Frequency conversion control method for dust removal fan and related equipment

Abstract

The invention discloses a dust removal fan frequency conversion control method and related equipment, and relates to the technical field of video control. The method comprises the steps that a training data set is generated based on historical video data of an iron notch area in the blast furnace tapping process; constructing an initial artificial intelligence model, and training the initial artificial intelligence model by adopting the training data set to obtain a target artificial intelligence model representing a mapping relationship among the dust concentration, the spark intensity and the fan frequency; based on the target artificial intelligence model and the current dust concentration feature and the current spark intensity feature in the current video data, the target fan frequency of the current tapping stage is determined; and generating a control signal based on the target fan frequency so as to adjust the operation frequency of the dust removal fan frequency converter through the control signal.

Description

Technical Field

[0001] The present application relates to the field of video control technology, and in particular to a dust removal fan variable frequency control method and related equipment. Background Art

[0002] "Green, low-carbon, energy-saving and consumption-reducing" is the long-term development goal and direction of industrial enterprises. Dust removal fans are the main energy-consuming and environmentally friendly equipment in smelting enterprises. How to save energy and reduce consumption while ensuring environmental protection is a research topic for every enterprise, especially at the iron outlet in front of the blast furnace. The molten iron temperature is as high as 1500℃, and the amount of dust varies from time to time. Conventional detection equipment cannot be used to detect the dust size and the operation process of the tapping machine and mud gun to adjust the operating frequency of the dust removal fan inverter. Currently, it can only be adjusted manually by the operator.

[0003] Therefore, how to automatically adjust the operating frequency of the dust removal fan inverter without relying on manual operation has become a technical problem that needs to be solved urgently. Summary of the Invention

[0004] The Summary of the Invention introduces a series of simplified concepts that will be further described in the Detailed Description of the Invention. The Summary of the Invention of this application is not intended to limit the key features and essential technical features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0005] This application specifically includes the following aspects:

[0006] In a first aspect, the present application proposes a variable frequency control method for a dust removal fan, comprising:

[0007] Generate a training data set based on historical video data of the tapping area during the blast furnace tapping process, wherein the historical video data includes historical dust concentration characteristics and historical spark intensity characteristics corresponding to different tapping stages;

[0008] Constructing an initial artificial intelligence model and training the initial artificial intelligence model using the training data set to obtain a target artificial intelligence model that characterizes the mapping relationship between dust concentration, spark intensity, and fan frequency;

[0009] Determining a target fan frequency for the current tapping stage based on the target artificial intelligence model, current dust concentration characteristics, and current spark intensity characteristics in the current video data;

[0010] A control signal is generated based on the target fan frequency, so as to adjust the operating frequency of the dust removal fan inverter through the control signal.

[0011] In a feasible implementation, determining the target fan frequency of the current tapping stage based on the target artificial intelligence model, the current dust concentration characteristics and the current spark intensity characteristics in the current video data includes:

[0012] Determining the current tapping stage based on the current dust concentration characteristic and the current spark intensity characteristic; wherein the current tapping stage includes one of a tapping preparation stage, a tapping early stage, a tapping mid-stage, a tapping late stage, a tapping plugging stage, and a tapping end stage;

[0013] determining a current dust concentration according to the current dust concentration characteristic;

[0014] According to the current iron tapping stage and the current dust concentration, the corresponding target fan frequency is matched from the target artificial intelligence model.

[0015] In a feasible implementation manner, when the current tapping stage is the tapping preparation stage, the target fan frequency is greater than the current fan frequency;

[0016] When the current iron-tapping stage is the middle iron-tapping stage, the target fan frequency is less than the current fan frequency;

[0017] When the current iron tapping stage is the iron mouth blocking stage, the target fan frequency is the first safety frequency of the dust removal fan inverter.

[0018] In a feasible implementation manner, the dust removal fan variable frequency control method further includes:

[0019] In the event of abnormal operating conditions, the first safety frequency of the dust removal fan inverter is increased to the second safety frequency, and the frequency is reduced to the first safety frequency again after the abnormal operating conditions are recovered; wherein, the abnormal operating conditions include secondary iron mouth opening, iron mouth washing during iron tapping, and iron tapping from one iron mouth while the other iron mouth is under maintenance.

