Methods and systems for adjusting parameters of aluminum-based master alloy smelting equipment

Abstract

This invention relates to the field of non-ferrous metal smelting technology, specifically to a method and system for adjusting parameters of aluminum-based master alloy smelting equipment. The method includes the following steps: collecting data on the molten metal level within the aluminum-based master alloy smelting equipment; collecting changes in the molten aluminum surface level at fixed time intervals; identifying the level difference, fluctuation amplitude, and fluctuation trend; and obtaining the molten metal level fluctuation state. In this invention, temperature stability is maintained by adjusting the heating electrode power. The heat load distribution is further optimized by collecting temperature data of the furnace wall after adjustment and calculating the thermal stress distribution. This helps reduce energy waste and improve smelting efficiency. The flow state of the molten aluminum is optimized by adjusting the electromagnetic stirring method and time, resulting in more uniform metal and improved product quality. Dynamic adjustment of the smelting time ensures the continuity and efficiency of the smelting process, significantly improving the economy and product quality of the entire smelting process.

Description

Technical Field

[0001] This invention relates to the field of non-ferrous metal smelting technology, and in particular to a method and system for adjusting the parameters of aluminum-based master alloy smelting equipment. Background Technology

[0002] The field of non-ferrous metal smelting technology encompasses the extraction and processing of various non-ferrous metal raw materials, as well as the preparation of alloys. Its core content covers key steps such as raw material preparation, smelting, refining, and casting. The main objective of non-ferrous metal smelting technology is to improve the purity and properties of metals to meet industrial and application requirements. Technologies involved in the smelting process include temperature control, chemical composition adjustment, impurity removal, and the precise addition of alloying elements, all aimed at optimizing the physical and chemical properties of the metals.

[0003] The method for adjusting parameters of aluminum-based master alloy smelting equipment refers to a method for scientifically adjusting the operating parameters of smelting equipment during aluminum alloy production. This patent addresses technical aspects including precise control of temperature settings, smelting time, alloy composition ratios, and cooling rates. By adjusting these parameters, the stability of the smelting process and the consistency of the finished alloy quality can be ensured. This is achieved through a computer control system, ensuring precise parameter adjustment and process automation.

[0004] Existing technologies face challenges in smelting processes, including imprecise temperature control and low energy efficiency. Inaccurate temperature control leads to unstable metal properties, affecting product quality and applications. Inefficient energy use not only increases production costs but also imposes a significant environmental burden. Furthermore, the lack of real-time data support for adjusting operating parameters of smelting equipment in existing technologies results in lags in adjustments, impacting production continuity and flexibility. These shortcomings limit improvements in production efficiency and product quality stability, making it difficult for non-ferrous metal smelting enterprises to meet market demands for high-performance metallic materials. Summary of the Invention

[0005] To address the problems of inaccurate temperature control and low energy utilization in existing technologies, where inaccurate temperature control leads to unstable metal properties, affecting product quality and application, and inefficient energy utilization increases production costs and imposes a significant environmental burden, and where existing technologies lack real-time data support for adjusting operating parameters of smelting equipment, resulting in lag in adjustments and impacting production continuity and flexibility, these shortcomings limit the improvement of production efficiency and the stability of product quality. This makes it difficult for non-ferrous metal smelting enterprises to meet market demands for high-performance metal materials. This invention provides a method and system for adjusting parameters in aluminum-based master alloy smelting equipment. The technical solution is as follows:

[0006] On the one hand, a method for adjusting the parameters of aluminum-based master alloy smelting equipment is provided, the method including:

[0007] S1: Collect data on the height of the molten metal in the aluminum-based master alloy smelting equipment, collect the change in the height of the molten aluminum surface at fixed time intervals, identify the height difference, fluctuation amplitude and fluctuation trend, and obtain the fluctuation state of the molten metal surface.

[0008] S2: Based on the fluctuation state of the molten metal surface and the temperature data of the smelting equipment, calculate the temperature change rate, analyze the trend of smelting temperature change, adjust the heating electrode power, and obtain the smelting temperature adjustment result;

[0009] S3: Based on the smelting temperature adjustment results, collect the temperature data of the furnace wall of the smelting equipment after adjustment, calculate the furnace wall temperature difference between multiple points, identify the thermal stress distribution, evaluate the degree of influence of thermal stress on energy transfer, and obtain the heat load distribution of the smelting equipment.

[0010] S4: Using the heat load distribution of the smelting equipment, identify the influence of electromagnetic stirring on the flow state of molten aluminum, calculate the contribution data of liquid surface fluctuation, adjust the electromagnetic stirring method and time, and obtain the electromagnetic stirring adjustment results;

[0011] S5: Based on the electromagnetic stirring adjustment results, calculate the change in heat conduction rate of the heated area of ​​the melting equipment, set a heat conduction rate threshold, filter melting times that exceed the threshold, calculate the melting time compensation amount, and obtain the melting time adjustment results.

[0012] As a further aspect of the present invention, the molten metal surface fluctuation state includes the difference in molten metal height, the fluctuation amplitude, and the fluctuation trend; the smelting temperature adjustment result includes the heating electrode power setting value and the adjusted smelting temperature; the smelting equipment heat load distribution includes the furnace wall temperature difference between multiple points, the thermal stress distribution, and the temperature gradient of the heated area; the electromagnetic stirring adjustment result includes the adjustment range of the stirring intensity, the stirring time arrangement, and the selection result of the stirring mode; and the smelting time adjustment result includes the set heat conduction rate threshold, the selected smelting time, and the smelting time compensation amount.

