Submerged arc furnace slag treatment control method based on water quenching method

Abstract

The invention belongs to the technical field of slag treatment control, and particularly discloses a submerged arc furnace slag treatment control method based on a water quenching method, which comprises the following steps: acquiring chemical element content and dynamic viscosity in a raw material, inputting the chemical element content and the dynamic viscosity into a fuzzy reasoning metallurgical model to obtain an expected component matrix, viscosity and yield interval of the slag, and collecting temperatures of N temperature measuring points, a self-adaptive control algorithm is used for calculating a preset control instruction of a slag flushing pump, water quenching data are detected in real time in the slag flushing process, the control instruction of the slag flushing pump is dynamically adjusted according to the water quenching data, and after water quenching is finished, cold water is separated out and recycled through the processes of precipitation, cooling and the like; according to the slag expected component matrix, the viscosity, the yield interval and the temperature, the self-adaptive algorithm is used for calculating the control instruction of the slag flushing pump, the complex characteristics and temperature fluctuation of the slag are accurately adapted, the water quenching parameters are dynamically optimized, the water quenching effect is improved, and abrasion of equipment and blockage of pipelines are reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of slag treatment control, and relates to a slag treatment control method of an electric arc furnace based on a water quenching method. Background Art

[0002] The slag (such as ferroalloy slag) produced during the smelting process of the electric arc furnace poses a lot of environmental hazards. The traditional water quenching method is to directly contact the high-temperature liquid slag with water, and use the latent heat of vaporization of water to quickly cool the slag and break it into small particles. This method can effectively suppress the generation of dust and reduce pollution to the atmospheric environment. In addition, the slag after water quenching has good activity and can be used as cement admixtures, concrete admixtures, etc. in the field of building materials to achieve secondary utilization of resources and improve resource utilization. Although the water quenching method can achieve rapid cooling and resource utilization, there are still significant technical bottlenecks in practical applications.

[0003] For example, the blast furnace slag water quenching system disclosed in the existing invention patent publication number CN118516563A improves the processing efficiency by optimizing the chute structure and the layout of the water quenching nozzles, but its technical solution has essential defects: 1. The use of fixed water quenching parameters cannot respond to the dynamic changes of slag composition and temperature, resulting in uneven cooling and incomplete crushing, causing abnormal wear of equipment and pipeline blockage.

[0004] 2. Relying on physical structure improvements and lacking process parameter control mechanisms, it is difficult to establish a dynamic response relationship between water quenching data and process parameters, resulting in fluctuations in treatment effects and reduced resource utilization. These problems seriously restrict the stability and economy of industrial production, and it is necessary to develop a water quenching treatment system with intelligent control functions. Summary of the invention

[0005] In view of this, in order to solve the problems raised in the above background technology, a slag treatment control method of an electric arc furnace based on a water quenching method is proposed.

[0006] The purpose of the present invention can be achieved through the following technical scheme: The present invention provides a slag treatment control method for an electric arc furnace based on a water quenching method, comprising: S1, obtaining the content of each chemical element in the raw material and the dynamic viscosity, and inputting the raw material data into the Takagi-Sugeno fuzzy reasoning metallurgical model to obtain the expected composition matrix, expected viscosity value and expected output range of the slag.

[0007] S2. Acquisition The temperature of each temperature measuring point is used to calculate the preset control instructions of the slag flushing pump through the adaptive control algorithm.

[0008] S3, execute the preset control instructions of the slag flushing pump, detect the water quenching data when the high-temperature liquid slag contacts with water for water quenching, and dynamically adjust the control instructions of the slag flushing pump.

[0009] S4. After the water quenching is completed, the cold water is separated and recycled through sedimentation, cooling tower cooling and inclined plate sedimentation device.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention calculates the slag flushing pump control instructions based on the expected slag composition matrix, viscosity, production range and temperature using an adaptive algorithm, accurately adapts to the complex characteristics of the slag and temperature fluctuations, dynamically optimizes the water quenching parameters, thereby improving the water quenching effect and reducing equipment wear and pipeline blockage.

[0011] (2) The present invention detects water quenching data, analyzes the angle control demand coefficient, water volume control demand coefficient and water pressure control demand coefficient of the slag flushing pump, determines the current control instruction of the slag flushing pump, and establishes a dynamic response relationship between the water quenching data and the adjustment instruction, thereby effectively ensuring the consistency of the slag water quenching effect and realizing the refined control of the slag water quenching.

[0012] (3) The present invention calculates the water pressure control demand coefficient of the slag flushing pump according to the diameter of each water-quenched slag in the water-quenched slag pool, accurately adapts the slag flushing demand of slags of different particle sizes, avoids the problem of insufficient slag flushing or excessive flushing of equipment due to improper water pressure, and thus improves the slag flushing efficiency and quality.

[0013] (4) The present invention inputs the content of each chemical element and the dynamic viscosity in the raw material into the Takagi-Sugeno fuzzy reasoning metallurgical model to obtain the expected composition matrix, expected viscosity value and expected output range of the slag, accurately predicts the composition parameters of the slag, and thus improves the accuracy of the subsequent preset control of the slag flushing pump, thereby achieving an improvement in energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0015] Figure 1 It is a schematic diagram of the connection of each step of the method of the present invention.

[0016] Figure 2 A schematic diagram of the connection steps of the adaptive control algorithm of the present invention for calculating preset control instructions for the slag flushing pump.

[0017] Figure 3 It is a schematic diagram of the connection of each process of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Embodiment 1

[0020] See also Figure 1 As shown, the present invention provides a slag treatment control method for an electric arc furnace based on a water quenching method, the method comprising: S1, obtaining the content of each chemical element in the raw material and the dynamic viscosity, and inputting the raw material data into a Takagi-Sugeno fuzzy reasoning metallurgical model to obtain an expected composition matrix, an expected viscosity value and an expected output range of the slag.

[0021] It should be added that the content of each chemical element and the dynamic viscosity of the raw material are obtained through a multi-sensor fusion device, which refers to a multi-sensor fusion detection device using an integrated laser induced breakdown spectrometer (LIBS) and a rotating viscosity probe. The advantages of using a multi-sensor fusion device are: 1. A single sensor can only detect a certain characteristic of the raw material, while a multi-sensor fusion device can simultaneously obtain multi-dimensional data such as the content of chemical elements and the dynamic viscosity coefficient, providing more comprehensive information for subsequent analysis. 2. Improve detection accuracy: Different sensors have different measurement principles and error sources. Through multi-sensor fusion, the data of multiple sensors can be used for cross-validation and data fusion, thereby reducing measurement errors and improving detection accuracy. 3. Real-time and high efficiency: The device can work simultaneously and obtain multiple data in a short time. There is no need to perform multiple tests or transfers on the raw materials, saving detection time, improving detection efficiency, and providing data support for real-time decision-making in the production process. In the preparation stage of smelting in an ore-heated furnace, the physical properties of the raw materials can be quickly obtained, which enables operators to adjust the production process and parameters in time to ensure efficient production.