[0020] In a feasible implementation manner, the dust removal fan variable frequency control method further includes:

[0021] When it is detected that the dust concentration in the current iron-tapping stage or the adjusted operating frequency does not meet the preset rules, an alarm signal is triggered and sent to the operation terminal.

[0022] In a feasible implementation manner, the preset rules include:

[0023] The dust concentration in the current iron-tapping stage exceeds the standard for a duration exceeding a first preset value, or the adjusted operating frequency still cannot reduce the dust concentration in the current iron-tapping stage to a preset concentration.

[0024] In a feasible implementation, the initial artificial intelligence model is a visual detection model based on a single detection algorithm.

[0025] In a second aspect, the present application proposes a dust removal fan variable frequency control system, which is applied to the dust removal fan variable frequency control method described in any one of the above embodiments, including:

[0026] A data acquisition module is used to generate a training data set based on historical video data of the tapping area during the blast furnace tapping process, wherein the historical video data includes historical dust concentration characteristics and historical spark intensity characteristics corresponding to different tapping stages;

[0027] a model training module, configured to construct an initial artificial intelligence model and train the initial artificial intelligence model using the training data set to obtain a target artificial intelligence model that characterizes the mapping relationship between dust concentration, spark intensity, and fan frequency;

[0028] a frequency acquisition module for determining a target fan frequency for the current tapping stage based on the target artificial intelligence model, current dust concentration characteristics, and current spark intensity characteristics in the current video data;

[0029] The frequency adjustment module is used to generate a control signal based on the target fan frequency, so as to adjust the operating frequency of the dust removal fan inverter through the control signal.

[0030] In a third aspect, an electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the steps of any one of the dust removal fan variable frequency control methods of the first aspect when executing the computer program stored in the memory.

[0031] In a fourth aspect, the present application further proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the dust removal fan variable frequency control methods of the first aspect.

[0032] In summary, the scene data set generation method proposed in this application monitors the taphole process from a distance, collects, analyzes, and processes image information under high temperature and high dust conditions. This allows the results of dust analysis at multiple stages of the taphole process, including preparation for taphole opening, early taphole, mid-tapping, late taphole, taphole blocking, and taphole completion, to be digitized. Signals are then output through an intelligent controller to control the frequency of the dust removal fan inverter, achieving both environmental protection and energy conservation. At the same time, in terms of video image processing, auxiliary analysis is performed in conjunction with data such as the taphole machine's mud gun pressure to obtain the taphole scene and the taphole machine and mud gun's motion processes. The intelligent controller transmits the signals via the network to the programmable logic controller, which then adjusts the inverter frequency.

[0033] The scene dataset generation method proposed in this application, and other advantages, objectives and features of this application will be reflected in part through the following description, and in part will also be understood by technical personnel in this field through research and practice of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present description. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0035] Figure 1 A schematic diagram of a process flow of a variable frequency control method for a dust removal fan provided in an embodiment of the present application;

[0036] Figure 2 A schematic diagram of camera installation positions and angles provided in an embodiment of the present application;

[0037] Figure 3 A schematic diagram of the increase in dust concentration during the tap hole opening stage provided in an embodiment of the present application;

[0038] Figure 4 A temperature and dust dynamic analysis diagram of the taphole process provided in an embodiment of the present application;

[0039] Figure 5 A schematic diagram of dust reduction and stabilization during the first stage of iron tapping provided in an embodiment of the present application;

[0040] Figure 6 A schematic diagram of dust reduction and stabilization during the second stage of iron tapping provided in an embodiment of the present application;

[0041] Figure 7 A schematic diagram of the increase in dust concentration during secondary tapping in a scenario provided by an embodiment of the present application;

[0042] Figure 8 A schematic diagram of increased dust concentration during secondary tapping in another scenario provided by an embodiment of the present application;

[0043] Figure 9 A schematic diagram of dust increasing again in the later stage of iron tapping in the first stage provided in the embodiment of the present application;

[0044] Figure 10 A schematic diagram showing dust increasing again in the later stage of iron tapping in the second stage provided in an embodiment of the present application;

[0045] Figure 11 A schematic diagram showing the gradual reduction of dust during the initial plugging process provided in an embodiment of the present application;