[0013] As a further aspect of the present invention, the step of obtaining the metal liquid surface fluctuation state specifically includes:

[0014] S101: Obtain the molten metal level data in the aluminum-based master alloy melting equipment, detect the molten aluminum surface height at fixed time intervals, record the molten metal level values ​​at multiple time nodes, calculate the height change at consecutive time nodes, and obtain the molten metal level change data.

[0015] S102: Using the liquid level height change data, calculate the height change value for adjacent time nodes to obtain the liquid level height difference for multiple time periods. Based on the height difference data for time periods, analyze the liquid level fluctuation trend, identify the fluctuation period and fluctuation amplitude, filter out abnormal values ​​that exceed the normal range, and delete the abnormal data to obtain the liquid level fluctuation period and amplitude dataset.

[0016] S103: Based on the liquid surface fluctuation period and amplitude dataset, evaluate the fluctuation stability in the time series, identify whether the liquid surface fluctuation state is stable in different time periods, analyze the characteristics of the liquid surface fluctuation, and obtain the metal liquid surface fluctuation state.

[0017] As a further aspect of the present invention, the step of obtaining the melting temperature adjustment result specifically includes:

[0018] S201: Based on the fluctuation state of the molten metal surface, obtain the temperature measurement value within a set period, establish a temperature data sequence according to the time order, calculate the temperature change rate between adjacent time nodes, analyze the temperature change rate and fluctuation amplitude within the time period, evaluate the stability of temperature change, and obtain temperature change rate and stability data.

[0019] S202: Based on the temperature change rate and stability data, analyze the temperature change trend, adjust the power output of the heating electrode, identify the relationship between the power adjustment range and the time parameter, adjust the power to match the temperature change requirements, and obtain the melting temperature adjustment result.

[0020] As a further aspect of the present invention, the adjustment of the heating electrode power output is achieved using the following formula:

[0021]

[0022] Among them, P t The power adjustment value at time t, T i T represents the temperature value at time i. i-1 k represents the temperature value at time i-1. i The coefficient representing the influence of temperature change at time i, t i τ represents the time interval at time i. i represents the temperature stability time constant at time i, and n represents the total number of temperature sampling points.

[0023] As a further aspect of the present invention, the step of obtaining the heat load distribution of the smelting equipment specifically includes:

[0024] S301: Using the smelting temperature adjustment result, collect the adjusted furnace wall temperature data of the smelting equipment, select multiple temperature measurement points for measurement, record the temperature values ​​of multiple points, calculate the temperature difference between the temperature measurement points, identify the temperature difference distribution between the temperature measurement points, and obtain the furnace wall temperature difference distribution area.

[0025] S302: Based on the furnace wall temperature difference distribution area, analyze the changing trend of furnace wall temperature difference value in the differential area, identify the temperature difference change, assess the range of thermal stress, and obtain thermal stress gradient change information.

[0026] S303: Based on the thermal stress gradient change information, assess the degree of influence of furnace wall thermal stress on heat transfer, analyze the distribution of heat load in the differentiated region, and obtain the heat load distribution of the smelting equipment.

[0027] As a further aspect of the present invention, the step of obtaining the electromagnetic stirring adjustment result specifically includes:

[0028] S401: By analyzing the heat load distribution of the smelting equipment, the correlation between the area of ​​action of the stirring magnetic field and the flow rate of the molten aluminum is analyzed, the variation range of the flow rate of the molten aluminum under different intensities is identified, the influence characteristics of the stirring magnetic field on the flow of the molten aluminum are extracted, and the information on the change of the flow rate of the molten aluminum is obtained.

[0029] S402: Based on the information on the change in the flow rate of the molten aluminum, evaluate the influence of the stirring magnetic field on the change in the liquid level, calculate the correlation index between the magnetic field strength change curve and the liquid level fluctuation curve, identify the contribution of different stirring methods to the liquid level fluctuation, and obtain the liquid level fluctuation contribution data.

[0030] S403: Based on the liquid level fluctuation contribution data, adjust the operation mode of the electromagnetic stirrer, evaluate the matching degree between the magnetic field strength and duration, correct the control parameters of the electromagnetic stirrer, and obtain the adjustment results of the electromagnetic stirrer.

[0031] As a further aspect of the present invention, the correlation index between the magnetic field intensity change curve and the liquid surface fluctuation curve is calculated using the following formula:

[0032]

[0033] Where RQ represents the correlation index between the magnetic field intensity change curve and the liquid surface fluctuation curve, B o This represents the magnetic field strength at the o-th measurement moment. H represents the average magnetic field strength at the time of measurement. o This represents the liquid level height at the o-th measurement time. G represents the average liquid level height at the measurement time, and G represents the total number of measurement times.

[0034] As a further aspect of the present invention, the step of obtaining the melting time adjustment result specifically includes:

[0035] S501: Using the electromagnetic stirring adjustment results, calculate the heat transfer rate of the heating zone of the smelting equipment, filter the heat transfer rate data within a set period, calculate the change in heat transfer rate at adjacent time nodes, identify time points that exceed the threshold range, and obtain the abnormal heat transfer rate interval.

[0036] S502: Based on the abnormal range of heat conduction rate, compare the melting time with the trend of heat conduction rate, calculate the melting time compensation value, adjust the total melting time, correct the uneven state of heat transfer during the melting process, and obtain the melting time adjustment result.