[0022] It should be added that the Takagi-Sugeno fuzzy reasoning metallurgical model is a hybrid reasoning system that combines fuzzy logic and mathematical models. The following is a detailed explanation of the model in the slag treatment scenario: The Takagi-Sugeno (TS) fuzzy model consists of the following two parts: The premise part is a rule base based on fuzzy logic, which divides the input variables (such as the proportion of chemical elements and dynamic viscosity) through fuzzy sets. The conclusion part corresponds to a local linear mathematical model (such as a polynomial equation) for each fuzzy rule, and the output result is a deterministic value or interval. Application process in metallurgical scenarios: (1) Fuzzification of input variables: the content of each chemical element of the input raw material and the dynamic viscosity of the raw material, fuzzy set partitioning: the input parameters are divided into multiple fuzzy sets according to metallurgical experience, and the membership function is defined.

[0023] (2) Fuzzy rule base: Each rule is generated by expert experience or historical data training, and the parameters of the conclusion part are determined by regression analysis or optimization algorithm.

[0024] (3) Reasoning and defuzzification: The activation weight of each rule is calculated based on the membership of the input parameters, and the final output is the weighted average of the outputs of each rule. Output results: Expected component matrix: the predicted proportion of each component in the slag; expected viscosity value: the key indicator of slag fluidity; expected output range: the output range after comprehensive consideration of process fluctuations.

[0025] Exemplarily, the raw material data is input into the Takagi-Sugeno fuzzy reasoning metallurgical model to obtain the expected composition matrix, expected viscosity value and expected output range of the slag, including: S1-1, normalizing the content of each chemical element to obtain the proportion of each chemical element, and defining the fuzzy subset membership function for it.

[0026] It should be added that the normalization process is: dividing the content value of each chemical element by the sum of the content values ​​of all chemical elements, so as to obtain the proportion of each chemical element.

[0027] S1-2. Based on the membership of the fuzzy subset to which each chemical element belongs, the corresponding rules are matched in the pre-set fuzzy reasoning rule library, and reasoning calculations are performed according to the membership of its antecedent and the functional relationship of its consequent to obtain the fuzzy reasoning results of each chemical component.

[0028] It should be added that the process of establishing the pre-set fuzzy inference rule base is as follows: (1) Collecting and organizing data: Under laboratory conditions, conducting slag smelting experiments with different raw material ratios and different process parameters (such as temperature, pressure, reaction time, etc.), recording the chemical element content of the raw materials, the final composition of the slag, viscosity and output data in each experiment, and collecting a large amount of data in the actual production process, including raw material information of different batches, production operation records and corresponding slag product data.

[0029] (2) Determine fuzzy linguistic variables and fuzzy subsets: Select factors related to slag composition, viscosity and output as fuzzy linguistic variables, such as the content of chemical elements in the raw materials, smelting temperature, reaction time, etc. as input variables, and the chemical composition, viscosity and output of the slag as output variables. At the same time, define appropriate fuzzy subsets for each fuzzy linguistic variable. For example, for the chemical element content, define it as fuzzy subsets such as "low", "medium", and "high"; for slag viscosity, define fuzzy subsets such as "extremely low", "low", "medium", "high", and "extremely high". Each fuzzy subset has a corresponding membership function, which is used to describe the degree to which the variable belongs to the subset.

[0030] (3) Summary of expert knowledge and experience: Invite experts in the field of metallurgy to evaluate and judge the slag output characteristics under different combinations of input variables based on their professional knowledge and rich experience, and then transform the expert judgment and experience into specific rules, such as "If the raw material contains High content and The content is low, then the silicate content in the slag is high". These rules are the basis of the fuzzy reasoning rule base.

[0031] (4) Data analysis and rule optimization: Use data mining technology to analyze the collected experimental data and production data, and explore the potential relationships and patterns between the data. For example, through association analysis, find out the strong association rules between the element content of raw materials and the composition of slag, and then use the existing data to verify the initially established rules and check the accuracy and rationality of the rules. When it is found that some rules deviate greatly from the actual data, the rules are adjusted and optimized in a timely manner, such as redefining fuzzy subsets, adjusting membership functions, or modifying the conditions and conclusions of the rules.

[0032] (5) Improvement and updating of the rule base: With the continuous accumulation of new experimental data and production data, the rule base is regularly updated and improved. Through continuous learning, the rule base can adapt to different production conditions and changing raw material characteristics. At the same time, a feedback mechanism is established to compare and analyze the slag detection results in actual production with the prediction results of the fuzzy reasoning model. When there are large differences, the reasons are promptly identified and the rule base is corrected to improve the accuracy and reliability of the fuzzy reasoning model.

[0033] S1-3. Multiply the fuzzy reasoning results of each chemical component by the preset weight of each chemical component to obtain the expected content of each chemical component, and then generate the expected composition matrix of the slag.

[0034] In a specific embodiment, suppose we have an electric arc furnace, and the raw materials processed mainly involve four chemical elements: iron (Fe), silicon (Si), calcium (Ca), and aluminum (Al). Through detection and analysis, the initial content of each chemical element in the raw materials is: 50g of iron, 20g of silicon, 15g of calcium, and 15g of aluminum. These element contents are normalized: the total content is 100g. Then the proportion of iron is 0.5, the proportion of silicon is 0.2, the proportion of calcium is 0.15, and the proportion of aluminum is 0.15.

[0035] The fuzzy subset membership function is defined for each chemical element: the fuzzy subsets of iron are defined as "high", "medium" and "low", and its membership function is set to "high": when the content is greater than or equal to 0.4, the membership is 1, and when it is less than 0.3, the membership is 0, and it changes linearly between 0.3 and 0.4. At this time, the membership of iron in the "high" fuzzy subset is 1.

[0036] “Medium”: The membership changes linearly from 0 to 1 between 0.2 and 0.3, and changes linearly from 1 to 0 between 0.3 and 0.4. The membership of the iron element in the “Medium” fuzzy subset is 0.

[0037] “Low”: When the content is less than or equal to 0.2, the membership is 1, and when it is greater than 0.3, the membership is 0. It changes linearly between 0.2 and 0.3. The membership of iron element in the “low” fuzzy subset is 0.