[0046] Figure 12 This is a schematic diagram of the embodiment of the present application providing a final stage in which the plugging is completed and the dust is reduced to a minimum;

[0047] Figure 13 A schematic diagram of the functional modules of a dust removal fan variable frequency control system provided in an embodiment of the present application;

[0048] Figure 14 A schematic diagram of the structure of an electronic device for variable frequency control of a dust removal fan provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to better understand the technical solutions provided by the embodiments of this specification, the technical solutions of the embodiments of this specification are described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of this specification and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this specification, rather than limitations on the technical solutions of this specification. In the absence of conflict, the embodiments of this specification and the technical features in the embodiments can be combined with each other.

[0050] In this article, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also include elements inherent to such process, method, article or equipment. In the absence of further restrictions, the elements defined by the statement "comprising a ..." do not exclude the presence of other identical elements in the process, method, article or equipment comprising the elements. The term "two or more" includes two or more than two cases.

[0051] See also Figure 1, which is a flow chart of a variable frequency control method for a dust removal fan provided in an embodiment of the present application, which may specifically include:

[0052] S110. Generate a training data set based on historical video data of the tapping area during the blast furnace tapping process, wherein the historical video data includes historical dust concentration characteristics and historical spark intensity characteristics corresponding to different tapping stages.

[0053] For example, in the high-temperature, high-dust casthouse area, high-definition, high-frequency cameras are installed at appropriate locations and angles to collect historical video data of dust, smoke, and sparks in the taphole area, ensuring diversity and representativeness. This historical video data includes samples of characteristics from multiple stages, including taphole preparation, early tapping, mid-tapping, late tapping, taphole plugging, and the end of tapping. By classifying and labeling these samples, a comprehensive training dataset is constructed.

[0054] S120. Construct an initial artificial intelligence model, and use the training data set to train the initial artificial intelligence model to obtain a target artificial intelligence model that characterizes the mapping relationship between dust concentration, spark intensity and fan frequency.

[0055] For example, to ensure the quality and consistency of the training dataset, the collected training dataset is preprocessed based on the dust concentration and spark intensity detected at different stages of iron tapping. Specifically, the model parameters of the initial AI model are adjusted to minimize the loss function, and the training dataset is cleaned, enhanced, and annotated to make it more suitable for training the initial AI model.

[0056] Furthermore, based on the specific requirements of the initial AI model, appropriate network structures and parameters are configured to ensure that the initial AI model achieves ideal performance on the test data. The initial AI model is then trained using the preprocessed training dataset. During this process, hyperparameters (such as the learning rate (the step size for each parameter update in the optimization algorithm) and batch size (the number of samples fed into the model during each training session) are adjusted to optimize the accuracy and speed of data detection.

[0057] To improve training efficiency, hardware devices such as graphics processing units (GPUs) are used to accelerate the training process. Regarding the selection of visual inspection models, a real-time object detection algorithm (you Only LookOnce version 8, YOLOv8) or other suitable models will be used to build a target AI model that characterizes the mapping relationship between dust concentration, spark intensity, and fan frequency.

[0058] S130. Determine the target fan frequency of the current iron-making stage based on the target artificial intelligence model, the current dust concentration characteristics and the current spark intensity characteristics in the current video data.

[0059] Exemplarily, based on a preset dynamic relationship curve (including dust concentration-target fan frequency, spark intensity-target fan frequency), multiple key inflection points are calibrated on the preset dynamic relationship curve, and the minimum safe frequency threshold (such as 30Hz) is set as the lower limit of the frequency of the dust removal fan inverter. The target artificial intelligence model converts the inflection point into a frequency adjustment instruction by fusing the preset dynamic relationship curve with the frequency compensation parameters generated in real time, and transmits it to the programmable logic controller to realize automatic control of the dust removal fan inverter. At the same time, the changes in the current dust concentration characteristics are monitored in real time. If the actual dust concentration data deviates from the predicted value of the target artificial intelligence model, the deviation information is automatically recorded and the target fan frequency compensation parameters are dynamically corrected for the target fan frequency optimization compensation when the iron mouth is subsequently opened.

[0060] S140. Generate a control signal based on the target fan frequency, so as to adjust the operating frequency of the dust removal fan inverter through the control signal.

