Intelligent transportation status monitoring method and system for smelting rare earth

Abstract

The present invention relates to the general field of control system technology, and in particular to a method and system for monitoring the intelligent transportation status of smelting rare earths. The present invention analyzes the matching of rare earth particles and transportation components based on the characteristics of rare earth transportation, performs abnormal analysis of the transportation equipment under magnetic interference based on the equipment operation stability evaluation results and the magnetic data of the transported rare earths, and finally performs transportation status analysis based on the rare earth transportation efficiency evaluation results and the equipment operation abnormality evaluation results, thereby improving the accuracy of the matching analysis between rare earth particles and transportation components.

Description

Technical Field

[0001] The present invention relates to the general technical field of control systems, and in particular to a method and system for monitoring the intelligent transportation status of smelting rare earth. Background Art

[0002] Rare earth elements are a special group of metallic elements, comprising 17 elements in total. These elements possess special magnetic and optical properties due to their unique electronic structure. Due to their excellent physical and chemical properties, rare earth elements are widely used in many high-tech fields. For example, they can be used to manufacture powerful permanent magnets, catalysts, magnetic materials, fluorescent materials, laser materials, superconducting materials, etc., playing a vital role in the development of modern science and technology. In industry, rare earth elements can improve the properties of alloys and are used to manufacture special steels, aluminum alloys, magnesium alloys, etc.

[0003] The intelligent transportation status monitoring method for smelting rare earth mainly uses modern information technology and automatic control technology to monitor and manage the transportation link of rare earth metals in real time. The existing technology installs various sensors on the conveying line of rare earth metal smelting, such as temperature sensors, pressure sensors, flow sensors, displacement sensors, etc., to collect various parameters in the transportation process in real time to monitor the safety of the transportation process. However, due to the magnetism of rare earth, it will have a negative impact on the transportation status. At the same time, the existing technology cannot analyze the matching of rare earth particles and conveying components based on the characteristics of rare earth transportation, resulting in the inability to perform abnormal analysis of conveying equipment under magnetic interference based on the equipment operation stability evaluation results and the magnetic data of the conveyed rare earth, which reduces the accuracy of the matching analysis of rare earth particles and conveying components.

[0004] In order to solve these problems, the present application designs a method and system for monitoring the intelligent transportation status of smelting rare earth. Summary of the Invention

[0005] In order to overcome the defects and shortcomings of the existing technology, the present invention provides a method and system for monitoring the intelligent transportation status of smelting rare earths. Based on the characteristics of rare earth transportation, the matching of rare earth particles and transportation components is analyzed. Based on the equipment operation stability evaluation results and the magnetic data of the transported rare earth, the abnormality analysis of the transportation equipment under magnetic interference is performed. Finally, the transportation status is analyzed based on the rare earth transportation efficiency evaluation results and the equipment operation abnormality evaluation results, thereby improving the accuracy of the matching analysis between rare earth particles and transportation components.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a method for monitoring the intelligent transportation status of rare earth smelting, comprising the following steps:

[0008] S1, obtaining rare earth particle image data, magnetic data of transported rare earth, and equipment operation data;

[0009] S2. evaluating the rare earth transport efficiency based on the rare earth particle image data and the smoothness of the transport components of the transport equipment;

[0010] S3. Evaluate equipment operation stability based on equipment control operation data;

[0011] S4. Evaluate equipment operation abnormalities during rare earth transportation based on equipment operation stability evaluation results and magnetic data of the transported rare earth;

[0012] S5. Analyze the transportation status based on the rare earth transportation efficiency evaluation results and the equipment operation abnormality evaluation results;

[0013] S6. Issue an early warning of abnormal transportation based on the transportation status analysis results.

[0014] In one implementation of the present invention, obtaining rare earth particle image data, magnetic data of transported rare earth particles, and equipment operation data in step S1 includes the following specific steps:

[0015] S11, acquiring image data of the rare earth particles to be transported through the image acquisition terminal, separating the rare earth particles from the background image to obtain contour data of the rare earth particles in the image, and storing the data in the contour storage component;

[0016] S12, obtaining magnetic field size data of the rare earth to be transported through a magnetic data acquisition terminal, and storing the data in a magnetic field size storage component;

[0017] S13. Collecting equipment operation data through the equipment operation collection terminal, wherein the equipment operation data includes equipment control instruction execution data, conveying process vibration data and equipment transmission component surface wear data, and storing the data in the equipment operation data storage component.

