Electric furnace zinc extraction control method and system for recycling domestic waste

Abstract

The present application relates to a method and system for controlling zinc extraction from an electric furnace for recycling domestic waste, the method comprising obtaining monitoring data of a steel rolling sensor, obtaining abnormal data of a steel rolling production line according to the monitoring data of the steel rolling sensor; analyzing the abnormal data of the steel rolling production line to obtain abnormal corresponding information of the steel rolling production line; obtaining corresponding control information of the steel rolling production line based on the abnormal corresponding information of the steel rolling production line; and adjusting the operating parameters of the steel rolling production line based on the corresponding control information of the steel rolling production line. The present application has the effect of improving the control effect of the scrap rate of the steel rolling production line and reducing the scrap rate of the steel rolling production line.

Description

Technical Field

[0001] The invention relates to the technical field of steel rolling production line control, and in particular to a method and system for controlling zinc extraction from an electric furnace for recycling domestic waste. Background Art

[0002] At present, with the continuous progress of the steel industry, the steel rolling production line, as its core link, has received increasing attention from the industry for its technological innovation and upgrading. At present, the technological development of the steel rolling production line is mainly focused on improving rolling efficiency, optimizing equipment performance and enhancing production line stability. The continuous evolution of these technologies has not only improved the speed and quality of steel rolling production, but also brought significant economic benefits and market competitiveness to steel companies.

[0003] At the same time, in order to improve the efficiency of energy recycling, the iron-containing waste in domestic waste will be re-refined to obtain the required rolled steel during the production of rolled steel. In this process, the iron-containing waste needs to be subjected to the step of zinc extraction through an electric furnace to meet the quality of the produced rolled steel. However, in the actual production process, the existing rolled steel production line still faces some challenges. For example, although the rolling speed has been greatly improved, if the rolled steel quality cannot be improved synchronously and the scrap steel rate of the rolled steel production line is not controlled, the rolling efficiency will be reduced. Therefore, how to effectively transform and optimize the rolled steel production line to control the scrap steel rate of the rolled steel production line has become an urgent problem to be solved in the current steel industry.

[0004] In the related art, during the rolling process, sensors are used to monitor in real time the temperature, thickness, width and other parameters of the rolled pieces sent out from the zinc-extracting electric furnace on the steel rolling production line, and the rolling parameters are adjusted in real time according to the monitoring results to ensure the rolling quality, thereby reducing the scrap rate. However, since the overall temperature of the steel rolling production line is relatively high during actual operation, the high ambient temperature will cause the monitoring data of the sensor to have a certain error, and the high ambient temperature will result in fewer types of sensors that can be installed on the steel rolling production line, resulting in reduced monitoring quality, thereby reducing the scrap rate control effect. Summary of the invention

[0005] In order to improve the scrap rate control effect of a steel rolling production line and reduce the scrap rate of a steel rolling production line, the present application provides a method and system for controlling zinc extraction in an electric furnace for recycling domestic waste.

[0006] In the first aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0007] A method for controlling zinc extraction from an electric furnace by recycling domestic waste, the method comprising:

[0008] Acquire steel rolling sensor monitoring data, and obtain abnormal data of the steel rolling production line according to the steel rolling sensor monitoring data;

[0009] Analyze the abnormal data of the steel rolling production line to obtain the corresponding information of the abnormality of the steel rolling production line;

[0010] Based on the abnormal corresponding information of the steel rolling production line, obtaining the corresponding control information of the steel rolling production line;

[0011] Based on the corresponding information of the steel rolling production line control, the operating parameters of the steel rolling production line are adjusted.

[0012] By adopting the above technical scheme, a variety of sensors are installed on the steel rolling production line, for example, temperature sensors for measuring the temperature of key parts such as molten steel, steel plates and rollers sent from the zinc extraction electric furnace, and pressure sensors installed in the hydraulic and pneumatic systems for monitoring the pressure of the rolling mill, etc. By acquiring the monitoring data of various sensors, the production status of the steel rolling production line can be grasped in real time, and the steel rolling sensor monitoring data corresponding to the sensor that monitors the abnormal situation can be judged. Since the steel rolling production line occupies a large area, a large number of sensors are installed on the overall steel rolling production line. Therefore, by analyzing the steel rolling sensor monitoring data corresponding to the sensor that monitors the abnormal situation, the specific situation can be further judged. The abnormal situation and the factors causing the abnormal situation, for example, the monitoring data of multiple abnormal temperature sensors are jointly analyzed, and then combined with the operation status of the current steel rolling production line, the location that causes the data abnormality on the overall steel rolling production line and the equipment corresponding to the location are specifically determined, and then according to the results of the specific analysis, the equipment control information for adjusting the equipment of the steel rolling production line is generated. Based on this, the corresponding monitoring data is obtained at the output end of the zinc extraction electric furnace through the steel rolling sensor, and through the overall analysis of the steel rolling production line, the degree to which the monitoring results are affected by environmental factors can be reduced, and the accuracy of monitoring can be improved, thereby improving the scrap steel rate control effect of the steel rolling production line and reducing the scrap steel rate of the steel rolling production line.

[0013] In a preferred example, the present application may be further configured as follows: the step of acquiring the steel rolling sensor monitoring data and obtaining the steel rolling production line abnormal data according to the steel rolling sensor monitoring data specifically includes:

[0014] Acquire steel rolling sensor monitoring data, wherein the steel rolling sensor monitoring data includes billet monitoring data and equipment monitoring data;

[0015] The billet monitoring data and the equipment monitoring data are input into a preset steel rolling process analysis model, and based on the steel rolling process analysis model, abnormal data of the steel rolling production line is obtained.

[0016] By adopting the above technical solution, the steel rolling sensor monitoring data includes billet monitoring data and equipment monitoring data, wherein the billet monitoring data refers to the monitoring data obtained by monitoring the molten steel and billet conveyed on the steel rolling production line, such as the temperature monitoring data of the molten steel and the billet, the size monitoring data of the billet and the conveying speed monitoring data of the billet, etc., and the equipment monitoring data refers to the monitoring data obtained by monitoring the production equipment on the steel rolling production line, such as the vibration monitoring data of the production equipment, the temperature monitoring data of the production equipment and the rolling pressure monitoring data of the production equipment, etc. The billet monitoring data and the equipment monitoring data correspond to different causes of scrap steel. factors, therefore, the billet monitoring data and the equipment monitoring data are input into a preset steel rolling process analysis model, which refers to a model used to analyze whether the billet monitoring data and the equipment monitoring data are abnormal. For example, by respectively comparing the billet monitoring data and the equipment monitoring data with the corresponding monitoring thresholds, and jointly analyzing the billet monitoring data and the equipment monitoring data corresponding to the same equipment area, it is determined whether the billet monitoring data corresponds to normal under the equipment operating conditions represented by the equipment monitoring data. In this way, the overall steel rolling production line is analyzed and monitored to ensure the accuracy of monitoring, thereby improving the scrap steel rate control effect of the steel rolling production line.