[0038] Similarly, corresponding fuzzy subsets and membership functions are defined for silicon, calcium and aluminum elements respectively.

[0039] Fuzzy reasoning calculation: In the pre-set fuzzy reasoning rule base, there is a rule, for example: if the iron element belongs to the "high content" fuzzy subset and the silicon element belongs to the "medium content" fuzzy subset, then a related compound component in the slag will be at a higher level. Reasoning calculation is performed based on the membership of the fuzzy subset to which each element belongs and the membership of the rule antecedent and the functional relationship of the consequent in the rule base. If the fuzzy reasoning result of the expected chemical composition A of the iron element in the slag is 0.8, the fuzzy reasoning result of the chemical composition A of the silicon element is 0.3, the calcium element is 0.1, and the aluminum element is 0.2.

[0040] Generate the expected slag composition matrix: In the preset chemical composition A, the weights of iron, silicon, calcium and aluminum elements are 0.5, 0.3, 0.1 and 0.1 respectively, then the expected content of chemical composition A = 0.8×0.5+0.3×0.3+0.1×0.1+0.2×0.1=0.52.

[0041] In the same way, the other chemical components in the slag are calculated, and finally the expected composition matrix of the slag is obtained, for example: [A: 0.52, B: 0.28, C: 0.15, C: 0.05].

[0042] S1-4. According to the fuzzy algorithm, the expected viscosity value and expected output range of the slag are obtained by similar analysis steps to the expected slag composition matrix.

[0043] The embodiment of the present invention inputs the content of each chemical element and the dynamic viscosity in the raw material into the Takagi-Sugeno fuzzy reasoning metallurgical model to obtain the expected composition matrix, expected viscosity value and expected output range of the slag, accurately predicts the composition parameters of the slag, and thus improves the accuracy of the subsequent slag flushing pump preset control, thereby achieving an improvement in energy efficiency.

[0044] S2. Acquisition The temperature of each temperature measuring point is used to calculate the preset control instructions of the slag flushing pump through the adaptive control algorithm.

[0045] It should be added that The temperature of each temperature measurement point is obtained through a distributed optical fiber temperature measurement system installed on the wall of the ore-heating furnace. The advantages of choosing a distributed optical fiber temperature measurement system to obtain temperature are: 1. Fully distributed continuous temperature measurement capability: A single optical fiber can achieve kilometer-level continuous temperature monitoring, breaking through the spatial limitations of traditional point sensors, and completely covering the complex spatial temperature field of the ore-heating furnace. At the same time, it supports the real-time generation of three-dimensional temperature cloud maps and accurately locates local high-temperature areas and temperature anomalies. 2. Adaptability to extreme environments: Using quartz optical fiber as the sensing medium, it can withstand high-temperature environments above 1000°C, has an intrinsically safe design, no electrical signal transmission, strong anti-electromagnetic interference ability, excellent anti-corrosion performance, and can resist chemical erosion during slag treatment. 3. High-precision dynamic monitoring: The temperature resolution can reach 0.1°C, the spatial resolution is better than 10cm, and the response time is <1 second, which meets the monitoring needs of the rapidly changing slag treatment process, supports μW-level weak light signal detection, and realizes reliable temperature measurement in extremely low-loss environments.

[0046] It should be added that the adaptive control algorithm is a control method that can automatically adjust the control strategy and parameters according to changes in the environment, parameters, etc. during the operation of the system to keep the system in the optimal or satisfactory operating state. It does not require accurate knowledge of the mathematical model of the controlled object in advance, but adjusts the parameters of the controller according to certain adaptive laws to adapt to changes in system characteristics by real-time monitoring of the input and output information of the system.

[0047] See also Figure 2 As shown, exemplarily, the preset control instruction of the slag flushing pump is calculated by the adaptive control algorithm, including: S2-1, based on The temperature of each temperature measuring point is used to calculate the preset control water volume of the slag flushing pump .

[0048] Furthermore, the preset control water volume of the slag flushing pump is calculated, including: S2-1-1, The temperature of each measuring point is recorded as , is the temperature measurement point number, .

[0049] S2-1-2. Calculate the average temperature of each temperature measuring point to obtain the average temperature in the ore-fired furnace, which is recorded as , and the expected viscosity of the slag is recorded as , Indicates time.

[0050] S2-1-3, preset control water volume of slag flushing pump , , , , and Set the reference proportional coefficient, integral coefficient, slag flushing start time and slag flushing end time respectively. is the number of temperature measurement points.

[0051] It should be added that It is a measure of the temperature dispersion degree of each temperature measuring point in the ore furnace. By calculating the average of the sum of the squares of the differences between the temperature of each temperature measuring point and the average temperature and then taking the square root, the temperature dispersion degree is obtained, which reflects the unevenness of the temperature distribution in the furnace. Indicates the start time of slag flushing End time of slag flushing During this period, the expected viscosity and integral coefficient of the slag The integral of the product. This takes into account the cumulative effect of the change in slag viscosity over time during the entire slag flushing process on the amount of water required for slag flushing.

[0052] It should be added that Setting process: When studying the influence of temperature gradient difference on water flow, we take some factors related to temperature gradient difference as the factors of orthogonal test. For example, the pressure in the furnace, the ratio of raw materials, smelting time, etc. These factors may indirectly affect the temperature distribution, and then affect the relationship between temperature gradient difference and water flow. The setting process is as follows: (1) Level setting: different levels are set for each factor. For example, the pressure in the furnace can be set to three levels: low, medium, and high. The raw material ratio can be set according to different proportion ranges. The smelting time can be set to several different duration levels.

[0053] (2) Experimental design and implementation: The experiments were arranged according to the orthogonal table, and the corresponding temperature gradient difference and water flow rate data were recorded for each experiment.

[0054] (3) Data analysis: By analyzing the test data, such as variance analysis, determine the significance of each factor on the water flow rate. In this way, find the best correlation between the temperature gradient difference and the water flow rate under different conditions, and determine the appropriate proportional coefficient. , for example, when the slag When the content is >0.45, determine Integration coefficient Obtained through the principle of Arrhenius equation: The general form of Arrhenius equation is ,in is the reaction rate constant, is the pre-factor, is the activation energy, is the gas constant, is the absolute temperature. It shows the exponential relationship between the chemical reaction rate and temperature. As the temperature rises, the reaction rate constant increases and the reaction rate accelerates. Application: In the water flow regulation formula, the viscosity compensation term Viscosity with slag The viscosity of slag is closely related to the physical and chemical properties of slag, among which the melting point of slag is is an important factor.