[0018] In one implementation of the present invention, step S2 evaluates the rare earth transport efficiency based on the rare earth particle image data and the smoothness of the transport component of the transport device, including the following specific steps:

[0019] S21, obtaining rare earth particle profile data, analyzing the roundness of each rare earth particle based on the rare earth particle profile data, and obtaining the conveying difficulty based on the weighted sum of the average value and uniformity of the roundness of the rare earth particles; comprising the following specific steps:

[0020] S211, obtaining rare earth particle contour data, and analyzing the roundness of each rare earth particle based on the rare earth particle contour data;

[0021] S212. averaging the roundness of all rare earth particles to obtain an average roundness value of the rare earth particles. Substituting the roundness of all rare earth particles into a uniformity calculation formula to obtain the uniformity of the rare earth particles. A weighted sum of the average roundness value of the rare earth particles and the uniformity of the rare earth particles is performed to obtain a conveying difficulty.

[0022] S22. Analyze the smoothness of the surface conveying component based on the wear data of the surface of the equipment transmission component. Obtain relative height data of each point on the surface of the equipment transmission component. Obtain the smoothness of the surface conveying component based on the inverse of the standard deviation of the relative height data of each point on the surface of the equipment transmission component. The smoother the surface of the conveying component, the easier it is for the rare earth particles to roll off the conveying module. Therefore, the smoothness of the surface conveying component and the conveying difficulty are used to comprehensively analyze the conveying efficiency of the conveying component.

[0023] S23. Obtain the conveying efficiency of the conveying component by taking the inverse of the weighted sum of the conveying difficulty and the smoothness of the surface conveying component.

[0024] In one implementation of the present invention, the step S3 of evaluating the equipment operation stability based on the control operation data of the equipment includes the following specific steps:

[0025] S31, extracting the equipment control instruction execution data of the conveying drive component during the test process, and simultaneously obtaining the vibration data of the surface conveying component during operation;

[0026] S32. Perform instruction execution fluctuation anomaly analysis based on the device control instruction execution data of the conveying drive component, wherein the instruction execution fluctuation anomaly analysis formula is: , where T is the test duration of the conveyor drive component, ft is the speed of the drive component after the speed control instruction at time t, ftm is the standard speed corresponding to the speed control instruction at time t, and dt is the time integral;

[0027] S33, performing vibration abnormality analysis of the surface conveying assembly based on the vibration data of the surface conveying assembly during operation;

[0028] S34. The equipment operation stability evaluation result is obtained by taking the inverse of the weighted sum of the instruction execution volatility anomaly analysis result and the surface conveying component vibration anomaly analysis result. In this way, the equipment operation stability and the surface conveying component stability are used to analyze the equipment's rare earth transportation stability during the transportation process.

[0029] In one implementation of the present invention, the evaluation of equipment operation abnormality during rare earth transportation based on the equipment operation stability evaluation result and the magnetic data of the transported rare earth in step S4 includes the following specific steps:

[0030] S41. Obtain magnetic data of the transported rare earths and analyze electromagnetic interference anomalies based on the magnetic data. Rare earth permanent magnet materials (such as neodymium iron boron) have high magnetic permeability and remanence, and can generate a strong magnetic field in the motor. This strong magnetic field may generate electromagnetic interference (EMI) to nearby electronic equipment, affecting the normal operation of the equipment.

[0031] S42. The obtained electromagnetic interference anomaly and equipment operation stability evaluation results are used to evaluate the equipment operation anomaly during the transportation of rare earths. In this way, the negative impact of the rare earth magnetic field on the equipment stability is used to comprehensively evaluate the equipment anomaly during the transportation of rare earths.

[0032] In one implementation of the present invention, the transport status analysis is performed based on the rare earth transport efficiency evaluation result and the equipment operation abnormality evaluation result in step S5, including the following specific contents:

[0033] S51. Obtaining the analyzed equipment operation abnormality assessment results and the transport efficiency assessment results during the rare earth transport process;

[0034] S52. The inverse of the equipment operation abnormality evaluation result obtained through analysis during the transportation of rare earths and the transportation efficiency evaluation result are normalized and then weighted summed to obtain a transportation status analysis value.