[0017] In a preferred example, the present application can be further configured as follows: analyzing the abnormal data of the steel rolling production line to obtain the abnormal corresponding information of the steel rolling production line specifically includes:

[0018] Based on the preset data interception rules, the steel rolling sensor monitoring data corresponding to the abnormal data of the steel rolling production line is intercepted to obtain abnormal dynamic data of the steel rolling production line;

[0019] The abnormal dynamic data of the steel rolling production line is input into a preset steel rolling dynamic analysis model, and the abnormal dynamic data of the steel rolling production line is analyzed based on the steel rolling dynamic analysis model to obtain corresponding information of the steel rolling production line abnormality.

[0020] By adopting the above technical solution, on the steel rolling production line, the location of the steel rolling sensor monitoring data indicates the location of the sensor where the monitoring abnormal data appears, and does not necessarily indicate the location where the abnormality occurs on the steel rolling production line. For example, if a temperature sensor shows abnormally high temperature at a certain part of the steel rolling mill, this may mean that there is an overheating problem at that part, but it may also be caused by a fault or improper operation of other parts, because on the steel rolling production line, the location of the factor that causes the abnormal data of the steel rolling production line will not be too far away from the corresponding location of the abnormal data of the steel rolling production line itself, and if all the steel rolling sensor monitoring data and the abnormal data of the steel rolling production line are combined for analysis, Analysis may be interfered by a large amount of data. Therefore, based on the preset data interception rules, which refer to the rules for intercepting data segments used to analyze abnormal data of the steel rolling production line, the data corresponding to the factors that may cause abnormal data of the steel rolling production line are intercepted to obtain abnormal dynamic data of the steel rolling production line, and the abnormal dynamic data of the steel rolling production line is input into the preset steel rolling dynamic analysis model, which refers to the model used to analyze the dynamic characteristics of the steel rolling production line, and then the position of the abnormal factor corresponding to the abnormal dynamic data of the steel rolling production line is found, so as to facilitate the adjustment of the abnormal factor position and improve the scrap steel rate control effect of the steel rolling production line.

[0021] In a preferred example, the present application can be further configured as follows: based on the abnormal corresponding information of the steel rolling production line, obtaining the corresponding information of the steel rolling production line control specifically includes:

[0022] Based on the abnormal corresponding information of the steel rolling production line, obtaining corresponding equipment operating parameters;

[0023] Determine whether the operating parameters of the corresponding device are abnormal, and if it is determined that the operating parameters of the corresponding device are abnormal, obtain device abnormality control information;

[0024] If it is determined that the operating parameters of the corresponding equipment are normal, then obtaining corresponding parameter control information of the steel rolling production line according to the abnormal corresponding information of the steel rolling production line;

[0025] The steel rolling production line control corresponding information includes equipment abnormality control information and the steel rolling production line parameter control information.

[0026] By adopting the above technical scheme, in addition to monitoring the state of the steel billet and the state of the production equipment on the steel rolling production line, it is also necessary to monitor the operating parameters of the production equipment, such as the operating power, current and voltage of the production equipment. When the operating parameters of the production equipment are abnormal, it means that the production equipment is abnormal, which will cause the scrap rate of the steel rolling production line to increase. Therefore, firstly, based on the abnormal corresponding information of the steel rolling production line, the suspected abnormal position indicated by the abnormal corresponding information of the steel rolling production line is judged, and all output production equipment corresponding to the suspected abnormal position indicated by the abnormal corresponding information of the steel rolling production line is marked to judge whether the operating parameters of these equipment are normal. When it is judged that the operating parameters of the corresponding equipment are abnormal, it can be judged that the factor causing the abnormal data of the steel rolling production line is the abnormal operating parameters of the production equipment, and then the equipment abnormal control information for controlling the production equipment is generated; when it is judged that the operating parameters of the corresponding equipment are normal, it means that the factor causing the abnormal data of the steel rolling production line is not the operating parameters of the production equipment, then according to the abnormal corresponding information of the steel rolling production line, other factors at the abnormal factor position corresponding to the abnormal dynamic data of the steel rolling production line are judged, and then the corresponding parameter control information of the steel rolling production line is obtained, so as to improve the scrap rate control effect of the steel rolling production line.

[0027] In a preferred example, the present application can be further configured as follows: if it is determined that the operating parameters of the corresponding equipment are normal, then after obtaining the corresponding parameter control information of the steel rolling production line according to the abnormal corresponding information of the steel rolling production line, the electric furnace zinc extraction control method for recycling domestic waste also includes:

[0028] Acquire the detection frequency information of the steel rolling sensor, analyze it in combination with the corresponding equipment operation parameters, the detection frequency information of the steel rolling sensor and the abnormal data of the steel rolling production line, and obtain the frequency analysis result;

[0029] generating sensor frequency adjustment information according to the frequency analysis result;

[0030] The sensor frequency adjustment information is associated with the steel rolling production line control corresponding information.

[0031] By adopting the above technical solution, when it is judged that the operating parameters of the corresponding equipment are normal, it means that the factor causing the abnormal data of the steel rolling production line is not the operating parameters of the production equipment, but it does not mean that it has nothing to do with the production equipment. For example, when the working frequency of the production equipment is just staggered with the detection frequency of the sensor used to detect the production equipment, and the production equipment will only show abnormality when it is working, it may cause the abnormality of the production equipment to be unable to be detected. For example, the roller will only generate high-intensity abnormal vibration when the billet passes, and the detection frequency of the sensor for detecting the vibration intensity of the roller is just staggered with the frequency of the roller passing the billet, which will cause the vibration intensity monitoring data of the roller to be normal, but the actual roller equipment has abnormal conditions. Therefore, the steel rolling sensor detection frequency information is obtained, and combined with the corresponding equipment operating parameters, the steel rolling sensor detection frequency information and the abnormal data of the steel rolling production line for analysis, that is, through the abnormal data of the steel rolling production line and the corresponding equipment operating parameters, the billet rolling frequency of the roller equipment and the abnormal data of multiple vibration sensors are judged, and then the detection frequency of each vibration sensor at the suspected abnormal position is judged. Abnormal, and the corresponding sensor frequency adjustment information is generated, so as to further ensure the accuracy of monitoring, thereby improving the scrap rate control effect of the steel rolling production line.

[0032] In the second aspect, the above invention objective of the present application is achieved through the following technical solutions:

[0033] A control system for extracting zinc from an electric furnace by recycling domestic waste, the control system comprising:

[0034] An abnormality analysis module, used to obtain the monitoring data of the steel rolling sensor, and obtain the abnormal data of the steel rolling production line according to the monitoring data of the steel rolling sensor;

[0035] An abnormality corresponding analysis module is used to analyze the abnormal data of the steel rolling production line and obtain abnormality corresponding information of the steel rolling production line;

[0036] A control corresponding analysis module, used for obtaining the control corresponding information of the steel rolling production line based on the abnormal corresponding information of the steel rolling production line;

[0037] A control adjustment module is used to adjust the operating parameters of the steel rolling production line based on the corresponding control information of the steel rolling production line.