[0055] The correction is based on the Arrhenius equation, Expressed as ,here Similar to the pre-exponential factor, Take 60-80 J / mol, which reflects the energy required to overcome resistance when the internal structure of the slag changes or flows. When the index changes, The value of will also change, thus adjusting The size of , which can more accurately consider the effect of slag melting point on the expected viscosity value in real time The impact on water flow.

[0056] It should be added that and The method of obtaining the slag content is to extract the slag content interval corresponding to each slag flushing time from the slag treatment control cloud platform of the slag furnace, and then match and compare the middle value of the expected slag output interval with the slag content interval corresponding to each slag flushing time, and obtain the slag flushing time period corresponding to the expected slag output, and then set the time to start the slag flushing pump as , the expected output of slag from the ore-heat furnace corresponds to the time after the slag flushing period as .

[0057] S2-2. Extract the length and diameter of the pipeline between the submerged arc furnace and the water quenching tank from the submerged arc furnace slag treatment control cloud platform, and then calculate the preset control water pressure of the slag flushing pump .

[0058] Furthermore, the preset control water pressure of the slag flushing pump is calculated, including: S2-2-1, recording the length and diameter of the pipeline between the ore-fired furnace and the water quenching tank as and .

[0059] S2-2-2. Extract the local resistance coefficients of the pipeline between the ore-fired furnace and the water quenching tank from the ore-fired furnace slag treatment control cloud platform, and sum them to obtain the local resistance coefficient of the pipeline, which is recorded as .

[0060] S2-2-3. Statistics of preset control water pressure of slag flushing pump , ,in , , and They are the safety factor, resistance coefficient along the way, slag flow rate and slag density for setting reference respectively.

[0061] It should be added that middle It is the safety factor for setting reference. Adding 1 is to increase a certain safety margin based on the calculation result to deal with possible unconsidered factors or operating condition fluctuations and ensure the safety of system operation. middle It is the resistance coefficient along the way, which reflects the resistance characteristics along the way caused by factors such as friction with the inner wall of the pipeline when the slag flows in the pipeline. is the length of the pipeline between the submerged arc furnace and the water quenching tank, is the diameter of the pipe, It reflects the influence of the geometric dimensions of the pipeline on the resistance along the way. The longer the length and the smaller the diameter, the greater the resistance along the way. It is the sum of the local resistance coefficients of the pipeline. It is obtained by extracting and summing the local resistance coefficients from the slag treatment control cloud platform of the ore-fired furnace. It represents the total resistance generated by local components such as elbows and valves in the pipeline. This part describes the resistance characteristics of the pipeline system as a whole. middle is the slag density, is the slag flow rate. These two parameters reflect the physical properties of the slag itself. Similar to the expression related to kinetic energy in fluid dynamics, the influence of the kinetic energy of slag flow on the required water pressure is reflected here. The formula multiplies the above parts and takes various factors into consideration to calculate the preset control water pressure of the slag flushing pump. .

[0062] It should be added that the preset control water pressure of the slag pump The total pressure loss needs to be overcome, and a certain safety margin must also be considered. Generally, the safety margin is 10%-20% of the total pressure loss, that is, the safety factor The value is 0.1-0.2.

[0063] It should be added that Setting method: Build a simulation device similar to the actual slag treatment system of the submerged arc furnace in the laboratory, use slag or simulated medium close to the actual situation, and conduct flow experiments under different flow rates and pipeline conditions. By measuring the pressure difference and flow rate at both ends of the pipeline, the Darcy-Weisberg formula is used to infer the resistance coefficient along the way. After multiple experiments, the experimental data were comprehensively analyzed and the middle value of the along-the-way resistance coefficient was selected as the reference along-the-way resistance coefficient.

[0064] It should be added that The method of obtaining: extract the middle value from the expected slag production range as the expected slag production , and according to the density of the slag, the slag flow rate is converted into volume flow rate , The cross-sectional area of ​​the pipe is , then the slag flow rate is: .

[0065] It should be added that How to obtain : Estimate the density of slag based on the slag composition matrix. A commonly used method is the extended form of Kopp's law, assuming that the slag is composed of n components and the particle size of each component is , the density of each component is , then the density of the slag It can be approximately expressed as: .

[0066] S2-3, using the preset control water volume and preset control water pressure of the slag flushing pump as the preset control instructions of the slag flushing pump.

[0067] The embodiment of the present invention uses an adaptive algorithm to calculate the slag flushing pump control instructions based on the expected slag composition matrix, viscosity, production range and temperature, accurately adapts to the complex characteristics of the slag and temperature fluctuations, dynamically optimizes the water quenching parameters, thereby improving the water quenching effect and reducing equipment wear and pipeline blockage.

[0068] S3, execute the preset control instructions of the slag flushing pump, detect the water quenching data when the high-temperature liquid slag contacts with water for water quenching, and dynamically adjust the control instructions of the slag flushing pump.

[0069] It should be added that the water quenching data includes: the actual output of slag from the electric arc furnace, the center position coordinates of the slag pile in the water quenching tank, the distribution uniformity of the water-quenched slag, the reflux rate of the slag flushing water, the real-time temperature and real-time steam pressure, and the diameter of each water-quenched slag in the water-quenching slag pool.

[0070] It should be added that the actual output of slag from the electric arc furnace is obtained through a thermal imager. Since the slag has a high temperature, the thermal imager can capture the thermal radiation image of the slag. According to the temperature distribution and shape of the slag in the thermal image, the actual output of the slag can be estimated using image analysis technology.

[0071] It should be added that the coordinates of the center position of the slag pile are obtained by a three-dimensional laser scanner installed on the top of the water-quenching slag pool, and the distribution uniformity of the water-quenching slag is obtained by ultrasonic sensors arranged in a ring along the inner wall of the water-quenching tank. The slag layer thickness distribution is analyzed by the echo signal.

[0072] It should be added that the reflux rate of the slag flushing water is obtained by the electromagnetic flowmeter installed on the reflux pipe between the cold water pool and the water quenching tank, the interval between each collection in the water quenching tank is obtained by an industrial-grade timer, the real-time temperature of the water quenching tank is obtained by an infrared thermometer installed inside the water quenching tank, and the real-time steam pressure of the water quenching tank is obtained by a pressure sensor installed inside the water quenching tank.

[0073] It should be added that the diameter of each water-quenched slag in the water-quenched slag pool is obtained by a laser particle size analyzer.

[0074] Exemplarily, the control instructions for dynamically adjusting the slag flushing pump include: S3-1, extracting the center position coordinates of the slag pile, the distribution uniformity of the water-quenched slag and the reflux speed of the slag flushing water from the water quenching data, and calculating the angle control demand coefficient of the slag flushing pump .