[0035] In one implementation of the present invention, the abnormality warning of transportation is performed based on the transportation status analysis result in step S6, including the following specific steps:

[0036] S61, obtaining the estimated transport state analysis value during the transport process;

[0037] S62. Preset a conveying status analysis threshold. When the conveying status analysis value during the conveying process is greater than the conveying status analysis threshold, it means that the corresponding conveying equipment can normally convey the rare earths. If the conveying status analysis value during the conveying process is less than or equal to the conveying status analysis threshold, it means that the corresponding conveying equipment cannot normally convey the rare earths, and an early warning is issued to the staff, reminding them that the conveying equipment needs to be maintained or replaced.

[0038] In a second aspect, the present invention further provides a system for monitoring the state of an intelligent rare earth smelting conveyor, comprising:

[0039] A data acquisition module is used to obtain rare earth particle image data, magnetic data of transported rare earth, and equipment operation data;

[0040] A rare earth transport efficiency analysis module evaluates rare earth transport efficiency based on rare earth particle image data and the smoothness of the transport equipment's transport components;

[0041] Operation stability assessment module, which assesses equipment operation stability based on the equipment's control operation data;

[0042] Equipment operation abnormality assessment module, which assesses equipment operation abnormalities during rare earth transportation based on equipment operation stability assessment results and magnetic data of transported rare earths;

[0043] The transportation status analysis module performs transportation status analysis based on the rare earth transportation efficiency evaluation results and equipment operation abnormality evaluation results;

[0044] The transportation abnormality warning module provides transportation abnormality warning based on the transportation status analysis results.

[0045] In a third aspect, the present invention provides an electronic device comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a method for monitoring the intelligent transportation status of smelting rare earths by calling the computer program stored in the memory.

[0046] In a fourth aspect, the present invention provides a computer-readable storage medium storing instructions, which, when executed on a computer, enables the computer to execute a method for monitoring the intelligent transportation status of smelting rare earths.

[0047] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0048] The present invention evaluates the rare earth conveying efficiency based on rare earth particle image data and the smooth state of the conveying component of the conveying equipment, evaluates the equipment operation stability based on the control operation data of the equipment, evaluates the equipment operation abnormality during the conveying of rare earth based on the equipment operation stability evaluation result and the magnetic data of the conveyed rare earth, analyzes the conveying state based on the rare earth conveying efficiency evaluation result and the equipment operation abnormality evaluation result, performs a conveying abnormality warning based on the conveying state analysis result, analyzes the matching of rare earth particles and conveying components based on the characteristics of rare earth conveying, analyzes the conveying equipment abnormality under magnetic interference based on the equipment operation stability evaluation result and the magnetic data of the conveyed rare earth, and finally analyzes the conveying state through the rare earth conveying efficiency evaluation result and the equipment operation abnormality evaluation result, thereby improving the accuracy of the matching analysis between rare earth particles and conveying components. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0050] Figure 1 Schematic diagram of the overall process of the method of the present invention;

[0051] Figure 2 This is a workflow diagram of step S2 in the method of the present invention;

[0052] Figure 3 This is a workflow diagram of step S3 in the method of the present invention;

[0053] Figure 4 Schematic diagram of the structure of the system of the present invention. DETAILED DESCRIPTION

[0054] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0055] Example 1

[0056] like Figure 1 、 Figure 2 and Figure 3 As shown, this embodiment provides a method for monitoring the intelligent transportation status of smelting rare earth, which specifically includes the following steps:

[0057] S1, obtaining rare earth particle image data, magnetic data of transported rare earth, and equipment operation data;

[0058] In this embodiment, obtaining rare earth particle image data, magnetic data of transported rare earth particles, and equipment operation data in step S1 includes the following specific steps:

[0059] S11. Acquire image data of the rare earth particles to be transported through an image acquisition terminal, separate the rare earth particles from the background image, and acquire contour data of the rare earth particles in the image. The specific steps are: use an optical microscope, a scanning electron microscope (SEM), or a laser confocal microscope to capture high-resolution images of the particles, perform preprocessing on the acquired images, including adjusting brightness and contrast, removing noise, and binarization, to clearly identify the contours of the particles, use a contour recognition algorithm in image analysis software (such as ImageJ, MATLAB, etc.) to detect the edges of the particles, and store the detected edges in a contour storage component.

