment. The equipment control judgment process is as follows: when the uranium ore grade and radon concentration exceed the set threshold, the unit outputs a control instruction to increase the corresponding equipment parameters; when the environmental parameters exceed the set threshold, the unit outputs a control instruction to start the actuator.

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