[0075] Furthermore, the statistical angle control demand coefficient of the slag flushing pump includes: S3-1-1, based on the position coordinates of the center of the slag pile, statistical deviation coefficient of the slag pile .

[0076] Furthermore, the statistical deviation coefficient of the slag pile includes: S3-1-1-1, extracting the position coordinates of the center of the slag groove in the water quenching tank from the slag treatment control cloud platform of the electric arc furnace.

[0077] S3-1-1-2. Based on the position coordinates of the slag pile center and the slag ditch center, the deviation distance of the slag pile is obtained by the Euclidean distance formula, which is recorded as .

[0078] It should be added that the explanation of the Euclidean distance formula is: Suppose there are two points on a two-dimensional plane and , then the formula for the Euclidean distance between points A and B is: .

[0079] S3-1-1-3, record the amount of slag pile as .

[0080] S3-1-1-4. Statistical deviation coefficient of slag pile , ,in, and Set the reference allowable deviation distance and allowable accumulation amount respectively.

[0081] It should be added that in the treatment of slag from an ore-fired furnace, the ideal state is that the slag is evenly deposited in a suitable position near the slag ditch, but in actual production, the slag pile may deviate from the ideal position. The larger the value, the further the slag pile deviates from the ideal position. Permissible deviation distance from the set reference The difference is the relative value of the deviation distance, which is used to measure the degree of actual deviation distance compared with the maximum allowable deviation distance, that is, the deviation in position.

[0082] Consider the accumulation factor It represents the accumulation amount of the slag pile. The amount of accumulation will also affect the slag treatment process. For example, too much accumulation may affect the effect of subsequent slag flushing and other operations. and Divide them to get the relative value of the accumulation amount, which is used to reflect the actual accumulation amount relative to the maximum allowable accumulation amount.

[0083] Multiply the above two relative values, that is , and then comprehensively consider the differences between the slag pile and the set allowable conditions in terms of position deviation and accumulation. The larger the value, the more serious the deviation of the slag pile from the permitted state in terms of position and accumulation, that is, the larger the deviation coefficient, which means that the current state of the slag pile needs more attention and adjustment in order to better carry out subsequent slag treatment work.

[0084] S3-1-2, record the distribution uniformity of water-quenched slag and the distribution uniformity interval of water-quenched slag as and .

[0085] S3-1-3. Statistical uniformity deviation coefficient of water-quenched slag , .

[0086] S3-1-4, based on the reflux rate of slag flushing water, according to The deviation coefficient of the reflux velocity of the slag flushing water is obtained by the same statistical method and recorded as .

[0087] S3-1-5. Select the maximum value from the slag pile deviation coefficient, water quenching slag uniformity deviation coefficient and slag flushing water return speed deviation coefficient as the angle control demand coefficient of the slag flushing pump, recorded as .

[0088] S3-2. Obtain the actual output of the submerged arc furnace from the water quenching data, as well as the real-time temperature and real-time steam pressure of the water quenching tank, calculate the temperature deviation ratio and steam pressure deviation ratio of the water quenching tank, and calculate the water volume control demand coefficient of the slag flushing pump in combination with the expected output of the submerged arc furnace. .

[0089] Furthermore, the temperature deviation ratio and steam pressure deviation ratio of the water quenching tank are calculated, and the water volume control demand coefficient of the slag flushing pump is calculated in combination with the expected output of the electric arc furnace, including: S3-2-1, extracting the reference temperature range of the water quenching tank from the electric arc furnace slag treatment control cloud platform, and extracting the middle value therefrom as the reference temperature of the water quenching tank.

[0090] S3-2-2. Subtract the real-time temperature of the water quenching tank from the reference temperature, and use the absolute value of the difference as the real-time temperature difference of the water quenching tank.

[0091] S3-2-3. The difference between the maximum and minimum values ​​in the reference temperature range of the water quenching tank is used as the reference temperature difference of the water quenching tank.

[0092] S3-2-4. The ratio of the real-time temperature difference of the water quenching tank to the reference temperature difference is taken as the temperature deviation ratio of the water quenching tank, which is recorded as .

[0093] S3-2-5. Based on the real-time steam pressure of the water quenching tank, the steam pressure deviation ratio of the water quenching tank is obtained by the same statistical method as the temperature deviation ratio of the water quenching tank. .

[0094] S3-2-6. Extract the middle value from the expected output range of the submerged arc furnace as the expected output of the submerged arc furnace, and record the expected output and actual output of the submerged arc furnace as and .

[0095] S3-2-7. Calculate the water volume control demand coefficient of the slag flushing pump , , and They are the temperature deviation ratio and steam pressure deviation ratio of the reference set, , and are the weights of setting the reference temperature deviation coefficient, steam pressure deviation coefficient and output deviation coefficient respectively. , .

[0096] It should be added that the temperature deviation is related to: is the temperature deviation ratio of the water quenching tank, which is obtained by the ratio of the real-time temperature difference of the water quenching tank to the reference temperature difference, reflecting the degree to which the current water quenching tank temperature deviates from the reference temperature range. To set the reference temperature deviation ratio, it represents the temperature deviation reference value under ideal or normal working conditions. What is calculated is the relative change of the real-time temperature deviation ratio relative to the reference temperature deviation ratio, which reflects the influence of the current temperature conditions on the water volume control demand. The relevant part of the steam pressure deviation is: is the steam pressure deviation ratio of the water quenching tank. The calculation method is similar to the temperature deviation ratio. It reflects the degree to which the current steam pressure of the water quenching tank deviates from the reference range. To set the reference steam pressure deviation ratio, it is the reference standard of steam pressure deviation. The calculation is the relative change of the real-time steam pressure deviation ratio relative to the reference steam pressure deviation ratio, indicating the effect of steam pressure conditions on water volume control requirements. and is the expected output of the ore-fired furnace, which is obtained by extracting the middle value from the expected output range. is the actual output of slag from the submerged arc furnace, It reflects the proportional relationship between expected output and actual output, and reflects the impact of output changes on the demand for water volume regulation of slag flushing pumps. Different outputs will produce different amounts of slag, and the amount of water required for slag flushing will also be different.