[0061] For example, based on the target fan frequency, the control system generates an adaptive control signal, which is transmitted to the dust removal fan inverter. Upon receiving the signal, the dust removal fan inverter precisely adjusts the operating frequency as indicated by the signal, dynamically regulating the dust removal fan's speed and air volume, effectively controlling dust removal efficiency and energy consumption.

[0062] In some examples, determining a target fan frequency for a current tapping stage based on the target artificial intelligence model, a current dust concentration characteristic, and a current spark intensity characteristic in current video data includes:

[0063] Determining the current tapping stage based on the current dust concentration characteristic and the current spark intensity characteristic; wherein the current tapping stage includes one of a tapping preparation stage, a tapping early stage, a tapping mid-stage, a tapping late stage, a tapping plugging stage, and a tapping end stage;

[0064] determining a current dust concentration according to the current dust concentration characteristic;

[0065] According to the current iron tapping stage and the current dust concentration, the corresponding target fan frequency is matched from the target artificial intelligence model.

[0066] Exemplarily, based on the current dust concentration characteristics (such as dust diffusion range and density distribution) and the current spark intensity characteristics (such as spark brightness and duration), a multi-dimensional analysis is performed through the target artificial intelligence model to determine that the current iron-tapping stage is one of the following six: the iron-mouth preparation stage, the iron-tapping early stage, the iron-tapping mid-stage, the iron-tapping late stage, the iron-mouth blocking stage or the iron-tapping end stage.

[0067] Specifically, based on the visible light blocking rate, motion trajectory and spatial distribution of the dust in the current video data, the current dust concentration level (such as high, medium, and low) is calculated and compared with the dust concentration threshold range preset in the target artificial intelligence model. Based on the current iron-making stage (such as the mid-stage of iron-making) and the current dust concentration level, the pre-trained dynamic relationship curve (dust concentration-fan frequency) is retrieved from the target artificial intelligence model to match the corresponding target fan frequency. For example: if the current stage is the stage of preparing to open the iron mouth and the dust concentration level is high, the target fan frequency is the preset frequency increase value (such as increased to 48Hz); if the current stage is the mid-stage of iron-making and the dust concentration level is stable at medium, the target fan frequency is the preset frequency reduction value (such as adjusted to 40Hz).

[0068] Furthermore, when there is a deviation between the actual exhaust dust data and the target fan frequency output by the target artificial intelligence model, the dynamic correction mechanism of the frequency compensation parameters is triggered, and the operating instructions of the dust removal fan inverter are updated through the programmable logic controller to ensure real-time matching of the target fan frequency and dust concentration.

[0069] In some examples, the dust removal fan variable frequency control method further includes:

[0070] When the current tapping stage is the tap hole preparation stage, the target fan frequency is greater than the current fan frequency;

[0071] When the current iron-tapping stage is the middle iron-tapping stage, the target fan frequency is less than the current fan frequency;

[0072] When the current iron tapping stage is the iron mouth blocking stage, the target fan frequency is the first safety frequency of the dust removal fan inverter.

[0073] For example, during the iron-tapping stage, the dust concentration rises sharply, and the target fan frequency needs to be increased to cope with the increased dust; during the mid-iron-tapping stage, the dust concentration tends to be stable, and the target fan frequency can be appropriately lowered to save energy; during the iron-mouth blocking stage, the dust concentration gradually decreases, and the target fan frequency is gradually lowered to the lowest safe frequency, such as 30Hz (i.e., the first safe frequency).

[0074] In some examples, the dust removal fan variable frequency control method further includes:

[0075] In the event of abnormal operating conditions, the first safety frequency of the dust removal fan inverter is increased to the second safety frequency, and the frequency is reduced to the first safety frequency again after the abnormal operating conditions are recovered; wherein, the abnormal operating conditions include secondary iron mouth opening, iron mouth washing during iron tapping, and iron tapping from one iron mouth while the other iron mouth is under maintenance.