[0038] Optionally, the abnormality analysis module includes:

[0039] A data acquisition submodule, used to acquire steel rolling sensor monitoring data, wherein the steel rolling sensor monitoring data includes billet monitoring data and equipment monitoring data;

[0040] The model analysis submodule is used to input the steel billet monitoring data and the equipment monitoring data into a preset steel rolling process analysis model, and obtain abnormal data of the steel rolling production line based on the steel rolling process analysis model.

[0041] Optionally, the abnormal correspondence analysis module includes:

[0042] A data interception submodule, for intercepting the steel rolling sensor monitoring data corresponding to the abnormal data of the steel rolling production line based on a preset data interception rule, and obtaining abnormal dynamic data of the steel rolling production line;

[0043] The dynamic analysis submodule is used to input the abnormal dynamic data of the steel rolling production line into a preset steel rolling dynamic analysis model, analyze the abnormal dynamic data of the steel rolling production line based on the steel rolling dynamic analysis model, and obtain corresponding information of the steel rolling production line abnormality.

[0044] In the third aspect, the above invention objective of the present application is achieved through the following technical solutions:

[0045] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned electric furnace zinc extraction control method for recycling domestic waste when executing the computer program.

[0046] In a fourth aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0047] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned electric furnace zinc extraction control method for recycling domestic waste.

[0048] In summary, the present application includes at least one of the following beneficial technical effects:

[0049] 1. A variety of sensors are installed on the steel rolling production line, for example, temperature sensors for measuring the temperature of key parts such as molten steel, steel plates and rolls, and pressure sensors installed in hydraulic and pneumatic systems for monitoring the pressure of rolling mills. By acquiring the monitoring data of various sensors, the production situation of the steel rolling production line can be grasped in real time, and the monitoring data of the steel rolling sensor corresponding to the sensor that monitors the abnormal situation can be judged. Since the steel rolling production line occupies a large area, a large number of sensors are installed on the entire steel rolling production line. Therefore, by analyzing the monitoring data of the steel rolling sensor corresponding to the sensor that monitors the abnormal situation, the specific abnormal situation and the factors causing the abnormal situation can be further judged. For example, the monitoring data of multiple abnormal temperature sensors are jointly analyzed, and then combined with the current operation of the steel rolling production line, the position that causes the data abnormality on the entire steel rolling production line and the equipment corresponding to the position are specifically judged. Then, according to the results of the specific analysis, the equipment control information for correspondingly adjusting the equipment of the steel rolling production line is generated. Based on this, through the overall analysis of the steel rolling production line, the degree to which the monitoring results are affected by environmental factors is reduced, and the accuracy of monitoring is improved, thereby improving the scrap rate control effect of the steel rolling production line and reducing the scrap rate of the steel rolling production line;

[0050] 2. The steel rolling sensor monitoring data includes billet monitoring data and equipment monitoring data. The billet monitoring data refers to the monitoring data obtained by monitoring the molten steel and billet conveyed on the steel rolling production line, such as the temperature monitoring data of the molten steel and billet, the size monitoring data of the billet and the conveying speed monitoring data of the billet, etc. The equipment monitoring data refers to the monitoring data obtained by monitoring the production equipment on the steel rolling production line, such as the vibration monitoring data of the production equipment, the temperature monitoring data of the production equipment and the rolling pressure monitoring data of the production equipment. The billet monitoring data and the equipment monitoring data correspond to different factors that lead to scrap steel, respectively. Herein, the billet monitoring data and the equipment monitoring data are input into a preset steel rolling process analysis model, which refers to a model used to analyze whether the billet monitoring data and the equipment monitoring data are abnormal. For example, by comparing the billet monitoring data and the equipment monitoring data with corresponding monitoring thresholds respectively, and jointly analyzing the billet monitoring data and the equipment monitoring data corresponding to the same equipment area, it is determined whether the billet monitoring data corresponds to normal under the equipment operating conditions represented by the equipment monitoring data. In this way, the overall steel rolling production line is analyzed and monitored to ensure the accuracy of monitoring, thereby improving the scrap steel rate control effect of the steel rolling production line;

[0051] 3. On the steel rolling production line, the location of the steel rolling sensor monitoring data indicates the location of the sensor where the abnormal monitoring data appears, and does not necessarily indicate the location where the abnormality occurs on the steel rolling production line. For example, if a temperature sensor shows abnormally high temperature at a certain part of the steel rolling mill, this may mean that there is an overheating problem in that part, but it may also be caused by failures or improper operation in other parts. Because on the steel rolling production line, the location of the factors that cause abnormal data of the steel rolling production line will not be too far away from the corresponding position of the abnormal data of the steel rolling production line itself, and if all the steel rolling sensor monitoring data and the abnormal data of the steel rolling production line are analyzed together, It may be interfered by a large amount of data. Therefore, based on the preset data interception rules, which refer to the rules for intercepting data segments used to analyze abnormal data of the steel rolling production line, the data corresponding to the factors that may cause abnormal data of the steel rolling production line will be intercepted to obtain abnormal dynamic data of the steel rolling production line, and the abnormal dynamic data of the steel rolling production line will be input into the preset steel rolling dynamic analysis model, which refers to the model used to analyze the dynamic characteristics of the steel rolling production line, and then the position of the abnormal factor corresponding to the abnormal dynamic data of the steel rolling production line is found, so as to facilitate the adjustment of the position of the abnormal factor and improve the scrap steel rate control effect of the steel rolling production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a first implementation flow chart of the electric furnace zinc extraction control method for recycling domestic waste in the embodiment of the present application;

[0053] Figure 2 It is a flow chart for realizing S10 of the electric furnace zinc extraction control method for recycling domestic waste in the embodiment of the present application;

[0054] Figure 3 It is a flow chart for realizing S20 of the electric furnace zinc extraction control method for recycling domestic waste in the embodiment of the present application;

[0055] Figure 4 This is a first implementation flow chart of S30 of the electric furnace zinc extraction control method for recycling domestic waste in the embodiment of the present application;

[0056] Figure 5 This is a second implementation flow chart of S30 of the electric furnace zinc extraction control method for recycling domestic waste in the embodiment of the present application;

[0057] Figure 6 This is a principle block diagram of a zinc extraction control system for an electric furnace for recycling domestic waste in an embodiment of the present application;

[0058] Figure 7 It is a diagram of the internal structure of a computer device for controlling zinc extraction from an electric furnace for recycling domestic waste in an embodiment of the present application. DETAILED DESCRIPTION

[0059] The following is combined with Figure 1-7 This application is described in further detail.