[0060] S12, obtaining magnetic field size data of the rare earth to be transported through a magnetic data acquisition terminal, and storing the data in a magnetic field size storage component;

[0061] S13. Collecting equipment operation data through the equipment operation collection terminal, wherein the equipment operation data includes equipment control instruction execution data, conveying process vibration data, and equipment transmission component surface wear data, and storing the data in the equipment operation data storage component;

[0062] S2. evaluating the rare earth transport efficiency based on the rare earth particle image data and the smoothness of the transport components of the transport equipment;

[0063] In this embodiment, step S2 evaluates the rare earth transport efficiency based on the rare earth particle image data and the smoothness of the transport component of the transport device, including the following specific steps:

[0064] S21, obtaining rare earth particle profile data, analyzing the roundness of each rare earth particle based on the rare earth particle profile data, and obtaining the conveying difficulty based on the weighted sum of the average value and uniformity of the roundness of the rare earth particles; comprising the following specific steps:

[0065] S211, obtaining rare earth particle contour data, and analyzing the roundness of each rare earth particle based on the rare earth particle contour data, wherein the roundness calculation formula of the i-th rare earth particle is: , where Ai is the surface area of ​​the rare earth particles and Pi is the circumference of the rare earth particles. Here, the roundness of the rare earth particles is used to analyze whether the rare earth particles are prone to rolling off the conveying module during the conveying process, resulting in low conveying efficiency. In actual operation, the viscosity and roughness of the rare earth particles can also be comprehensively analyzed to determine whether the rare earth particles are prone to rolling off the conveying module.

[0066] S212. Calculate the average roundness of all rare earth particles based on the average roundness of the rare earth particles, and substitute the roundness of all rare earth particles into a uniformity calculation formula to obtain the uniformity of the rare earth particles. The uniformity can be the inverse of the calculated variance or standard deviation. The transportation difficulty is obtained by taking the weighted sum of the average roundness of the rare earth particles and the uniformity of the rare earth particles.

[0067] S22. Analyze the smoothness of the surface conveying component based on the wear data of the surface of the equipment transmission component. Obtain relative height data of each point on the surface of the equipment transmission component. Obtain the smoothness of the surface conveying component based on the inverse of the standard deviation of the relative height data of each point on the surface of the equipment transmission component. The smoother the surface of the conveying component, the easier it is for the rare earth particles to roll off the conveying module. Therefore, the smoothness of the surface conveying component and the conveying difficulty are used to comprehensively analyze the conveying efficiency of the conveying component.

[0068] S23, obtaining the conveying efficiency of the conveying component by taking the inverse of the weighted sum of the conveying difficulty and the smoothness of the surface conveying component;

[0069] S3. Evaluate equipment operation stability based on equipment control operation data;

[0070] In this embodiment, the device operation stability assessment is performed based on the control operation data of the device in step S3, including the following specific steps:

[0071] S31, extracting the equipment control instruction execution data of the conveying drive component during the test process, and simultaneously obtaining the vibration data of the surface conveying component during operation;

[0072] S32. Perform instruction execution fluctuation anomaly analysis based on the device control instruction execution data of the conveying drive component, wherein the instruction execution fluctuation anomaly analysis formula is: , where T is the test duration of the conveyor drive component, ft is the speed of the drive component after the speed control instruction at time t, ftm is the standard speed corresponding to the speed control instruction at time t, and dt is the time integral;

[0073] S33. Performing vibration anomaly analysis of the surface conveying assembly based on the vibration data of the surface conveying assembly during operation, wherein the vibration anomaly analysis of the surface conveying assembly is as follows: , where Nt is the average number of vibrations of the surface conveying assembly at time t, Djt is the vibration amplitude of the j-th vibration of the surface conveying assembly at time t, and Dm is the safe vibration amplitude of the surface conveying assembly;

[0074] S34. A weighted sum of the results of the instruction execution fluctuation anomaly analysis and the results of the surface conveying component vibration anomaly analysis is performed, and the inverse thereof is calculated to obtain an equipment operation stability assessment result. In this way, the equipment operation stability and the surface conveying component stability are used to analyze the equipment's transportation stability of rare earths during the transportation process.