[0037] On the other hand, the aluminum-based master alloy smelting equipment parameter adjustment system is used to execute the above-mentioned aluminum-based master alloy smelting equipment parameter adjustment method, and the system includes:

[0038] The liquid level fluctuation monitoring module acquires aluminum liquid level height data, collects data on changes in aluminum liquid level height, calculates the liquid level height difference, filters abnormal fluctuation data, extracts fluctuation period and amplitude, calculates liquid level fluctuation stability index, and obtains the metal liquid level fluctuation state.

[0039] The temperature fluctuation analysis module obtains the furnace temperature measurement value through the fluctuation state of the molten metal surface, calculates the temperature change rate, filters data that exceed the melting temperature fluctuation threshold, analyzes the influence of heating electrode power output on temperature fluctuation, adjusts the heating electrode power, corrects the power adjustment amplitude and time parameters, and obtains the melting temperature adjustment result.

[0040] The furnace wall heat load assessment module uses the smelting temperature adjustment results to calculate the temperature difference value of the furnace wall temperature measuring points, identify the furnace wall temperature difference distribution, analyze the range of thermal stress, analyze the trend of furnace wall heat load change, and obtain the heat load distribution of the smelting equipment.

[0041] The electromagnetic stirring optimization module evaluates the impact of electromagnetic stirring on the flow rate and liquid level of molten aluminum based on the heat load distribution of the smelting equipment, adjusts the electromagnetic stirring mode and duration, and obtains the electromagnetic stirring adjustment results.

[0042] The melting time adjustment module uses the electromagnetic stirring adjustment results to calculate the change in melting heat conduction rate, filter data that exceeds the heat conduction rate threshold, calculate the melting time compensation value, adjust the total melting time, and obtain the melting time adjustment result.

[0043] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0044] By monitoring and analyzing the fluctuations in the molten metal surface within the smelting equipment, the smelting temperature can be controlled more precisely, the heating electrode power adjusted, and temperature stability maintained. Collecting temperature data of the furnace wall after adjustments and calculating thermal stress distribution further optimizes the heat load distribution, helping to reduce energy waste and improve smelting efficiency. Adjusting the method and duration of electromagnetic stirring optimizes the flow of molten aluminum, resulting in more uniform metal and improved product quality. Dynamically adjusting the smelting time ensures the continuity and efficiency of the smelting process, significantly improving the economy and product quality of the entire smelting process. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0046] Figure 2 This is a detailed flowchart of S1 of the present invention;

[0047] Figure 3 This is a detailed flowchart of the S2 process of the present invention;

[0048] Figure 4 This is a detailed flowchart of the S3 process of the present invention;

[0049] Figure 5 This is a detailed flowchart of the S4 process of the present invention;

[0050] Figure 6 This is a detailed flowchart of S5 of the present invention;

[0051] Figure 7 This is a system flowchart of the present invention. Detailed Implementation

[0052] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0053] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0054] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0055] Please see Figure 1 This invention provides a method for adjusting the parameters of an aluminum-based master alloy smelting equipment. The process of this method may include the following steps:

[0056] S1: Collect data on the height of the molten metal in the aluminum-based master alloy smelting equipment. Collect the change in the height of the molten aluminum surface at fixed time intervals. Obtain the molten metal height values ​​at multiple time points through continuous measurement. Calculate the height difference between adjacent time points. Analyze the molten metal fluctuation trend based on the height difference. Identify the fluctuation period and amplitude. After removing outliers, identify the stability of the molten metal fluctuation and obtain the molten metal fluctuation state.

[0057] S2: By analyzing the temperature measurement values ​​within a set period through the fluctuation state of the molten metal surface, calculate the temperature change rate between adjacent time nodes, identify the temperature change rate and stability, analyze the temperature change trend, adjust the power output of the heating electrode, correct the power adjustment amplitude and time parameters, and obtain the melting temperature adjustment result.

[0058] S3: Using the results of the smelting temperature adjustment, collect the furnace wall temperature data of the smelting equipment after the adjustment, select multiple temperature measurement points for measurement, calculate the temperature difference between the measurement points, identify the distribution area of ​​the furnace wall temperature difference, perform trend analysis on the furnace wall temperature difference, identify the range and gradient change of thermal stress, evaluate the degree of influence of furnace wall thermal stress on heat transfer, and obtain the heat load distribution of the smelting equipment.

[0059] S4: By analyzing the heat load distribution of the smelting equipment, analyze the correlation between the area of ​​action of the stirring magnetic field and the flow rate of the aluminum liquid, evaluate the influence of magnetic field strength on the change of liquid level, extract the correlation index between the magnetic field strength change curve and the liquid level fluctuation curve, identify the contribution data of differentiated stirring methods to liquid level fluctuation, adjust the electromagnetic stirring operation mode and duration, and obtain the electromagnetic stirring adjustment results.

[0060] S5: Using the results of electromagnetic stirring adjustment, calculate the heat transfer rate of the heating zone of the smelting equipment, filter the heat transfer rate data within the set period, calculate the change in heat transfer rate, filter the time points that exceed the threshold range, compare the smelting time with the trend of heat transfer rate change, calculate the smelting time compensation value, adjust the total smelting time, and obtain the smelting time adjustment result.