[0060] In one embodiment, if Figure 1 As shown, the present application discloses a method for controlling zinc extraction from an electric furnace by recycling domestic waste, which specifically comprises the following steps:

[0061] S10: Acquire the monitoring data of the steel rolling sensor, and obtain the abnormal data of the steel rolling production line according to the monitoring data of the steel rolling sensor.

[0062] In this embodiment, the control method for extracting zinc from an electric furnace for recycling domestic waste is applied to an electric furnace for extracting zinc and a steel rolling production line. The electric furnace is used to purify a mixture of domestic waste containing iron, and raw materials containing iron and zinc for producing steel rolling have been extracted. The steel rolling production line is used to produce rebar. A variety of sensors are installed on the steel rolling production line, including temperature sensors (infrared thermometers) for measuring the temperature of key parts such as molten steel, steel billets and rolls, pressure sensors installed in hydraulic and pneumatic systems for monitoring the pressure of the rolling mill, displacement sensors for measuring the displacement of the rolls and the thickness of the rolled product, speed sensors installed on the rolling mill and conveyor belts for monitoring the running speed of the steel billets and equipment, vibration sensors installed on key equipment for monitoring the vibration of the equipment, and surface quality detection sensors for detecting surface defects and quality problems of steel billets, etc. Optionally, ultrasonic sensors for detecting internal defects of rolled products and measuring parameters such as thickness, as well as visual recognition systems for automatically detecting and identifying the surface quality of steel billets, etc. can also be set. The monitoring data of the steel rolling sensor refers to the monitoring data of the sensors installed on the steel rolling production line. The abnormal data of the steel rolling production line refers to the abnormal data in the monitoring data of the steel rolling sensor.

[0063] Specifically, during the steel rolling production process, sensors installed on the steel rolling production line monitor the production status in real time, and obtain the monitoring data of the sensors installed on the steel rolling production line, namely, the steel rolling sensor monitoring data. It should be noted that multiple sensors of the same type may be installed on the steel rolling production line. For example, temperature sensors and vibration sensors are installed on each rolling mill of rough rolling and finishing rolling. Therefore, the steel rolling sensor monitoring data includes the monitoring data of each sensor, and the steel rolling sensor monitoring data includes the temperature and vibration intensity of molten steel, billet and roll, the displacement and rolling pressure of the roll, the position and size parameters of the billet, and the speed of the billet. Because the working conditions of the equipment in each process are basically unchanged during the operation of the steel rolling production line, therefore, before the operation of the steel rolling production line, a monitoring threshold corresponding to each sensor is set. After obtaining the steel rolling sensor monitoring data, the monitoring data of each sensor represented by the steel rolling sensor monitoring data is compared with the corresponding monitoring threshold, so as to obtain abnormal data in the steel rolling sensor monitoring data, namely, abnormal data of the steel rolling production line.

[0064] Furthermore, since the steel rolling production line has a long thread, for example, multiple rolling mills are installed, the operation conditions of the steel rolling production line are complicated. Therefore, the corresponding sensor monitoring data is large, and the set monitoring thresholds are not necessarily accurate. Simply comparing the steel rolling sensor monitoring data with the corresponding monitoring thresholds cannot detect the corresponding abnormal conditions in time. Therefore, it is necessary to conduct multi-faceted analysis on the monitoring data of the steel rolling sensor, including similar data analysis, correlation analysis and fluctuation analysis. Similar data analysis refers to comprehensive analysis of the same type of monitoring data, for example, each temperature monitoring data of each finishing mill is analyzed to determine whether the difference of each temperature monitoring data of each finishing mill is normal and whether the change trend of each temperature monitoring data of each finishing mill is normal; correlation analysis refers to analysis of different types of monitoring data with correlation, for example, to determine that the temperature change of the finishing mill is correlated with the vibration intensity change of the finishing mill, then the temperature monitoring data of the finishing mill and the vibration intensity monitoring data of the finishing mill are correlated to determine whether the correlation between the temperature monitoring data of the finishing mill and the vibration intensity monitoring data of the finishing mill is normal; fluctuation analysis refers to analysis of the monitoring data of the same sensor within a period of time, for example, the temperature monitoring data of the finishing mill within a period of time is collected and the fluctuation degree of the temperature monitoring data is determined to be normal. Based on this, through multi-faceted abnormal analysis, the steel rolling sensor with abnormal performance is regarded as abnormal data of the steel rolling production line.

[0065] S20: Analyze the abnormal data of the steel rolling production line to obtain the corresponding information of the abnormality of the steel rolling production line.

[0066] In this embodiment, the steel rolling production line abnormality corresponding information refers to the corresponding position of the steel rolling production line abnormality data on the steel rolling production line.

[0067] Specifically, since the steel rolling production line occupies a large area, the monitoring range of each sensor is limited, and the number of sensors installed on the entire steel rolling production line will be large. In addition, the transmission speed of the steel billet in the steel rolling production line is fast, and the temperature of the steel billet is also relatively high. Therefore, the abnormal data of the steel rolling production line indicates that the data monitored by the sensor is abnormal, and does not necessarily mean that the equipment where the sensor is located is abnormal. Therefore, the steel rolling sensor monitoring data corresponding to the sensor that monitors the abnormal situation is combined and analyzed to determine the specific abnormal situation and the factors and locations that cause the abnormal situation, and obtain the corresponding abnormal information of the steel rolling production line.

[0068] For example, when the abnormal data of the steel rolling production line indicates that the changing trend of the temperature monitoring data of the finishing mill is abnormal, it is determined whether the changing trend of the temperature monitoring data of the finishing mill is consistent with the changing trend of the temperature monitoring data of other equipment before and after the finishing mill. When it is determined that the changing trend of the temperature monitoring data of the finishing mill is inconsistent with the changing trend of the temperature monitoring data of other equipment before and after the finishing mill, the equipment with the largest fluctuation degree is determined as the abnormal equipment based on the degree of fluctuation of the temperature monitoring data of the finishing mill and the temperature monitoring data of other equipment before and after the finishing mill, and the factor causing the abnormal situation is temperature. When it is determined that the changing trend of the temperature monitoring data of the finishing mill is inconsistent with the changing trend of the temperature monitoring data of other equipment before and after the finishing mill, the equipment with the largest fluctuation degree is determined as the abnormal equipment, and the factor causing the abnormal situation is temperature. When the changing trend of the temperature monitoring data is consistent with the changing trend of the temperature monitoring data of other equipment before and after the finishing mill, then based on the correlation analysis results of the temperature monitoring data of the finishing mill and the vibration intensity monitoring data of the finishing mill, if the correlation between the temperature monitoring data of the finishing mill and the vibration intensity monitoring data of the finishing mill is abnormal, the finishing mill is judged as an abnormal equipment, and the factor causing the abnormal situation is temperature. Specific abnormal situations include excessive rolling speed or unstable rolling speed; if the correlation between the temperature monitoring data of the finishing mill and the vibration intensity monitoring data of the finishing mill is normal, the finishing mill is judged as an abnormal equipment, and the factors causing the abnormal situation are temperature and vibration.