[0076] Exemplarily, when an abnormal operating condition is detected, the operating frequency of the dust removal fan inverter is increased from a first safety frequency to a second safety frequency, and automatically restored to the first safety frequency after the abnormal operating condition is resolved; wherein, the abnormal operating condition includes at least one of the following situations: secondary iron mouth opening, that is, the same iron mouth needs to be opened repeatedly due to opening irregularities; iron mouth washing during iron tapping, that is, the iron mouth area needs to be cleaned due to slag; multi-iron mouth coordinated abnormality, that is, one iron mouth is in the iron tapping state and the other iron mouth is undergoing maintenance operations simultaneously.

[0077] Specifically, when the target artificial intelligence model identifies abnormal working conditions (such as a sudden increase in dust during the secondary opening of the iron mouth, or abnormal mechanical movements during the iron mouth washing process), it immediately triggers a frequency upgrade instruction; the second safety frequency is set based on the dust peak value of the abnormal working condition to ensure that the dust removal capacity covers the worst working condition requirements. Real-time video data is used to verify whether the abnormal working condition has been resolved (such as the iron mouth is fully opened, or the iron mouth washing operation is completed); if the dust concentration falls back to the normal range and the equipment movement meets the characteristics of the standard stage, the programmable logic controller is used to gradually reduce the frequency to the first safety frequency. In the scenario of multi-iron mouth coordinated abnormality, the intelligent controller dynamically allocates frequency resources according to the global dust concentration distribution, giving priority to the dust removal needs of the iron mouth, and the fan of the maintenance iron mouth maintains the lowest safe frequency.

[0078] In some examples, the dust removal fan variable frequency control method further includes:

[0079] When it is detected that the dust concentration in the current iron-tapping stage or the adjusted operating frequency does not meet the preset rules, an alarm signal is triggered and sent to the operation terminal.

[0080] In some examples, the preset rules include:

[0081] The dust concentration in the current iron-tapping stage exceeds the standard for a duration exceeding a first preset value, or the adjusted operating frequency still cannot reduce the dust concentration in the current iron-tapping stage to a preset concentration.

[0082] For example, if the dust concentration in the current tapping stage or the adjusted operating frequency does not meet preset rules, an alarm signal is triggered and simultaneously pushed to the operator terminal. Operators can remotely review the alarm information and choose to manually adjust the target frequency, activate emergency control mode, or notify on-site processing, forming a complete closed-loop control system. Preset rules support flexible configuration, such as continuous exceeding duration thresholds or instantaneous peak thresholds, to ensure energy conservation goals are achieved while ensuring production safety.

[0083] In some examples, the initial artificial intelligence model is a visual detection model based on a single detection algorithm.

[0084] For example, the initial AI visual inspection model based on a single-shot detection algorithm has significant advantages. It features fast detection speed, capable of identifying a large number of targets in a short period of time, meeting the requirements of real-time scenarios. Its relatively simple structure reduces computational complexity and resource consumption, making it easy to deploy. It also boasts high training and inference efficiency, enabling rapid processing of images or video streams. It also possesses a certain degree of generalization capability, adapting to diverse environments and target changes, laying a solid foundation for subsequent model optimization.

[0085] The technical solution of this application is further described in detail below through specific embodiments.

[0086] A camera is installed at a suitable position and angle on the closed wall opposite the iron mouth, and the camera video is moved to the control center and the dust removal operation room respectively, so that the blast furnace operator and the dust removal system operator can observe the iron tapping condition in front of the furnace. Figure 2 .

[0087] Video collection is performed based on the key parts of the process and equipment (such as the tapping machine body, iron mouth, tapping machine drill rod sleeve, tapping machine drill rod). Specifically, the tapping machine is the tapping equipment, and the mud gun machine is the tapping equipment. The tapping machine stays in the low-temperature waiting area before the tapping is opened, and the mud gun machine stays in the low-temperature waiting area before blocking the tapping. When opening the tapping, the tapping machine rotates to the tapping, and then the drill rod sleeve carries the drill rod forward, vibrating while moving forward. At this time, the intelligent controller outputs a signal to prepare for tapping until the tapping is opened. In this process, the video characteristics of the tapping machine body, drill rod sleeve, and drill rod movement, as well as the pressure characteristics of the tapping machine and mud gun are analyzed, and the video artificial intelligence controller outputs a signal to prepare for tapping. From the beginning of tapping, the dust concentration and the surrounding temperature will rise sharply. Figure 3 、 Figure 4 As shown, when preparing to open the iron mouth, the video artificial intelligence controller uses the video model and artificial intelligence analysis to output a signal in advance to prepare for opening the iron mouth to the programmable logic controller, which increases the frequency of the inverter, increases the air volume, and controls dust suppression according to the instruction output.