[0075] S4. Evaluate equipment operation abnormalities during rare earth transportation based on equipment operation stability evaluation results and magnetic data of the transported rare earth;

[0076] In this embodiment, the evaluation of equipment operation abnormality during rare earth transportation based on the equipment operation stability evaluation result and the magnetic data of the transported rare earth in step S4 includes the following specific steps:

[0077] S41. Obtain magnetic data of the transported rare earth, and analyze electromagnetic interference anomalies based on the magnetic data of the transported rare earth. The electromagnetic interference anomaly calculation formula is: , where Hk is the magnetic field strength of the rare earth, and Hm is the safe value of the magnetic field strength for stable operation of the conveying equipment; rare earth permanent magnet materials (such as neodymium iron boron) have high magnetic permeability and remanence, and can generate a strong magnetic field in the motor. This strong magnetic field may cause electromagnetic interference (EMI) to nearby electronic equipment, affecting the normal operation of the equipment;

[0078] S42. The obtained electromagnetic interference anomaly and equipment operation stability evaluation results are used to evaluate the equipment operation anomaly during the transportation of rare earths. The evaluation formula for the equipment operation anomaly during the transportation of rare earths is: , where a is the instruction execution volatility factor, The electromagnetic interference factor is used to comprehensively evaluate equipment abnormalities during rare earth transportation by considering the negative impact of the rare earth magnetic field on equipment stability.

[0079] S5. Analyze the transportation status based on the rare earth transportation efficiency evaluation results and the equipment operation abnormality evaluation results;

[0080] In this embodiment, the transport status analysis is performed based on the rare earth transport efficiency evaluation results and the equipment operation abnormality evaluation results in step S5, including the following specific contents:

[0081] S51. Obtaining the analyzed equipment operation abnormality assessment results and the transport efficiency assessment results during the rare earth transport process;

[0082] S52, obtaining a transport status analysis value by normalizing the inverse of the equipment operation abnormality evaluation result obtained by analyzing the transport efficiency evaluation result during the transport of rare earths and performing weighted summation;

[0083] S6. Provide an early warning of abnormal transportation based on the transportation status analysis results;

[0084] In this embodiment, the abnormality warning of transportation is performed based on the transportation status analysis result in step S6, which includes the following specific steps:

[0085] S61, obtaining the estimated transport state analysis value during the transport process;

[0086] S62: Preset a conveying status analysis threshold. When the conveying status analysis value during the conveying process is greater than the conveying status analysis threshold, it indicates that the corresponding conveying equipment can normally convey the rare earths. If the conveying status analysis value during the conveying process is less than or equal to the conveying status analysis threshold, it indicates that the corresponding conveying equipment cannot normally convey the rare earths, and an early warning is issued to the staff, reminding them that maintenance or replacement of the conveying equipment is required.

[0087] It should be noted that the setting parameters (such as weights and thresholds) in this embodiment are obtained by experiments by those skilled in the art. The specific experimental method is: obtaining rare earth particle image data, magnetic data of transported rare earths, and equipment operation data from multiple historical rare earth transportation processes, and substituting them into each step in this embodiment to evaluate the transport status analysis value, and at the same time obtaining the judgment result of whether the historical transport efficiency meets the transport requirements, and importing the judgment result of whether the historical transport efficiency meets the transport requirements and the evaluation result of the transport status analysis value into the fitting software for continuous fitting to obtain the values ​​of the setting parameters (such as weights and thresholds) that meet the maximum contamination risk judgment accuracy.

[0088] It should be noted that this embodiment has the following benefits: evaluating the rare earth conveying efficiency based on the rare earth particle image data and the smooth state of the conveying component of the conveying equipment, evaluating the equipment operation stability based on the equipment control operation data, evaluating the equipment operation abnormality during the rare earth conveying process based on the equipment operation stability evaluation results and the magnetic data of the conveyed rare earth, analyzing the conveying status based on the rare earth conveying efficiency evaluation results and the equipment operation abnormality evaluation results, issuing a conveying abnormality warning based on the conveying status analysis results, analyzing the matching of rare earth particles and conveying components based on the characteristics of rare earth conveying, analyzing the conveying equipment abnormality under magnetic interference based on the equipment operation stability evaluation results and the magnetic data of the conveyed rare earth, and finally analyzing the conveying status based on the rare earth conveying efficiency evaluation results and the equipment operation abnormality evaluation results, thereby improving the accuracy of the matching analysis of rare earth particles and conveying components.