[0069] S30: Based on the abnormal corresponding information of the steel rolling production line, obtain the corresponding control information of the steel rolling production line.

[0070] In this embodiment, the steel rolling production line control corresponding information refers to the control information of the equipment on the steel rolling production line.

[0071] Specifically, after obtaining the corresponding information of the steel rolling production line abnormality, the preset equipment control index table is queried according to the factors causing the abnormal situation and the corresponding equipment indicated by the corresponding information of the steel rolling production line abnormality. The equipment control index table includes equipment control information corresponding to each abnormal situation of each equipment. For example, when the corresponding information of the steel rolling production line abnormality indicates that the temperature of the finishing mill is abnormal, the preset equipment control index table is queried. The equipment control information corresponding to the temperature abnormality of the finishing mill in the preset equipment control index table includes shutting down, checking the lubricating oil system, checking the motor cooling system and reducing the rolling speed, etc. Then, according to the results of checking the lubricating oil system and checking the motor cooling system, as well as the specific abnormal situation in the corresponding information of the steel rolling production line abnormality, the corresponding equipment control information is selected to obtain the corresponding corresponding information of the steel rolling production line control.

[0072] S40: Adjusting the operation parameters of the steel rolling production line based on the corresponding information of the steel rolling production line control.

[0073] Specifically, after obtaining the corresponding information of the steel rolling production line control, the operating parameters of the corresponding equipment on the steel rolling production line are adjusted or the operation of the corresponding equipment is controlled based on the corresponding information of the steel rolling production line control.

[0074] In one embodiment, if Figure 2 As shown, in step S10, the steel rolling sensor monitoring data is obtained, and the abnormal data of the steel rolling production line is obtained according to the steel rolling sensor monitoring data, which specifically includes:

[0075] S11: Acquire steel rolling sensor monitoring data, where the steel rolling sensor monitoring data includes billet monitoring data and equipment monitoring data.

[0076] In this embodiment, the billet monitoring data refers to the sensor monitoring data of the billet, and the equipment monitoring data refers to the sensor monitoring data of the equipment on the steel rolling production line.

[0077] Specifically, steel rolling sensor monitoring data is obtained, wherein the steel rolling sensor monitoring data includes billet monitoring data and equipment monitoring data. The billet monitoring data refers to the monitoring data obtained by monitoring the molten steel and billets conveyed on the steel rolling production line, such as the temperature monitoring data of the molten steel and the billets, the size monitoring data of the billets and the conveying speed monitoring data of the billets, etc., while the equipment monitoring data refers to the monitoring data obtained by monitoring the production equipment on the steel rolling production line, such as the vibration monitoring data of the production equipment, the temperature monitoring data of the production equipment and the rolling pressure monitoring data of the production equipment, etc.

[0078] S12: Input the steel billet monitoring data and the equipment monitoring data into a preset steel rolling process analysis model, and obtain abnormal data of the steel rolling production line based on the steel rolling process analysis model.

[0079] In this embodiment, the steel rolling process analysis model refers to a model used to analyze whether the billet monitoring data and the equipment monitoring data are abnormal.

[0080] Specifically, the billet monitoring data and the equipment monitoring data correspond to different factors that lead to the appearance of scrap steel, respectively. Therefore, the billet monitoring data and the equipment monitoring data are input into a preset steel rolling process analysis model, which refers to a model used to analyze whether the billet monitoring data and the equipment monitoring data are abnormal. The steel rolling process analysis model is pre-trained with a large amount of monitoring data of steel rolling production lines, and can learn to analyze different production modes of steel rolling production lines. For example, by comparing the billet monitoring data and the equipment monitoring data with the corresponding monitoring thresholds, respectively, and jointly analyzing the billet monitoring data and the equipment monitoring data corresponding to the same equipment area, it is determined whether the billet monitoring data corresponds to normal under the equipment operating conditions represented by the equipment monitoring data, thereby obtaining abnormal data of the steel rolling production line.

[0081] It should be noted that the abnormal data of the steel rolling production line includes abnormal data of the steel rolling production line indicating equipment abnormality and abnormal data of the steel rolling production line indicating abnormality of the steel billet or molten steel, wherein the abnormal data of the steel rolling production line indicating abnormality of the steel billet or molten steel can be obtained through the steel billet monitoring data or the equipment monitoring data. For example, the changing trend of the temperature monitoring data of the steel billet should be gradually decreasing in the steel rolling production line. If it is judged through the steel billet monitoring data that the changing trend of the temperature monitoring data of the steel billet is increasing, then the temperature monitoring data corresponding to the increasing changing trend is judged to be abnormal data; or when the surface quality detection sensor used to detect surface defects and quality problems of the steel billet indicates that the surface of the steel billet is normal, and the fluctuation degree of the temperature monitoring data of the steel billet is large, at this time, the monitoring data of the surface quality detection sensor and the temperature monitoring data of the steel billet when the corresponding fluctuation degree is large are simultaneously regarded as abnormal data.

[0082] In one embodiment, if Figure 3 As shown, in step S20, the abnormal data of the steel rolling production line is analyzed to obtain the abnormal corresponding information of the steel rolling production line, which specifically includes:

[0083] S21: Based on the preset data interception rules, intercept the steel rolling sensor monitoring data corresponding to the abnormal data of the steel rolling production line to obtain the abnormal dynamic data of the steel rolling production line.

[0084] In this embodiment, the data interception rule refers to the rule for intercepting the data segment used for analyzing the abnormal data of the steel rolling production line. The abnormal dynamic data of the steel rolling production line refers to the data used for analyzing the dynamic characteristics of the steel rolling production line.

[0085] Specifically, on a steel rolling production line, the location of the steel rolling sensor monitoring data indicates the location of the sensor where the abnormal monitoring data appears, but does not necessarily indicate the location where the abnormality appears on the steel rolling production line. For example, if a temperature sensor shows abnormally high temperature at a certain part of the steel rolling mill, this may mean that there is an overheating problem at that part, but it may also be caused by a fault or improper operation in other parts. It is found through practical experience that on a steel rolling production line, the location of the factors that cause abnormal data of the steel rolling production line will not be too far away from the corresponding position of the abnormal data of the steel rolling production line itself; and if all the steel rolling sensor monitoring data and the abnormal data of the steel rolling production line are combined for analysis, they may be interfered by a large amount of data. Therefore, based on the preset data interception rule, the data interception rule refers to the rule for intercepting the data segment used to analyze the abnormal data of the steel rolling production line, and the steel rolling sensor monitoring data corresponding to the current abnormal data of the steel rolling production line is intercepted from all the steel rolling sensor monitoring data to obtain the abnormal dynamic data of the steel rolling production line.