[0088] After the taphole is opened, the dust gradually decreases over a period of time and then gradually stabilizes. Figure 5 、 Figure 6 When the video artificial intelligence controller detects that the dust has been reduced and stabilized, it will output an intermediate tapping signal after analysis. The intermediate tapping signal is output to the frequency converter through the programmable logic controller for frequency reduction operation. However, if the tapping is not smooth at the first time and the tapping is too small, a second tapping is required. During the second tapping, dust will increase, and the frequency converter frequency will be increased again. Figure 7 、 Figure 8 .

[0089] At the end of tapping, or when the furnace condition is bad, the amount of dust will increase again. When the intelligent controller detects that the dust is getting bigger, Figure 9 、 Figure 10 , the output signal is sent to the programmable logic controller to adjust the frequency of the inverter.

[0090] After the iron is tapped, the plugging machine will plug the iron. As the plugging progresses, the dust gradually decreases until the dust reaches the lowest level. The iron tapping completion signal is output. Figure 11 、 Figure 12 .

[0091] According to the video artificial intelligence model and combined with the on-site process conditions, the opening signal and the blocking signal are analyzed and judged to solve the problem that the electrical monitoring equipment detection signal cannot be installed in the iron mouth area; the opening signal and the blocking signal can be transmitted through the network to the Inno-Buffalo granulation and dehydration system, the automatic traction and positioning system of the molten iron tank, and other systems, truly realizing the automatic control and intelligent control of the furnace equipment.

[0092] It should be noted that the above embodiments are only the best examples and are not intended to limit the implementation of the present application.

[0093] Furthermore, the present application also proposes a dust removal fan variable frequency control system, which is applied to any of the above embodiments of the dust removal fan variable frequency control method, specifically as follows: Figure 13 As shown in FIG, this application proposes a functional module diagram of a dust removal fan variable frequency control system, including:

[0094] A data acquisition module 21 is configured to generate a training data set based on historical video data of the tapping area during the blast furnace tapping process, wherein the historical video data includes historical dust concentration characteristics and historical spark intensity characteristics corresponding to different tapping stages;

[0095] A model training module 22 is used to construct an initial artificial intelligence model and train the initial artificial intelligence model using the training data set to obtain a target artificial intelligence model that characterizes the mapping relationship between dust concentration, spark intensity, and fan frequency;

[0096] a frequency acquisition module 23 for determining a target fan frequency for the current tapping stage based on the target artificial intelligence model, current dust concentration characteristics and current spark intensity characteristics in the current video data;

[0097] The frequency adjustment module 24 is configured to generate a control signal based on the target fan frequency, so as to adjust the operating frequency of the dust removal fan inverter through the control signal.

[0098] like Figure 14 As shown, an embodiment of the present application also provides an electronic device 300, including a processor 310, a memory 320, and a computer program 321 stored in the memory 320 and executable on the processor. When the processor 310 executes the computer program 321, the steps of any of the above-mentioned dust removal fan variable frequency control methods are implemented.

[0099] Since the electronic device introduced in this embodiment is a device used to implement a variable frequency control method for a dust removal fan in the embodiment of this application, based on the method introduced in the embodiment of this application, technical personnel in this field can understand the specific implementation method of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of this application will not be introduced in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of this application falls within the scope of protection of this application.

[0100] In the specific implementation process, the computer program 321 can be implemented when executed by the processor Figure 1 Any implementation manner in the corresponding embodiments.

[0101] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0102] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-readable program code.

[0103] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, 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 computer, 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 flowchart and / or block diagram. 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.

[0104] 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.

[0105] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0106] An embodiment of the present application further provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device executes the process of the dust removal fan variable frequency control method.

[0107] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)).

[0108] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0110] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0111] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0112] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0113] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

[0114] Although the preferred embodiments of this specification have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of this specification.

[0115] Obviously, those skilled in the art may make various changes and modifications to this specification without departing from the spirit and scope of this specification. Thus, if such changes and modifications fall within the scope of the claims of this specification and their equivalents, this specification is intended to include such changes and modifications.