[0061] The fluctuation state of the molten metal surface includes the difference in liquid level height, fluctuation amplitude, and fluctuation trend. The smelting temperature adjustment results include the heating electrode power setting value and the adjusted smelting temperature. The heat load distribution of the smelting equipment includes the furnace wall temperature difference between multiple points, thermal stress distribution, and temperature gradient of the heated area. The electromagnetic stirring adjustment results include the adjustment range of stirring intensity, stirring time arrangement, and stirring mode selection results. The smelting time adjustment results include the set heat conduction rate threshold, the selected smelting time, and the smelting time compensation amount.

[0062] Please see Figure 2 The specific steps for obtaining the fluctuation state of the molten metal surface are as follows:

[0063] S101: Obtain the molten metal level data in the aluminum-based master alloy melting equipment, detect the molten aluminum surface height at fixed time intervals, record the molten metal level values ​​at multiple time nodes, calculate the height change at consecutive time nodes, and obtain the molten metal level change data.

[0064] To obtain the molten metal level height data within an aluminum-based master alloy smelting apparatus, a high-precision laser rangefinder or ultrasonic level sensor needs to be installed above the smelting apparatus. This ensures the measurement range covers the entire surface of the molten aluminum. The sensor's installation angle should be adjusted according to the equipment structure to minimize data acquisition errors. Measurements are taken at fixed time intervals, and the molten metal level height data obtained from each measurement can be represented as H. t Where t represents the sampling time point, and the data at each time point is recorded in the database for subsequent calculation and analysis. Let's assume that the aluminum liquid level recorded at a certain time t1 is 1200mm, and the height recorded at the next time t2 is 1195mm. Then the change in height can be calculated as:

[0065]

[0066] This calculation method is used to calculate the difference in liquid level height at all adjacent time points. If the measurement cycle is 10 seconds, 6 sets of data can be obtained within one minute, and 5 sets of continuous height changes ΔH1, ΔH2, ΔH3, ΔH4, and ΔH5 can be calculated. All height change data are stored in the system data and marked with timestamps for subsequent analysis to obtain liquid level height change data.

[0067] S102: Using liquid level change data, calculate the liquid level change value for adjacent time nodes to obtain the liquid level difference over multiple time periods. Based on the height difference data over time periods, analyze the liquid level fluctuation trend, identify the fluctuation period and fluctuation amplitude, filter out outliers that exceed the normal range, delete the outlier data, and obtain the liquid level fluctuation period and amplitude dataset.

[0068] The moving window analysis method, using programming software (such as Python), is used to calculate the height change between adjacent time points to obtain the liquid level height difference. The analysis window length is set to N (with 5 time points), and the height difference ΔH is calculated for each time period. sum This is the sum of all changes within the window, i.e.:

[0069]

[0070] Taking a time period of 50 seconds (measured every 10 seconds) as an example, if the measured changes in height are -5, 3, -2, 4, and -1 respectively, then the height difference for this time period is calculated as follows:

[0071] ΔHsum = (-5) + 3 + (-2) + 4 + (-1) = -1;

[0072] Trend analysis was performed on data from all time periods. The FFT (Fast Fourier Transform) method was used to identify the main period of liquid surface fluctuations. A fluctuation period threshold of 30 to 120 seconds was set, and the fluctuation amplitude A was calculated as the maximum change range for each data point.

[0073] A = max(H) - min(H):

[0074] If the maximum height within a certain time window is 1205mm and the minimum height is 1190mm, then the amplitude is calculated as follows:

[0075] A = 1205 - 1190 = 15 mm;

[0076] Filter outliers that exceed the normal range. The outlier filtering criteria can be set based on the mean μ and standard deviation σ of the data. For example, if a data point H... t Satisfy | H t If -μ|>3σ, it is identified as an outlier and removed, and the data set of liquid surface fluctuation period and amplitude is obtained.

[0077] S103: Based on the liquid surface fluctuation period and amplitude dataset, evaluate the fluctuation stability in the time series, identify whether the liquid surface fluctuation state is stable in different time periods, analyze the characteristics of liquid surface fluctuation, and obtain the metal liquid surface fluctuation state.

[0078] To assess the stability of fluctuations in a time series, the moving root mean square (RMS) method is used to evaluate the degree of stability. The calculation formula is as follows:

[0079]

[0080] If the height changes over a certain period are -5, 3, -2, 4, and -1 mm, then the RMS is calculated as follows:

[0081]

[0082] A threshold for judging the stability of the fluctuation is set. The fluctuation is considered stable if the RMS is less than 5 mm, otherwise it is judged as unstable. The RMS of data from different time periods is calculated and compared to identify whether the liquid surface fluctuation status of the different time periods is stable. If the RMS of a certain time period is much higher than that of the remaining time periods, the calculated RMS value is set to 8 mm, which indicates that the liquid surface fluctuation of that time period is large. Further analysis of the estimated influencing factors (such as stirring intensity, aluminum liquid replenishment frequency, etc.) is conducted in combination with time series data to identify the characteristics of the liquid surface fluctuation and obtain the metal liquid surface fluctuation status.

[0083] Please see Figure 3The specific steps for obtaining the smelting temperature adjustment results are as follows:

[0084] S201: By observing the fluctuation state of the molten metal surface, obtain the temperature measurement value within a set period, establish a temperature data sequence in chronological order, calculate the temperature change rate between adjacent time nodes, analyze the temperature change rate and fluctuation amplitude within the time period, evaluate the stability of temperature change, and obtain temperature change rate and stability data.