[0097] It should be added that the temperature of the water quenching tank has a significant impact on the physical state of the slag. If the temperature is too high or too low, the viscosity and other properties of the slag will change. For example, when the temperature is too high, the viscosity of the slag decreases, but the excessive fluidity may cause splashing and other problems. Therefore, the slag pump needs to adjust the water volume in time to maintain the appropriate water quenching effect to ensure that the slag can be processed smoothly. Therefore, the weight corresponding to the temperature deviation has the greatest impact on the water volume control demand. The steam pressure in the water quenching tank will affect the efficiency and stability of the water quenching process. When the steam pressure is abnormal, the heat exchange and other links of the water quenching process will be disturbed, which will affect the cooling and processing effect of the slag. Although it does not directly change the physical properties of the slag like temperature, it is also necessary to balance the operating state of the system by adjusting the water volume of the slag pump to ensure that the entire slag flushing process is normal, so the weight of the steam pressure is in the middle. The output deviation of the submerged arc furnace does affect the amount of slag produced, and thus affects the water demand of the slag pump. However, the change in output is relatively slow and predictable. The production plan usually has certain plans and expectations for the output. In actual production, other auxiliary measures (such as adjusting the production rhythm, etc.) can be used to coordinate the change in output, rather than simply relying on the adjustment of the water volume of the slag pump. Compared with the immediate impact of temperature and steam pressure, the impact of output deviation on the water volume control demand coefficient is relatively small, so its weight is the smallest, so it is set , in order to facilitate analysis, The specific value can be 0.5. The specific value can be 0.3. The specific value can be 0.2.

[0098] S3-3. Extract the diameter of each water-quenched slag in the water-quenched slag pool from the water-quenched slag data and sort them. After sorting, take the specific particle size value, calculate the average diameter and the standard deviation of the particle size distribution, and then calculate the water pressure control demand coefficient of the slag flushing pump. .

[0099] Furthermore, the water pressure control demand coefficient of the slag flushing pump is calculated, including: S4-3-1, sorting the diameters of the water-quenched slags in the water-quenched slag pool from large to small, extracting the particle size values ​​corresponding to the particle size reaching 10%, 50% and 90%, and recording them as , and .

[0100] It should be added that in the statistics of particle size distribution, , and is a parameter used to describe the particle size characteristics. It means the particle size value corresponding to the cumulative particle size reaching 10% after all the water-quenched slag particle sizes are sorted from small to large, that is, 10% of the water-quenched slag particle sizes are less than or equal to , Also called median particle size, it refers to the particle size value corresponding to when the cumulative particle size reaches 50%, which means that half (50%) of the water-quenched slag has a particle size less than or equal to , which reflects the intermediate level of particle size, It indicates the particle size value corresponding to when the cumulative particle size reaches 90%, that is, 90% of the water-quenched slag particle size is less than or equal to , the remaining 10% of the slag has a particle size larger than , which reflects the situation of larger particle size particles.

[0101] S3-3-2. Calculate the average diameter of each water-quenched slag to obtain the average diameter, which is recorded as At the same time, the standard deviation of the particle size distribution of water-quenched slag is calculated by the standard deviation formula, which is recorded as .

[0102] S3-3-3. Calculate the water pressure control demand coefficient of the slag flushing pump , , To set the reference slag median particle size, , and They are the reference particle size deviation coefficient, distribution uniformity coefficient and weight of coarse particle proportion, , .

[0103] It should be added that Setting: Extract the particle size data of water-quenched slag in the historical treatment process of ore-blast furnace slag from the ore-blast furnace slag treatment control cloud platform, calculate the median particle size of the particle size data, and after statistical analysis of multiple groups of particle size data, extract the mode as the setting reference median particle size.

[0104] It should be added that The calculation is the relative deviation between the median particle size of the current water-quenched slag and the median particle size of the reference slag. This item represents the impact of particle size deviation on the water pressure control demand coefficient. The larger the deviation, the more it means that the current slag particle size characteristics are significantly different from expectations, and the water pressure may need to be adjusted, which will contribute more to the water pressure control demand coefficient. is the standard deviation of the particle size distribution of the water-quenched slag, Reflects the degree of dispersion of particle size; is the average diameter, It reflects the uniformity of particle size distribution. The larger the ratio, the more uneven the particle size distribution. This item represents the effect of the uniformity of particle size distribution on the water pressure regulation demand coefficient. The more uneven the distribution is, the more water pressure needs to be adjusted to accommodate slag of different particle sizes, and the greater the impact on the water pressure regulation demand coefficient. and Ratio It can reflect the proportion of coarse particles (larger particle size particles) in all particles. The larger the ratio, the higher the proportion of coarse particles. This item represents the effect of the coarse particle ratio on the water pressure regulation demand coefficient. The higher the coarse particle ratio, the greater the water pressure required to flush the slag, and the greater the contribution to the water pressure regulation demand coefficient.

[0105] It should be added that the median particle size of water-quenched slag reflects the overall level of slag particle size. Changes in the median particle size directly affect the fluidity of the slag and the friction resistance to the pipeline. For example, as the median particle size increases, the slag particles become relatively coarser, and greater water pressure is required to push them when flowing in the pipeline, which has a more direct and significant impact on the demand for water pressure regulation. Therefore, the particle size deviation factor plays a key role in determining the water pressure of the slag flushing pump, so its weight is the largest. The uniformity of the slag particle size distribution will affect its flow state in the pipeline. When the particle size distribution is uneven, particles of different sizes are prone to stratification and blockage, which in turn affects the slag flushing effect, and the water pressure needs to be adjusted to ensure smooth slag flushing. Although it is not as direct as the impact of the median particle size change, it also plays an important role in water pressure regulation, so its weight is in the middle. The proportion of coarse particles has a certain impact on water pressure. A high proportion of coarse particles may require a higher water pressure. However, in the actual slag flushing process, the impact of the proportion of coarse particles is relatively more indirect, and can be assisted by other methods (such as adjusting the slag flushing time, etc.). Compared with the median particle size and particle size distribution uniformity, its impact on the water pressure control demand coefficient is relatively small, so its weight is the smallest, so it is set , in order to facilitate analysis, The specific value can be 0.5. The specific value can be 0.3. The specific value can be 0.2.

[0106] The embodiment of the present invention calculates the water pressure control demand coefficient of the slag flushing pump according to the diameter of each water-quenched slag in the water-quenched slag pool, accurately adapts the slag flushing demand of slag with different particle sizes, avoids the problem of insufficient slag flushing or excessive flushing of equipment due to improper water pressure, and thus improves the slag flushing efficiency and quality.

[0107] S3-4, the angle control demand coefficient of the slag flushing pump is greater than the set reference angle control demand coefficient as condition 1, and the water volume control demand coefficient of the slag flushing pump is greater than the set reference water volume control demand coefficient as condition 2, and at the same time, the water pressure control demand coefficient of the slag flushing pump is greater than the set reference water pressure control demand coefficient as condition 3.