Claims

1. A dust removal fan frequency conversion control method, characterized in that: include: Generate a training data set based on historical video data of the tapping area during the blast furnace tapping process, wherein the historical video data includes historical dust concentration characteristics and historical spark intensity characteristics corresponding to different tapping stages; Constructing an initial artificial intelligence model and training the initial artificial intelligence model using the training data set to obtain a target artificial intelligence model that characterizes the mapping relationship between dust concentration, spark intensity, and fan frequency; Determining a target fan frequency for the current tapping stage based on the target artificial intelligence model, current dust concentration characteristics, and current spark intensity characteristics in the current video data; A control signal is generated based on the target fan frequency, so as to adjust the operating frequency of the dust removal fan inverter through the control signal.

2. The dust removal fan frequency conversion control method according to claim 1, characterized in that: The determining of the target fan frequency of the current tapping stage based on the target artificial intelligence model, the current dust concentration characteristics and the current spark intensity characteristics in the current video data includes: Determining the current tapping stage based on the current dust concentration characteristic and the current spark intensity characteristic; wherein the current tapping stage includes one of a tapping preparation stage, a tapping early stage, a tapping mid-stage, a tapping late stage, a tapping plugging stage, and a tapping end stage; determining a current dust concentration according to the current dust concentration characteristic; According to the current iron tapping stage and the current dust concentration, the corresponding target fan frequency is matched from the target artificial intelligence model.

3. The dust removal fan frequency conversion control method according to claim 2, characterized in that: include: When the current tapping stage is the tap hole preparation stage, the target fan frequency is greater than the current fan frequency; When the current iron-tapping stage is the middle iron-tapping stage, the target fan frequency is less than the current fan frequency; When the current iron tapping stage is the iron mouth blocking stage, the target fan frequency is the first safety frequency of the dust removal fan inverter.

4. The dust removal fan frequency conversion control method according to claim 3, characterized in that: Also includes: In the event of abnormal operating conditions, the first safety frequency of the dust removal fan inverter is increased to the second safety frequency, and the frequency is reduced to the first safety frequency again after the abnormal operating conditions are recovered; wherein, the abnormal operating conditions include secondary iron mouth opening, iron mouth washing during iron tapping, and iron tapping from one iron mouth while the other iron mouth is under maintenance.

5. The dust removal fan frequency conversion control method according to claim 1, characterized in that: Also includes: When it is detected that the dust concentration in the current iron-tapping stage or the adjusted operating frequency does not meet the preset rules, an alarm signal is triggered and sent to the operation terminal.

6. The dust removal fan frequency conversion control method according to claim 5, characterized in that: The preset rules include: The dust concentration in the current iron-tapping stage exceeds the standard for a duration exceeding a first preset value, or the adjusted operating frequency still cannot reduce the dust concentration in the current iron-tapping stage to a preset concentration.

7. The dust removal fan variable frequency control method according to claim 1, characterized in that: The initial artificial intelligence model is a visual detection model based on a single detection algorithm.

8. A dust removal fan variable frequency control system, applied to the dust removal fan variable frequency control method according to any one of claims 1 to 7, characterized in that: include: A data acquisition module is used to generate a training data set based on historical video data of the tapping area during the blast furnace tapping process, wherein the historical video data includes historical dust concentration characteristics and historical spark intensity characteristics corresponding to different tapping stages; a model training module, configured to construct an initial artificial intelligence model and train the initial artificial intelligence model using the training data set to obtain a target artificial intelligence model that characterizes the mapping relationship between dust concentration, spark intensity, and fan frequency; a frequency acquisition module for determining a target fan frequency for the current tapping stage based on the target artificial intelligence model, current dust concentration characteristics, and current spark intensity characteristics in the current video data; The frequency adjustment module is used to generate a control signal based on the target fan frequency, so as to adjust the operating frequency of the dust removal fan inverter through the control signal.

9. An electronic device comprising: A memory and a processor, characterized in that the processor is used to implement the steps of the dust removal fan variable frequency control method according to any one of claims 1 to 7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the dust removal fan variable frequency control method according to any one of claims 1 to 7 are implemented.

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