[0085] To acquire temperature measurements within a set period, multiple temperature sensors are deployed during the smelting process to collect temperature data at different time points. A temperature data sequence is then established in chronological order, recording the temperature value every 5 seconds within each set time interval to form a complete data stream. After establishing the temperature data sequence, the rate of temperature change between adjacent time points is calculated. This involves calculating the temperature change per unit time to determine the rate of temperature change. In practical applications, a sliding window method can be used to analyze changes at multiple time points to reduce the impact of random errors. The fluctuation amplitude also needs to be calculated. This involves identifying the maximum and minimum temperature values ​​within the set period and calculating the difference between them. Large fluctuation amplitudes indicate temperature instability during smelting, requiring further stability analysis. Stability assessment can be based on standard deviation analysis, calculating the standard deviation of temperature changes throughout the set period. A smaller standard deviation indicates more stable temperature changes; otherwise, significant fluctuations are considered. This process acquires data on the rate of temperature change and stability.

[0086] S202: Based on the temperature change rate and stability data, analyze the temperature change trend, adjust the heating electrode power output, identify the relationship between the power adjustment range and the time parameter, adjust the power to match the temperature change requirements, and obtain the melting temperature adjustment results;

[0087] Adjust the power output of the heating electrode using the following formula:

[0088]

[0089] Among them, P t The power adjustment value at time t, T i T represents the temperature value at time i. i-1 k represents the temperature value at time i-1. i The coefficient representing the influence of temperature change at time i, t i τ represents the time interval at time i. i represents the temperature stability time constant at time i, and n represents the total number of temperature sampling points;

[0090] Parameter meaning:

[0091] Temperature difference |T i -Ti-1 | represents the temperature difference between time i and the previous time, measured by temperature T at each time point using devices such as thermocouples or infrared thermometers. i and T i-1 The absolute value of the difference is used to obtain it;

[0092] Temperature change influence coefficient k i : Indicates the degree of impact of temperature changes on the system. This coefficient can be obtained through experimental calibration and reflects the sensitivity of power demand to temperature changes. k i The value ranges from 0.5 to 2.0, determined based on system characteristics and empirical data;

[0093] Time interval t i : Represents the time interval at time i, which is obtained by recording the timestamp of each temperature measurement and calculating the time difference between adjacent measurements;

[0094] Temperature stability time constant τ i τ represents the time required for the system to reach a stable temperature state. This constant can be determined experimentally and reflects the system's response speed to temperature changes. Depending on the material and structure, τ... i The value is between 5 and 20 seconds;

[0095] Total number of sampling points n: This represents the number of temperature sampling points during the calculation period, which is determined based on the monitoring frequency and total time.

[0096] Calculation example:

[0097] During the smelting process, a thermocouple is used to measure the temperature once per second, and the following data (unit: degrees Celsius) are obtained: T0 = 1500, T1 = 1502, T2 = 1505, T3 = 1503, T4 = 1506;

[0098] The corresponding time interval t i All intervals are 1 second. The influence coefficient k of temperature change was determined through experimental calibration. i Both are 1.5, and the temperature stability time constant τ i Both are 10 seconds;

[0099] The calculation process is as follows:

[0100] Calculate the absolute value of the temperature difference: |T1-T0|=|1502-1500|=2;

[0101] |T2-T1|=|1505-1502|=3;

[0102] |T3-T2|=|1503-1505|=2;

[0103] |T4-T3|=|1506-1503|=3;

[0104] Calculate the numerator:

[0105]

[0106] Calculate the denominator:

[0107]

[0108] Calculate the power adjustment value:

[0109]

[0110] The results indicate that, during the current smelting process, based on the measured temperature changes and system characteristics, the calculated power adjustment value is approximately 23.72 units (the specific unit depends on the system's power measurement standard). This value is used to guide the adjustment of the heating electrode power in actual operation to ensure the stability and uniformity of the smelting temperature.

[0111] Please see Figure 4 The specific steps for obtaining the heat load distribution of the smelting equipment are as follows:

[0112] S301: Using the results of smelting temperature adjustment, collect the furnace wall temperature data of the adjusted smelting equipment, select multiple temperature measurement points for measurement, record the temperature values ​​of multiple points, calculate the temperature difference between the temperature measurement points, identify the temperature difference distribution between the temperature measurement points, and obtain the furnace wall temperature difference distribution area.

[0113] Collect the adjusted furnace wall temperature data of the smelting equipment. Arrange multiple temperature measurement points on the furnace wall, ensuring these points cover different heated areas, such as areas near the heating electrodes, the central area of ​​the furnace, and the edge of the furnace wall. Record the temperature data using thermocouples or infrared thermometers, with a sampling interval of 30 seconds. The temperature data for each measurement point is represented as T. i,t Where i represents the temperature measurement point number and t represents the sampling time, after acquiring the temperature data of all temperature measurement points, the temperature difference between the temperature measurement points is calculated using the following formula:

[0114] ΔT i,j =|T i -T j |;

[0115] Taking four temperature measuring points on the furnace wall as an example, setting T1 = 850℃, T2 = 870℃, T3 = 890℃, and T4 = 860℃, then calculate the temperature difference:

[0116] ΔT 1,2 =|850-870| = 20℃;

[0117] ΔT2,3 =|870-890| = 20℃;

[0118] ΔT 3,4 =|890-860| = 30℃;

[0119] Calculate the temperature difference matrix for all temperature measurement points, analyze the temperature difference distribution among the measurement points, and set a threshold for judging the temperature difference distribution. If ΔT i,j A temperature >25℃ is considered a large temperature difference region and is marked as a high temperature difference region. If ΔT i,j If the temperature is ≤25℃, it is marked as a low temperature difference area, and a dataset of furnace wall temperature difference distribution area is obtained.