[0108] S3-5. When condition 1 is met, angle control will be performed as the current control instruction of the slag flushing pump.

[0109] S3-6. When condition 2 is met, water volume regulation will be performed as the current control instruction of the slag flushing pump.

[0110] S3-7. When condition 3 is met, water pressure regulation will be performed as the current control instruction of the slag flushing pump.

[0111] S3-8: When conditions 1, 2, and 3 are not met, the current regulation will be maintained as the current control instruction of the slag flushing pump.

[0112] The embodiment of the present invention detects water quenching data, analyzes the angle control demand coefficient, water volume control demand coefficient and water pressure control demand coefficient of the slag flushing pump, determines the current control instructions of the slag flushing pump, and establishes a dynamic response relationship between the water quenching data and the adjustment instructions, thereby effectively ensuring the consistency of the slag water quenching effect and realizing refined control of the slag water quenching.

[0113] S4. After the water quenching is completed, the cold water is separated and recycled through sedimentation, cooling tower cooling and inclined plate sedimentation device.

[0114] Embodiment 2

[0115] As an embodiment of the present invention, refer to Figure 3 , flow chart of water quenching treatment of slag from an ore-heating furnace, wherein the ore-heating furnace is the core production equipment, which produces liquid slag by high-temperature smelting of ore (such as ferroalloy, calcium carbide, etc.).

[0116] The function of the water quenching tank is to cool rapidly: the high-temperature liquid slag is directly contacted with high-pressure water, and the heat is taken away by the latent heat of water vaporization, so that the slag is instantly cooled and broken.

[0117] The water quenching slag pool is used for slag-water separation: the slag particles after water quenching are deposited at the bottom of the pool, and the hot water flows to the hot water pool through a hot water pump.

[0118] The function of the hot water pool is to store hot water: collect hot water overflowing from the water quenching tank (temperature is about 60-90°C), and also have a heat buffer function to balance the water temperature fluctuation of the system to avoid directly affecting the load of the cooling tower.

[0119] The function of the cooling tower is to cool down the hot water in the hot water pool to 20-30°C through evaporative cooling or forced ventilation for circulation in the cold water pool.

[0120] The function of the cold water pool is to store cold water: store cooling water after being cooled by the cooling water tower, and provide a stable low-temperature water source for the water quenching tank.

[0121] The function of the water replenishment tank is to replenish the water source: replenish the system with water carried away by evaporation, leakage or slag, and maintain the water balance of the system.

[0122] In the water quenching operation process of the submerged arc furnace of the present invention, firstly, the submerged arc furnace produces liquid slag by high-temperature smelting ore, and the high-temperature liquid slag flows out of the submerged arc furnace and directly enters the water quenching tank connected thereto.

[0123] A slag flushing pump is arranged in the water quenching tank. When the high-temperature slag enters the water quenching tank, a large amount of high-pressure water is sprayed out from the nozzle of the slag flushing pump and instantly contacts the slag. The latent heat of vaporization of water quickly takes away the heat of the slag, causing the slag to cool quickly and break into small particles, thus realizing the granulation of the slag.

[0124] The slag-water mixture after water quenching flows from the water quenching tank into the water quenching slag pool. In the water quenching slag pool, the slag and water are separated, the slag particles settle at the bottom of the pool due to gravity, and the hot water on the upper layer flows into the hot water pool through the hot water pump.

[0125] The hot water collected in the hot water pool is at a high temperature and is then transported to the cooling tower. The cooling tower lowers the temperature of the hot water through evaporative heat dissipation and forced ventilation. The cooled water is filtered and flows from the cooling tower into the cold water pool.

[0126] The cold water pool plays a role of storage and buffering, continuously providing low-temperature circulating water to the water quenching tank to ensure the stability of the water quenching process.

[0127] As the entire water quenching system operates, some water will be lost due to evaporation, being carried away with the slag, etc. This is when the water replenishment tank comes into play. The water replenishment tank replenishes water to the cold water pool to maintain the water balance in the system and ensure that the water quenching operation can run uninterruptedly for a long time.

[0128] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for controlling slag treatment of an electric arc furnace based on a water quenching method, characterized in that: The method includes: S1. Obtain the content of each chemical element and dynamic viscosity in the raw material, and input the raw material data into the Takagi-Sugeno fuzzy reasoning metallurgical model to obtain the expected composition matrix, expected viscosity value and expected output range of the slag; S2. Acquisition The temperature of each temperature measuring point is used to calculate the preset control instructions of the slag flushing pump through the adaptive control algorithm; S3, executing the preset control instructions of the slag flushing pump, detecting the water quenching data when the high-temperature liquid slag contacts with water for water quenching, and dynamically adjusting the control instructions of the slag flushing pump; S4. After the water quenching is completed, the cold water is separated and recycled through sedimentation, cooling tower cooling and inclined plate sedimentation device.

2. The method for controlling slag treatment of an electric arc furnace based on a water quenching method according to claim 1, characterized in that: The raw material data is input into the Takagi-Sugeno fuzzy reasoning metallurgical model to obtain the expected composition matrix, expected viscosity value and expected output range of the slag, including: The content of each chemical element is normalized to obtain the proportion of each chemical element, and the fuzzy subset membership function is defined for it; Based on the membership of the fuzzy subset to which each chemical element belongs, the corresponding rules are matched in the pre-set fuzzy reasoning rule library, and the reasoning calculation is performed according to the membership of its antecedent and the functional relationship of the consequent to obtain the fuzzy reasoning results of each chemical component; The fuzzy reasoning results of each chemical component are correspondingly multiplied with the preset weights of each chemical component to obtain the expected content of each chemical component, thereby generating the expected composition matrix of the slag; According to the fuzzy algorithm, the expected viscosity value and expected output range of the slag are obtained by similar analysis steps to the expected slag composition matrix.

3. The method for controlling slag treatment of an electric arc furnace based on a water quenching method according to claim 1, characterized in that: The method of calculating the preset control instructions of the slag flushing pump by using an adaptive control algorithm includes: based on The temperature of each temperature measuring point is used to calculate the preset control water volume of the slag flushing pump ; Extract the length and diameter of the pipeline between the submerged arc furnace and the water quenching tank from the submerged arc furnace slag treatment control cloud platform, and then calculate the preset control water pressure of the slag flushing pump ; The preset control water volume and preset control water pressure of the slag flushing pump are used as preset control instructions of the slag flushing pump.