[0089] Example 2

[0090] like Figure 4 As shown, this embodiment provides a system for monitoring the status of an intelligent rare earth smelting conveyor, including:

[0091] A data acquisition module is used to obtain rare earth particle image data, magnetic data of transported rare earth, and equipment operation data;

[0092] A rare earth transport efficiency analysis module evaluates rare earth transport efficiency based on rare earth particle image data and the smoothness of the transport equipment's transport components;

[0093] Operation stability assessment module, which assesses equipment operation stability based on the equipment's control operation data;

[0094] Equipment operation abnormality assessment module, which assesses equipment operation abnormalities during rare earth transportation based on equipment operation stability assessment results and magnetic data of transported rare earths;

[0095] The transportation status analysis module analyzes the transportation status based on the rare earth transportation efficiency evaluation results and the equipment operation abnormality evaluation results;

[0096] The transportation abnormality warning module provides transportation abnormality warning based on the transportation status analysis results.

[0097] The above-mentioned parameters and steps for each unit module to achieve corresponding functions in the intelligent transportation status monitoring system for smelting rare earths of the present invention can refer to the parameters and steps in the embodiment of the intelligent transportation status monitoring method for smelting rare earths above, and will not be repeated here.

[0098] Example 3

[0099] An electronic device according to an embodiment of the present invention includes a processor and a memory. The memory stores a computer program that can be called by the processor. The processor executes a method for monitoring the intelligent transportation status of rare earth smelting by calling the computer program stored in the memory. It should be noted that all computer programs of the method for monitoring the intelligent transportation status of rare earth smelting are implemented in the C language.

[0100] Example 4

[0101] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0102] When the computer program is run on a computer device, the computer device is caused to execute the above-mentioned method for monitoring the intelligent transportation status of smelting rare earth.

[0103] The various embodiments of the present invention are described in a progressive manner. Similar portions between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the IoT device and medium embodiments are generally similar to the method embodiments, so their description is relatively simple. For relevant portions, refer to the description of the method embodiments.

[0104] The system and medium provided in the embodiments of the present invention correspond one-to-one to the method. Therefore, the system and medium also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0105] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0106] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0107] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0108] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0109] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0110] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology to store information. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0111] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0112] The above are merely embodiments of the present invention and are not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A method for monitoring the intelligent transportation status of rare earth smelting, characterized in that: The steps include: Step S1, acquiring rare earth particle image data, magnetic data of transported rare earth, and equipment operation data, wherein the magnetic data includes magnetic field intensity, magnetic permeability, and remanence; Step S2: evaluating the rare earth transport efficiency based on the rare earth particle image data and the smoothness of the transport component of the transport equipment; Step S3: Evaluate the equipment operation stability based on the equipment control operation data; Step S4: evaluating equipment operation abnormality during rare earth transportation based on the equipment operation stability evaluation result and the magnetic data of the transported rare earth; Step S5: analyzing the transport status based on the rare earth transport efficiency evaluation results and the equipment operation abnormality evaluation results; Step S6: issuing a warning of abnormal transportation based on the transportation status analysis result.

2. The method for monitoring the intelligent transportation status of smelting rare earth according to claim 1, characterized in that: The step S2 includes evaluating the rare earth transport efficiency based on the rare earth particle image data and the smoothness of the transport component of the transport device, and includes the following specific steps: S21. Obtaining rare earth particle profile data, analyzing the roundness of each rare earth particle based on the rare earth particle profile data, and obtaining a conveying difficulty based on a weighted sum of an average value and a uniformity of the roundness of the rare earth particles; S22. Analyzing the smoothness of the surface conveying component based on the wear data of the surface of the equipment conveying component, obtaining relative height data of each point on the surface of the equipment conveying component, and obtaining the smoothness of the surface conveying component based on the inverse of the standard deviation of the relative height data of each point on the surface of the equipment conveying component; S23. Obtain the conveying efficiency of the conveying component by taking the inverse of the weighted sum of the conveying difficulty and the smoothness of the surface conveying component.

3. The method for monitoring the intelligent transportation status of smelting rare earth according to claim 2, characterized in that: In step S3, the device operation stability assessment is performed based on the control operation data of the device, including the following specific steps: S31, extracting the equipment control instruction execution data of the conveying drive component during the test process, and simultaneously obtaining the vibration data of the surface conveying component during operation; S32. Performing instruction execution fluctuation anomaly analysis based on the equipment control instruction execution data of the conveying drive component; S33, performing vibration abnormality analysis of the surface conveying assembly based on the vibration data of the surface conveying assembly during operation; S34. Obtain the equipment operation stability evaluation result by performing a weighted summation of the instruction execution fluctuation anomaly analysis result and the surface conveying component vibration anomaly analysis result and then calculating the inverse thereof.