[0120] S302: Based on the furnace wall temperature difference distribution area, analyze the changing trend of furnace wall temperature difference value in the differentiated area, identify the temperature difference change, assess the range of thermal stress, and obtain information on thermal stress gradient changes.

[0121] Analyze the changing trend of furnace wall temperature difference in different regions, select multiple time points in the time series, and calculate the rate of temperature change of each temperature measuring point at different time points:

[0122]

[0123] If the temperature at a certain temperature measuring point i is 850℃ at time t1 = 0s and the temperature is 860℃ at time t2 = 30s, then the rate of temperature change is:

[0124]

[0125] Calculate the temperature change rate sequence for multiple temperature measurement points, plot the temperature difference trend curve, and identify temperature difference fluctuations. If the temperature change rate in a certain area is much higher than that in the remaining areas (e.g., R...), the temperature change rate is significantly higher. Ti If the temperature change is greater than 0.5℃ / s, then the temperature in this region changes rapidly. Further calculation of the thermal stress range is then performed using the thermal stress calculation formula:

[0126] σ T =E·α·ΔT;

[0127] Where E is the elastic modulus of the furnace wall material (e.g., 70 GPa for aluminum alloy), and α is the coefficient of thermal expansion (e.g., 23 × 10⁻⁶). -6 If the temperature difference in a certain area is ΔT = 30℃, then calculate the thermal stress:

[0128] σ T =70×10 9 ×23×10 -6 ×30=48.3;

[0129] Identify areas with large temperature differences. If the calculated thermal stress exceeds the material's yield strength (e.g., 50 MPa), it is determined that there is significant thermal stress in that area, and information on the change in thermal stress gradient is obtained.

[0130] S303: Based on the information on changes in thermal stress gradient, assess the degree of influence of furnace wall thermal stress on heat transfer, analyze the distribution of heat load in differentiated regions, and obtain the heat load distribution of smelting equipment;

[0131] To assess the impact of furnace wall thermal stress on heat transfer, the heat flux q is calculated to analyze the heat load distribution. The formula for calculating the heat flux is:

[0132]

[0133] Where k is the thermal conductivity of the furnace wall material (e.g., 180 W / m·K for aluminum alloy), and dT / dx is the temperature gradient;

[0134] If the temperature gradient in a certain region is 10℃ / cm, then calculate the heat flux:

[0135]

[0136] A region with high heat flux indicates a large heat load. Further calculation of the heat load Q distribution is needed:

[0137] Q = q × A;

[0138] Where A is the heated area. If the area of ​​a certain region is 0.5, then the heat load is calculated as follows:

[0139] Q = -180000 × 0.5 = -90000;

[0140] Identify areas with high heat loads. For example, if a region has a heat load concentration of Q > -100000W, then obtain heat load distribution data for the smelting equipment.

[0141] Please see Figure 5 The specific steps for obtaining the results of electromagnetic stirring adjustment are as follows:

[0142] S401: By analyzing the heat load distribution of the smelting equipment, the correlation between the area of ​​action of the stirring magnetic field and the flow rate of the molten aluminum is analyzed, the variation range of the molten aluminum flow rate under different intensities is identified, the influence characteristics of the stirring magnetic field on the flow of molten aluminum are extracted, and the information on the change of molten aluminum flow rate is obtained.

[0143] To analyze the correlation between the area of ​​influence of the stirring magnetic field and the flow velocity of molten aluminum, multiple velocity measuring points were arranged inside the melting equipment. Electromagnetic induction velocimeters or laser Doppler velocimeters (LDV) were used to measure the flow velocity of the molten aluminum. The measurement time interval was set to 10 seconds, and the flow velocity data at each measuring point was recorded as v. i,tWhere i represents the velocity measurement point number and t represents the sampling time, after acquiring the flow velocity data of all velocity measurement points, the relationship between the magnetic field strength B and the aluminum liquid flow velocity v is calculated, and the flow velocity change trend is determined by linear fitting method:

[0144] v = kB + v0;

[0145] Where k is the fitting coefficient and v0 is the flow velocity without the action of a magnetic field;

[0146] With magnetic field strengths of 0.2T, 0.4T, and 0.6T, the measured aluminum molten flow velocities were 0.5m / s, 1.0m / s, and 1.4m / s, respectively. A fitting yielded k≈2.5. The effect of magnetic field strength on the aluminum molten flow was determined, and the velocity variation under different magnetic field strengths was calculated.

[0147] Δv=|v B2 -v B1 |;

[0148] If the magnetic field increases from 0.4T to 0.6T, the change in flow velocity is calculated as follows:

[0149] Δv = |1.4 - 1.0| = 0.4 m / s;

[0150] Calculations were performed at different velocity measurement points to extract the influence characteristics of the stirring magnetic field on the flow of molten aluminum, identify the velocity change patterns of molten aluminum in different magnetic field regions, and obtain information on the velocity change of molten aluminum.

[0151] S402: Based on the information on the change of aluminum liquid flow rate, evaluate the influence of the stirring magnetic field on the change of liquid level, calculate the correlation index between the magnetic field strength change curve and the liquid level fluctuation curve, identify the contribution of different stirring methods to the liquid level fluctuation, and obtain the liquid level fluctuation contribution data.