[0086] S22: Inputting the abnormal dynamic data of the steel rolling production line into a preset steel rolling dynamic analysis model, analyzing the abnormal dynamic data of the steel rolling production line based on the steel rolling dynamic analysis model, and obtaining corresponding information of the steel rolling production line abnormality.

[0087] In this embodiment, the steel rolling dynamic analysis model refers to a model used to analyze the dynamic characteristics of a steel rolling production line.

[0088] Specifically, the abnormal dynamic data of the steel rolling production line is input into a preset steel rolling dynamic analysis model, which refers to a model used to analyze the dynamic characteristics of the steel rolling production line. The steel rolling dynamic analysis model is pre-trained with a large amount of production data of the steel rolling production line, and can judge the operating conditions of each device and the state of the steel billet during transmission according to the abnormal dynamic data of the steel rolling production line. Therefore, the abnormal dynamic data of the steel rolling production line is analyzed based on the steel rolling dynamic analysis model to judge the current operating conditions of each device and the state of the steel billet during transmission, and then generate the abnormal corresponding information of the steel rolling production line. For example, through the temperature monitoring data of the steel billet and the vibration monitoring data of the vibration sensor installed on the key equipment to monitor the vibration of the equipment, it is judged that cracks appear during the steel billet transmission process, and according to the pressure monitoring data of the pressure sensor used to monitor the pressure of the rolling mill, the equipment causing the abnormality is judged, and the corresponding abnormal corresponding information of the steel rolling production line is obtained.

[0089] Furthermore, in this embodiment, within a preset verification period after the operation parameters of the steel rolling production line are adjusted, actual scrap steel rate data is obtained, and the actual scrap steel rate data refers to the scrap steel rate of actual production. The actual scrap steel rate data is input into the steel rolling dynamic analysis model. In addition to being able to analyze the dynamic characteristics of the steel rolling production line, the steel rolling dynamic analysis model can also predict the scrap steel rate of the current steel rolling production line. Therefore, by collecting the acquired steel rolling sensor monitoring data, steel rolling production line abnormal data, steel rolling production line abnormal corresponding information and steel rolling production line control corresponding information and other data into the steel rolling dynamic analysis model in real time, through the steel rolling dynamic analysis model, after obtaining When obtaining the actual scrap steel rate data, the predicted scrap steel rate data is obtained at the same time, and the actual scrap steel rate data is compared with the predicted scrap steel rate data. If the difference between the actual scrap steel rate data and the predicted scrap steel rate data exceeds the preset scrap steel rate threshold, it is judged that the current adjustment cannot meet the demand. Therefore, based on the dynamic analysis characteristics of the steel rolling dynamic analysis model, the predicted steel rolling production line control corresponding information when the scrap steel rate meets the demand is inferred, and the operating parameters of the steel rolling production line are readjusted based on the predicted steel rolling production line control corresponding information. For example, the predicted scrap steel rate is used as the standard scrap steel rate, and a back-analysis is performed based on the predicted scrap steel rate data to generate the predicted steel rolling production line control corresponding information.

[0090] In one embodiment, if Figure 4As shown, in step S30, the steel rolling production line control corresponding information includes equipment abnormality control information and steel rolling production line parameter control information. Based on the steel rolling production line abnormality corresponding information, the steel rolling production line control corresponding information is obtained, which specifically includes:

[0091] S31: Based on the abnormal information corresponding to the steel rolling production line, obtain the corresponding equipment operating parameters.

[0092] In this embodiment, the corresponding equipment operating parameters refer to the operating parameters of the production equipment corresponding to the abnormal information of the steel rolling production line.

[0093] Specifically, on a steel rolling production line, in addition to monitoring the status of the steel billet and the status of the production equipment, it is also necessary to monitor the operating parameters of the production equipment, such as the operating power, current and voltage of the production equipment. When the operating parameters of the production equipment are abnormal, it means that the production equipment is abnormal, which will cause the scrap rate of the steel rolling production line to increase. Therefore, based on the corresponding information of the steel rolling production line abnormality, the suspected abnormal position indicated by the corresponding information of the steel rolling production line abnormality is judged, and all production equipment corresponding to the suspected abnormal position indicated by the corresponding information of the steel rolling production line abnormality is marked, and the operating parameters of the marked production equipment are obtained to obtain the corresponding equipment operating parameters.

[0094] S32: Determine whether the operating parameters of the corresponding device are abnormal. If the operating parameters of the corresponding device are abnormal, obtain device abnormality control information.

[0095] In this embodiment, the equipment abnormality control information refers to control information used to control the operation of production equipment.

[0096] Specifically, it is determined whether the corresponding equipment operating parameters are abnormal, for example, it is determined whether the operating power, current and voltage of the production equipment exceed the rated power, rated operating current and rated voltage, etc. If it is determined that the corresponding equipment operating parameters are abnormal, it can be determined that the factor causing the abnormal data of the steel rolling production line is the abnormal operating parameters of the production equipment, and then the equipment abnormality control information for controlling the production equipment is generated, for example, according to the judgment result of the abnormality of the corresponding equipment operating parameters, the equipment abnormality control information for adjusting the operating power of the production equipment is generated.

[0097] S33: If it is determined that the operating parameters of the corresponding equipment are normal, the corresponding parameter control information of the steel rolling production line is obtained according to the corresponding abnormal information of the steel rolling production line.

[0098] Specifically, if it is judged that the operating parameters of the corresponding equipment are normal, it means that the factor causing the abnormal data of the steel rolling production line is not the operating parameters of the production equipment. Therefore, according to the corresponding information of the steel rolling production line abnormality, other factors at the abnormal factor position corresponding to the abnormal dynamic data of the steel rolling production line are judged. For example, when the corresponding information of the steel rolling production line abnormality indicates that the factor causing the abnormal situation is temperature, the specific abnormal situation includes excessive rolling speed or unstable rolling speed, and the factor causing the abnormality is not the operating parameters of the production equipment. Therefore, according to the corresponding information of the steel rolling production line abnormality, the monitoring data of the displacement sensor for measuring the displacement of the rolling roller and the speed sensor for detecting the running speed of the rolling roller are used to judge whether the factor causing the excessive rolling speed or unstable rolling speed is improper displacement of the rolling roller or excessive or unstable running speed of the rolling roller, and then generate corresponding steel rolling production line parameter control information for controlling the displacement of the rolling roller or steel rolling production line parameter control information for controlling the running speed of the rolling roller.

[0099] In one embodiment, if Figure 5 As shown, after S33, that is, if it is determined that the corresponding equipment operating parameters are normal, then according to the abnormal corresponding information of the steel rolling production line, after obtaining the corresponding steel rolling production line parameter control information, the electric furnace zinc extraction control method for recycling domestic waste also includes:

[0100] S34: Acquire the detection frequency information of the steel rolling sensor, and analyze it in combination with the corresponding equipment operating parameters, the detection frequency information of the steel rolling sensor and the abnormal data of the steel rolling production line to obtain the frequency analysis result.