4. The method for monitoring the intelligent transportation status of smelting rare earth according to claim 3, characterized in that: The step S4 of evaluating the abnormal operation of the equipment during the transportation of rare earth based on the equipment operation stability evaluation result and the magnetic data of the transported rare earth includes the following specific steps: S41. Acquire magnetic data of the transported rare earth, and analyze electromagnetic interference anomalies based on the magnetic data of the transported rare earth; S42. Obtain the obtained electromagnetic interference anomaly and equipment operation stability assessment results to conduct equipment operation anomaly assessment during the rare earth transportation process.

5. The method for monitoring the intelligent transportation status of smelting rare earth according to claim 4, characterized in that: In step S5, the transportation status analysis is performed based on the rare earth transportation efficiency evaluation results and the equipment operation abnormality evaluation results, including the following specific contents: S51. Obtaining the analyzed equipment operation abnormality assessment results and the transport efficiency assessment results during the rare earth transport process; S52. The inverse of the equipment operation abnormality evaluation result obtained through analysis during the transportation of rare earths and the transportation efficiency evaluation result are normalized and then weighted summed to obtain a transportation status analysis value.

6. The method for monitoring the intelligent transportation status of smelting rare earth according to claim 5, characterized in that: In step S6, an abnormality warning of transportation is performed based on the transportation status analysis result, including the following specific steps: S61, obtaining the estimated transport state analysis value during the transport process; S62. Preset a conveying status analysis threshold. When the conveying status analysis value during the conveying process is greater than the conveying status analysis threshold, it means that the corresponding conveying equipment can normally convey the rare earths. If the conveying status analysis value during the conveying process is less than or equal to the conveying status analysis threshold, it means that the corresponding conveying equipment cannot normally convey the rare earths, and an early warning is issued to the staff, reminding them that the conveying equipment needs to be maintained or replaced.

7. The method for monitoring the intelligent transportation status of smelting rare earth according to claim 6, characterized in that: The method for obtaining the delivery difficulty in step S21 includes the following specific steps: S211, obtaining rare earth particle contour data, and analyzing the roundness of each rare earth particle based on the rare earth particle contour data; S212. The average roundness value of the rare earth particles is obtained based on the average roundness of all rare earth particles. The roundness value of all rare earth particles is substituted into the uniformity calculation formula to obtain the uniformity of the rare earth particles. The transportation difficulty is obtained by weighted summing the average roundness value of the rare earth particles and the uniformity of the rare earth particles.

8. The method for monitoring the intelligent transportation status of smelting rare earth according to claim 7, characterized in that: Acquiring rare earth particle image data, magnetic data of transported rare earth particles, and equipment operation data in step S1 includes the following specific steps: S11, acquiring image data of the rare earth particles to be transported through the image acquisition terminal, separating the rare earth particles from the background image to obtain contour data of the rare earth particles in the image, and storing the data in the contour storage component; S12, obtaining magnetic field size data of the rare earth to be transported through a magnetic data acquisition terminal, and storing the data in a magnetic field size storage component; S13. Collecting equipment operation data through the equipment operation collection terminal, wherein the equipment operation data includes equipment control instruction execution data, conveying process vibration data and equipment transmission component surface wear data, and storing the data in the equipment operation data storage component.

9. A system for monitoring the state of intelligent transportation of smelting rare earths, which is implemented based on the method for monitoring the state of intelligent transportation of smelting rare earths according to any one of claims 1 to 8, characterized in that: The system comprises: A data acquisition module is used to obtain rare earth particle image data, magnetic data of transported rare earth, and equipment operation data; A rare earth transport efficiency analysis module evaluates rare earth transport efficiency based on rare earth particle image data and the smoothness of the transport equipment's transport components; Operation stability assessment module, which assesses equipment operation stability based on the equipment's control operation data; Equipment operation abnormality assessment module, which assesses equipment operation abnormalities during rare earth transportation based on equipment operation stability assessment results and magnetic data of transported rare earths; The transportation status analysis module performs transportation status analysis based on the rare earth transportation efficiency evaluation results and equipment operation abnormality evaluation results; The transportation abnormality warning module provides transportation abnormality warning based on the transportation status analysis results.

10. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes the method for monitoring the intelligent transportation status of smelting rare earths as described in any one of claims 1 to 8 by calling the computer program stored in the memory.

Images