[0152] The correlation index between the magnetic field intensity change curve and the liquid surface fluctuation curve is calculated using the following formula:

[0153]

[0154] Where RQ represents the correlation index between the magnetic field intensity change curve and the liquid surface fluctuation curve, B o This represents the magnetic field strength at the o-th measurement moment. H represents the average magnetic field strength at the time of measurement. o This represents the liquid level height at the o-th measurement time. G represents the average liquid level height at the measurement time, and G represents the total number of measurement times.

[0155] Parameter meaning:

[0156] Parameter B oThe value represents the magnetic field strength at the o-th measurement moment. It is collected by a magnetic field detector and is measured in Tesla (T). The data comes from records of magnetic field changes at different time points. A high-precision Hall sensor is used during the measurement process, recording once per second.

[0157] parameter The average magnetic field strength at all measurement moments is calculated as follows:

[0158]

[0159] The measured magnetic field strength data are as follows:

[0160] B1 = 0.45T, B2 = 0.48T, B3 = 0.50T, B4 = 0.47T, B5 = 0.49T, during measurement

[0161] Total number of strokes G = 5;

[0162] Calculate the average magnetic field strength:

[0163]

[0164] Parameter H o The liquid level height at the 0th measurement moment is obtained using a laser rangefinder sensor, with the unit being millimeters (mm). The device collects liquid level height data once per second.

[0165] parameter The average liquid level height at all measurement times is calculated as follows:

[0166]

[0167] The measured liquid level heights were as follows: H1 = 150.2 mm, H2 = 152.4 mm, H3 = 151.8 mm, H4 = 149.9 mm, H5 = 150.7 mm;

[0168] Calculate the average liquid level height:

[0169]

[0170] Calculate the numerator:

[0171]

[0172]

[0173] Calculate the denominator:

[0174]

[0175] Part One:

[0176]

[0177] Part Two:

[0178]

[0179] Calculate the correlation index:

[0180]

[0181] The results show that the correlation between the magnetic field strength variation curve and the liquid surface fluctuation curve is 0.586, which is a moderate correlation. This indicates that there is a certain linear relationship between the magnetic field strength and the fluctuation of the liquid surface height, but it is not completely linear. This value will be used for subsequent analysis of the contribution of the stirring method to the fluctuation of the liquid surface.

[0182] S403: Based on the contribution data of liquid level fluctuation, adjust the operation mode of electromagnetic stirring, evaluate the matching degree between magnetic field strength and duration, correct the control parameters of electromagnetic stirring, and obtain the adjustment results of electromagnetic stirring;

[0183] The operation mode of the electromagnetic stirrer is adjusted, selecting a stirring mode with high contribution and setting the initial stirring mode according to the flow characteristics of molten aluminum. During the adjustment process, it is necessary to evaluate the matching degree between magnetic field strength and duration. That is, based on the contribution of liquid surface fluctuations, the appropriate magnetic field strength range and action time are calculated to avoid excessive magnetic field strength leading to splashing of molten aluminum or insufficient stirring due to insufficient magnetic field strength. In practical applications, a dynamic adjustment strategy can be adopted, that is, the magnetic field strength is gradually corrected based on real-time feedback of liquid surface fluctuations. If the liquid surface fluctuation amplitude exceeds the set threshold, the stirring magnetic field strength is reduced; conversely, if the fluctuation is insufficient, the magnetic field strength is increased. At the same time, the time parameters of the electromagnetic stirrer are adjusted to optimize the magnetic field action cycle. When the liquid surface fluctuation is small, the stirring time can be appropriately extended to enhance the uniform flow of molten aluminum, while when the fluctuation is large, the stirring time can be appropriately shortened to reduce liquid surface instability. Through multiple rounds of optimization, the control parameters of the electromagnetic stirrer are corrected to ensure that the stirring effect meets the requirements of the smelting process and to obtain the adjustment results of the electromagnetic stirrer.

[0184] Please see Figure 6 The specific steps for obtaining the smelting time adjustment results are as follows:

[0185] S501: Utilize the results of electromagnetic stirring adjustment to calculate the heat transfer rate of the heating zone of the smelting equipment, filter the heat transfer rate data within a set period, calculate the change in heat transfer rate at adjacent time nodes, identify time points that exceed the threshold range, and obtain abnormal intervals of heat transfer rate.

[0186] To calculate the heat transfer rate in the heating zone of the smelting equipment, temperature data at different locations and time points during the smelting process are collected from temperature sensors or infrared thermometers. The temperatures at points A, B, and C are recorded at time points of 0 seconds, 5 seconds, and 10 seconds, respectively. The thermal conductivity k of the material is set to 50 W / (m·K), and the distance between measurement points Δx is 0.02 m. The heat transfer rate over a certain time period is then calculated using Fourier's law of heat conduction, using the following formula:

[0187]

[0188] If the temperatures at points A and B are measured to be 1600K and 1580K respectively at a certain moment, the heat conduction rate during that time period is calculated as follows:

[0189]

[0190] After calculating the heat transfer rate at multiple time points, data within a set period are filtered, and outliers exceeding three standard deviations are removed. If most data points are between -60,000 and -40,000, but the heat transfer rate abruptly drops to -100,000 at certain times, it is considered an anomaly and removed. The change between adjacent time points is calculated.

[0191] Δq=q t+1 -q t ;

[0192] If the change exceeds the set threshold, such as 10,000, then the time point is marked as abnormal, and the abnormal time interval is identified using the sliding window method to determine the time period of abnormal heat conduction rate and obtain the abnormal heat conduction rate interval.