[0101] In this embodiment, the steel rolling sensor detection frequency information refers to the detection frequency of the sensor on the steel rolling production line. The frequency analysis result refers to the result of analyzing whether the frequency is abnormal.

[0102] Specifically, when it is judged that the operating parameters of the corresponding equipment are normal, it means that the factor causing the abnormal data of the steel rolling production line is not the operating parameters of the production equipment, but it does not mean that it has nothing to do with the production equipment. For example, when the operating frequency of the production equipment happens to be offset from the detection frequency of the sensor used to detect the production equipment, and the production equipment will only show abnormalities when it is working, it may lead to the inability to detect the abnormality of the production equipment. For example, the roller will only generate high-intensity abnormal vibration when the billet passes by, and the detection frequency of the sensor for detecting the vibration intensity of the roller happens to be offset from the frequency of the roller passing the billet, which will lead to the vibration intensity monitoring of the roller. The data is normal, but the actual rolling mill equipment has abnormal conditions. Therefore, the detection frequency of the sensors on the steel rolling production line, that is, the detection frequency information of the steel rolling sensor, is obtained, and analyzed in combination with the corresponding equipment operating parameters, the detection frequency information of the steel rolling sensor and the abnormal data of the steel rolling production line. For example, the rolling frequency of the rolling mill equipment is judged by the corresponding equipment operating parameters, and the abnormal data of multiple vibration sensors are judged by the abnormal data of the steel rolling production line. Then, it is judged whether the detection frequency of each vibration sensor in the suspected abnormal position represented by the corresponding information of the steel rolling production line can be detected when the rolling mill equipment rolls the steel billet, and the frequency analysis result is obtained.

[0103] S35: Generate sensor frequency adjustment information according to the frequency analysis result.

[0104] In this embodiment, the sensor frequency adjustment information refers to control information for adjusting the detection frequency of the sensor.

[0105] Specifically, according to the frequency analysis results, if the frequency analysis results show that the detection frequency of the sensor on the steel rolling production line is abnormal or it is difficult to accurately detect the required data, then according to the frequency analysis results indicating that the frequency is too fast or the frequency is too slow, corresponding control information for adjusting the detection frequency of the sensor is generated, i.e., sensor frequency adjustment information.

[0106] S36: Associate the sensor frequency adjustment information to the corresponding information of the steel rolling production line control.

[0107] Specifically, the sensor frequency adjustment information is associated with the corresponding information of the steel rolling production line control, so that when the operating parameters of the steel rolling production line are adjusted based on the corresponding information of the steel rolling production line control, the detection frequency of the sensor is adjusted at the same time, thereby further improving the accuracy of monitoring.

[0108] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0109] In one embodiment, a control system for extracting zinc from an electric furnace by recycling domestic waste is provided, and the control system for extracting zinc from an electric furnace by recycling domestic waste corresponds to the control method for extracting zinc from an electric furnace by recycling domestic waste in the above embodiment. Figure 6 As shown, the electric furnace zinc extraction control system for recycling domestic waste includes an abnormality analysis module, an abnormality corresponding analysis module, a control corresponding analysis module and a control adjustment module. The detailed description of each functional module is as follows:

[0110] The abnormality analysis module is used to obtain the monitoring data of the steel rolling sensor and obtain the abnormal data of the steel rolling production line according to the monitoring data of the steel rolling sensor;

[0111] The abnormality corresponding analysis module is used to analyze the abnormal data of the steel rolling production line and obtain the abnormal corresponding information of the steel rolling production line;

[0112] A control corresponding analysis module is used to obtain corresponding control information of the steel rolling production line based on the abnormal corresponding information of the steel rolling production line;

[0113] The control adjustment module is used to adjust the operating parameters of the steel rolling production line based on the corresponding information of the steel rolling production line control.

[0114] Optionally, the exception analysis module includes:

[0115] The data acquisition submodule is used to acquire the steel rolling sensor monitoring data, which includes the billet monitoring data and the equipment monitoring data;

[0116] The model analysis submodule is used to input the billet monitoring data and the equipment monitoring data into the preset steel rolling process analysis model, and obtain the abnormal data of the steel rolling production line based on the steel rolling process analysis model.

[0117] Optionally, the abnormality correspondence analysis module includes:

[0118] A data interception submodule is used to intercept the steel rolling sensor monitoring data corresponding to the abnormal data of the steel rolling production line based on the preset data interception rules, and obtain the abnormal dynamic data of the steel rolling production line;

[0119] The dynamic analysis submodule is used to input the abnormal dynamic data of the steel rolling production line into a preset steel rolling dynamic analysis model, analyze the abnormal dynamic data of the steel rolling production line based on the steel rolling dynamic analysis model, and obtain the corresponding information of the steel rolling production line abnormality.

[0120] Optionally, the steel production line control corresponding information includes equipment abnormality control information and steel rolling production line parameter control information, and the control corresponding analysis module includes:

[0121] The equipment parameter acquisition submodule is used to obtain the corresponding equipment operating parameters based on the corresponding information of the steel rolling production line abnormality;

[0122] The device abnormality judgment submodule is used to judge whether the corresponding device operating parameters are abnormal. If the corresponding device operating parameters are judged to be abnormal, the device abnormality control information is obtained;

[0123] The equipment judgment normal submodule is used to obtain the corresponding steel rolling production line parameter control information based on the corresponding abnormal information of the steel rolling production line if it is judged that the corresponding equipment operating parameters are normal.

[0124] Optionally, the control correspondence analysis module further includes:

[0125] The frequency acquisition submodule is used to obtain the detection frequency information of the steel rolling sensor, and analyze the corresponding equipment operating parameters, the detection frequency information of the steel rolling sensor and the abnormal data of the steel rolling production line to obtain the frequency analysis results;

[0126] The frequency adjustment information submodule is used to generate sensor frequency adjustment information according to the frequency analysis result;

[0127] The adjustment information association submodule is used to associate the sensor frequency adjustment information with the corresponding information of the steel rolling production line control.

[0128] The specific definition of the control system for zinc extraction from an electric furnace for recycling domestic waste can be found in the definition of the control method for zinc extraction from an electric furnace for recycling domestic waste mentioned above, which will not be repeated here. Each module in the above-mentioned control system for zinc extraction from an electric furnace for recycling domestic waste can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0129] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store abnormal data of the steel rolling production line, corresponding information of abnormal steel rolling production line and corresponding information of steel rolling production line control. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for controlling zinc extraction from an electric furnace for recycling domestic waste is realized.