4. The method for controlling slag treatment of an electric arc furnace based on a water quenching method according to claim 3, characterized in that: The preset control water volume of the statistical slag flushing pump includes: Will The temperature of each measuring point is recorded as , is the temperature measurement point number, ; The average temperature of each temperature measuring point is calculated to obtain the average temperature in the ore-arc furnace, which is recorded as , and the expected viscosity of the slag is recorded as , Indicates time; Statistics of preset control water volume of slag flushing pump , , , , and Set the reference proportional coefficient, integral coefficient, slag flushing start time and slag flushing end time respectively. is the number of temperature measurement points.

5. The method for controlling slag treatment of an electric arc furnace based on a water quenching method according to claim 3, characterized in that: The preset control water pressure of the statistical slag flushing pump includes: The length and diameter of the pipeline between the submerged arc furnace and the water quenching tank are respectively and ; The local resistance coefficients of the pipeline between the ore-fired furnace and the water quenching tank are extracted from the ore-fired furnace slag treatment control cloud platform, and the sum of the local resistance coefficients of the pipeline is obtained, which is recorded as ; Statistics of the preset control water pressure of the slag flushing pump , ,in , , and They are the safety factor, resistance coefficient along the way, slag flow rate and slag density for setting reference respectively.

6. The method for controlling slag treatment of an electric arc furnace based on a water quenching method according to claim 1, characterized in that: The control instructions for dynamically adjusting the slag flushing pump include: Extract the center coordinates of the slag pile, the distribution uniformity of the water-quenched slag, and the reflux rate of the slag flushing water from the water quenching data, and calculate the angle control demand coefficient of the slag flushing pump ; Obtain the actual output of the submerged arc furnace from the water quenching data, as well as the real-time temperature and real-time steam pressure of the water quenching tank, calculate the temperature deviation ratio and steam pressure deviation ratio of the water quenching tank, and calculate the water volume control demand coefficient of the slag flushing pump in combination with the expected output of the submerged arc furnace ; Extract the diameter of each water-quenched slag in the water-quenched slag pool from the water-quenched slag data and sort them. After sorting, take the specific particle size value, calculate the average diameter and the standard deviation of the particle size distribution, and then calculate the water pressure control demand coefficient of the slag flushing pump ; The angle control demand coefficient of the slag flushing pump is greater than the angle control demand coefficient of the set reference as condition 1, and the water volume control demand coefficient of the slag flushing pump is greater than the water volume control demand coefficient of the set reference as condition 2, and the water pressure control demand coefficient of the slag flushing pump is greater than the water pressure control demand coefficient of the set reference as condition 3; When condition 1 is met, angle control will be performed as the current control instruction of the slag flushing pump; When condition 2 is met, water volume regulation will be performed as the current control instruction of the slag flushing pump; When condition 3 is met, water pressure regulation will be performed as the current control instruction of the slag flushing pump; When conditions 1, 2, and 3 are not met, the current regulation will be maintained as the current control instruction of the slag flushing pump.

7. The method for controlling slag treatment of an electric arc furnace based on a water quenching method according to claim 6, characterized in that: The statistical angle control demand coefficient of the slag flushing pump includes: Based on the position coordinates of the slag pile center, the deviation coefficient of the slag pile is calculated ; The distribution uniformity of the water-quenched slag and the distribution uniformity interval of the water-quenched slag set as reference are respectively and ; Statistical uniformity deviation coefficient of water-quenched slag , ; Based on the reflux rate of slag flushing water, The deviation coefficient of the reflux velocity of the slag flushing water is obtained by the same statistical method and recorded as ; The maximum value is selected from the slag pile deviation coefficient, the water quenching slag uniformity deviation coefficient and the slag flushing water return velocity deviation coefficient as the angle control demand coefficient of the slag flushing pump, which is recorded as .

8. The method for controlling slag treatment of an electric arc furnace based on a water quenching method according to claim 7, characterized in that: The calculation of the temperature deviation ratio and the steam pressure deviation ratio of the water quenching tank and the water volume control demand coefficient of the slag flushing pump in combination with the expected output of the submerged arc furnace include: Extract the position coordinates of the slag groove center in the water quenching tank from the slag treatment control cloud platform of the submerged arc furnace; Based on the position coordinates of the slag pile center and the slag ditch center, the deviation distance of the slag pile is obtained by the Euclidean distance formula, which is recorded as ; The amount of slag pile is recorded as ; Coefficient of variation of statistical slag pile , ,in, and Set the reference allowable deviation distance and allowable accumulation amount respectively.

9. The method for controlling slag treatment of an electric arc furnace based on a water quenching method according to claim 6, characterized in that: The water volume control demand coefficient of the slag flushing pump is calculated, including: Extract the reference temperature range of the water quenching tank from the slag treatment control cloud platform of the ore-fired furnace, and extract the middle value as the reference temperature of the water quenching tank; The real-time temperature of the water quenching tank is subtracted from the reference temperature, and the absolute value of the difference is used as the real-time temperature difference of the water quenching tank; The difference between the maximum value and the minimum value in the reference temperature interval of the water quenching tank is used as the reference temperature difference of the water quenching tank; The ratio of the real-time temperature difference of the water quenching tank to the reference temperature difference is taken as the temperature deviation ratio of the water quenching tank, which is recorded as ; Based on the real-time steam pressure of the water quenching tank, the steam pressure deviation ratio of the water quenching tank is obtained by the same statistical method as the temperature deviation ratio of the water quenching tank. ; The middle value is extracted from the expected output range of the submerged arc furnace as the expected output of the submerged arc furnace, and the expected output and actual output of the submerged arc furnace are recorded as and ; Statistical water volume control demand coefficient of slag flushing pump , , and They are the temperature deviation ratio and steam pressure deviation ratio of the reference set, , and are the weights of setting the reference temperature deviation coefficient, steam pressure deviation coefficient and output deviation coefficient respectively. , .

10. The method for controlling slag treatment of an electric arc furnace based on a water quenching method according to claim 6, characterized in that: The statistical water pressure control demand coefficient of the slag flushing pump includes: The diameters of the water-quenched slags in the water-quenched slag pool are sorted from large to small, and the particle size values ​​corresponding to the particle size reaching 10%, 50% and 90% are extracted and recorded as , and ; The average diameter of each water-quenched slag is calculated and recorded as At the same time, the standard deviation of the particle size distribution of water-quenched slag is calculated by the standard deviation formula, which is recorded as ; Statistical water pressure control demand coefficient of slag flushing pump , , To set the reference slag median particle size, , and They are the reference particle size deviation coefficient, distribution uniformity coefficient and weight of coarse particle proportion, , .

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