[0130] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0131] Acquire the monitoring data of the steel rolling sensor, and obtain the abnormal data of the steel rolling production line according to the monitoring data of the steel rolling sensor;

[0132] Analyze the abnormal data of the steel rolling production line and obtain the corresponding information of the abnormality of the steel rolling production line;

[0133] Based on the abnormal corresponding information of the steel rolling production line, obtain the corresponding control information of the steel rolling production line;

[0134] Based on the corresponding information of the steel rolling production line control, the operating parameters of the steel rolling production line are adjusted.

[0135] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0136] Acquire the monitoring data of the steel rolling sensor, and obtain the abnormal data of the steel rolling production line according to the monitoring data of the steel rolling sensor;

[0137] Analyze the abnormal data of the steel rolling production line and obtain the corresponding information of the abnormality of the steel rolling production line;

[0138] Based on the abnormal corresponding information of the steel rolling production line, obtain the corresponding control information of the steel rolling production line;

[0139] Based on the corresponding information of the steel rolling production line control, the operating parameters of the steel rolling production line are adjusted.

[0140] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0141] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0142] The embodiments described above 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, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such 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, and should all be included in the protection scope of the present application.

Claims

1. A method for controlling zinc extraction from an electric furnace by recycling domestic waste, characterized in that: The electric furnace zinc extraction control method for recycling domestic waste comprises: Acquire steel rolling sensor monitoring data, and obtain abnormal data of the steel rolling production line according to the steel rolling sensor monitoring data; Analyze the abnormal data of the steel rolling production line to obtain the corresponding information of the abnormality of the steel rolling production line; Based on the abnormal corresponding information of the steel rolling production line, obtaining the corresponding control information of the steel rolling production line specifically includes: Based on the abnormal corresponding information of the steel rolling production line, obtaining corresponding equipment operating parameters; Determine whether the operating parameters of the corresponding device are abnormal, and if it is determined that the operating parameters of the corresponding device are abnormal, obtain device abnormality control information; If it is determined that the operating parameters of the corresponding equipment are normal, then obtaining corresponding parameter control information of the steel rolling production line according to the abnormal corresponding information of the steel rolling production line; Acquire the detection frequency information of the steel rolling sensor, analyze it in combination with the corresponding equipment operation parameters, the detection frequency information of the steel rolling sensor and the abnormal data of the steel rolling production line, and obtain the frequency analysis result; generating sensor frequency adjustment information according to the frequency analysis result; Associating the sensor frequency adjustment information with the steel rolling production line control corresponding information; The steel rolling production line control corresponding information includes equipment abnormality control information and the steel rolling production line parameter control information; Based on the corresponding information of the steel rolling production line control, the operating parameters of the steel rolling production line are adjusted.

2. The electric furnace zinc extraction control method for recycling domestic waste according to claim 1 is characterized in that: The step of acquiring the steel rolling sensor monitoring data and obtaining the abnormal data of the steel rolling production line according to the steel rolling sensor monitoring data specifically includes: Acquire steel rolling sensor monitoring data, wherein the steel rolling sensor monitoring data includes billet monitoring data and equipment monitoring data; The billet monitoring data and the equipment monitoring data are input into a preset steel rolling process analysis model, and based on the steel rolling process analysis model, abnormal data of the steel rolling production line is obtained.

3. The electric furnace zinc extraction control method for recycling domestic waste according to claim 1 is characterized in that: The analyzing the abnormal data of the steel rolling production line to obtain the abnormal corresponding information of the steel rolling production line specifically includes: Based on the preset data interception rules, the steel rolling sensor monitoring data corresponding to the abnormal data of the steel rolling production line is intercepted to obtain abnormal dynamic data of the steel rolling production line; The abnormal dynamic data of the steel rolling production line is input into a preset steel rolling dynamic analysis model, and the abnormal dynamic data of the steel rolling production line is analyzed based on the steel rolling dynamic analysis model to obtain corresponding information of the steel rolling production line abnormality.

4. A zinc extraction control system for electric furnaces for recycling domestic waste, characterized in that: The electric furnace zinc extraction control system for recycling domestic waste comprises: An abnormality analysis module, used to obtain the monitoring data of the steel rolling sensor, and obtain the abnormal data of the steel rolling production line according to the monitoring data of the steel rolling sensor; An abnormality corresponding analysis module is used to analyze the abnormal data of the steel rolling production line and obtain abnormality corresponding information of the steel rolling production line; A control corresponding analysis module is used to obtain the control corresponding information of the steel rolling production line based on the abnormal corresponding information of the steel rolling production line. The control corresponding information of the steel rolling production line includes equipment abnormality control information and steel rolling production line parameter control information. The control corresponding analysis module includes: The equipment parameter acquisition submodule is used to obtain the corresponding equipment operating parameters based on the corresponding information of the steel rolling production line abnormality; The device abnormality judgment submodule is used to judge whether the corresponding device operating parameters are abnormal. If the corresponding device operating parameters are judged to be abnormal, the device abnormality control information is obtained; The equipment judgment normal submodule is used to obtain the corresponding steel rolling production line parameter control information according to the corresponding information of the steel rolling production line abnormality if the corresponding equipment operation parameters are judged to be normal; The frequency acquisition submodule is used to obtain the detection frequency information of the steel rolling sensor, and analyze the corresponding equipment operating parameters, the detection frequency information of the steel rolling sensor and the abnormal data of the steel rolling production line to obtain the frequency analysis results; The frequency adjustment information submodule is used to generate sensor frequency adjustment information according to the frequency analysis result; An adjustment information association submodule is used to associate the sensor frequency adjustment information with the corresponding information of the steel rolling production line control; A control adjustment module is used to adjust the operating parameters of the steel rolling production line based on the corresponding control information of the steel rolling production line.

5. The electric furnace zinc extraction control system for recycling domestic waste according to claim 4 is characterized in that: The abnormality analysis module comprises: A data acquisition submodule, used to acquire steel rolling sensor monitoring data, wherein the steel rolling sensor monitoring data includes billet monitoring data and equipment monitoring data; The model analysis submodule is used to input the steel billet monitoring data and the equipment monitoring data into a preset steel rolling process analysis model, and obtain abnormal data of the steel rolling production line based on the steel rolling process analysis model.

6. The electric furnace zinc extraction control system for recycling domestic waste according to claim 5 is characterized in that: The abnormal correspondence analysis module includes: A data interception submodule, for intercepting the steel rolling sensor monitoring data corresponding to the abnormal data of the steel rolling production line based on a preset data interception rule, and obtaining abnormal dynamic data of the steel rolling production line; The dynamic analysis submodule is used to input the abnormal dynamic data of the steel rolling production line into a preset steel rolling dynamic analysis model, analyze the abnormal dynamic data of the steel rolling production line based on the steel rolling dynamic analysis model, and obtain corresponding information of the steel rolling production line abnormality.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the electric furnace zinc extraction control method for recycling domestic waste as described in any one of claims 1 to 3 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the steps of the electric furnace zinc extraction control method for recycling domestic waste as described in any one of claims 1 to 3 are implemented.

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