[0193] S502: Based on the abnormal range of heat conduction rate, compare the trend of melting time with the change of heat conduction rate, calculate the melting time compensation value, adjust the total melting time, correct the unbalanced state of heat transfer during melting, and obtain the melting time adjustment result.

[0194] It is necessary to compare the trends of melting time and heat transfer rate, extract heat transfer rate data at each time point within the abnormal range, and analyze its changes over time. In practical applications, linear regression can be used to fit the data and calculate the trend value of heat transfer rate changes. If the fitting results show that the heat transfer rate is decreasing and the decrease exceeds the set benchmark range, then melting time compensation calculation is required. The compensation value can be calculated based on the actual heat loss during the melting process. In some cases, due to uneven temperature distribution, the heat transfer efficiency in some areas is low, causing the temperature in some areas to drop too quickly during the melting process. To ensure the stability of melting, it is necessary to determine the additional melting time based on the changes in heat transfer rate. When calculating the compensation time, a time compensation coefficient can be set, and the required additional melting time can be calculated based on the decrease in heat transfer rate. The adjusted melting time can effectively balance the uneven heat transfer state, ensure the stability of the melting process, and adjust the heating power of the melting equipment accordingly to ensure that the melting efficiency meets the process requirements, thus obtaining the melting time adjustment result.

[0195] like Figure 7 As shown, the parameter adjustment system for aluminum-based master alloy smelting equipment includes:

[0196] The liquid level fluctuation monitoring module acquires aluminum liquid level height data, collects data on changes in aluminum liquid level height, calculates the liquid level height difference, filters abnormal fluctuation data, extracts fluctuation period and amplitude, calculates liquid level fluctuation stability index, and obtains the metal liquid level fluctuation state.

[0197] The temperature fluctuation analysis module obtains the temperature measurement value of the smelting furnace by measuring the fluctuation state of the molten metal surface, calculates the temperature change rate, filters data that exceed the smelting temperature fluctuation threshold, analyzes the influence of the heating electrode power output on the temperature fluctuation, adjusts the heating electrode power, corrects the power adjustment amplitude and time parameters, and obtains the smelting temperature adjustment result.

[0198] The furnace wall heat load assessment module uses the smelting temperature adjustment results to calculate the temperature difference value of the furnace wall temperature measuring points, identify the furnace wall temperature difference distribution, analyze the range of thermal stress, analyze the trend of furnace wall heat load change, and obtain the heat load distribution of the smelting equipment.

[0199] The electromagnetic stirring optimization module evaluates the impact of electromagnetic stirring on the flow rate and liquid level of molten aluminum based on the heat load distribution of the smelting equipment, adjusts the electromagnetic stirring mode and duration, and obtains the electromagnetic stirring adjustment results.

[0200] The melting time adjustment module uses the results of electromagnetic stirring to calculate the change in melting heat conduction rate, filters out data that exceeds the heat conduction rate threshold, calculates the melting time compensation value, adjusts the total melting time, and obtains the melting time adjustment result.

[0201] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for adjusting parameters of aluminum-based master alloy smelting equipment, characterized in that, Includes the following steps: S1: Collect data on the height of the molten metal in the aluminum-based master alloy smelting equipment, collect the change in the height of the molten aluminum surface at fixed time intervals, identify the height difference, fluctuation amplitude and fluctuation trend, and obtain the fluctuation state of the molten metal surface. S2: Based on the fluctuation state of the molten metal surface and the temperature data of the smelting equipment, calculate the temperature change rate, analyze the trend of smelting temperature change, adjust the heating electrode power, and obtain the smelting temperature adjustment result; S3: Based on the smelting temperature adjustment results, collect the temperature data of the furnace wall of the smelting equipment after adjustment, calculate the furnace wall temperature difference between multiple points, identify the thermal stress distribution, evaluate the degree of influence of thermal stress on energy transfer, and obtain the heat load distribution of the smelting equipment. S4: Using the heat load distribution of the smelting equipment, identify the influence of electromagnetic stirring on the flow state of molten aluminum, calculate the contribution data of liquid surface fluctuation, adjust the electromagnetic stirring method and time, and obtain the electromagnetic stirring adjustment results; S5: Based on the electromagnetic stirring adjustment results, calculate the change in heat conduction rate of the heated area of ​​the melting equipment, set a heat conduction rate threshold, filter out melting times that exceed the threshold, and obtain the melting time adjustment results.

2. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 1, characterized in that, The molten metal surface fluctuation state includes the difference in liquid level height, fluctuation amplitude, and fluctuation trend. The smelting temperature adjustment result includes the heating electrode power setting value and the adjusted smelting temperature. The smelting equipment heat load distribution includes the furnace wall temperature difference between multiple points, thermal stress distribution, and temperature gradient of the heated area. The electromagnetic stirring adjustment result includes the adjustment range of stirring intensity, stirring time arrangement, and stirring mode selection result. The smelting time adjustment result includes the set heat conduction rate threshold, the selected smelting time, and the smelting time compensation amount.

3. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 1, characterized in that, The specific steps for obtaining the fluctuation state of the liquid metal surface are as follows: S101: Obtain the molten metal level data in the aluminum-based master alloy melting equipment, detect the molten aluminum surface height at fixed time intervals, record the molten metal level values ​​at multiple time nodes, calculate the height change at consecutive time nodes, and obtain the molten metal level change data. S102: Using the liquid level height change data, calculate the height change value for adjacent time nodes to obtain the liquid level height difference for multiple time periods. Based on the height difference data for time periods, analyze the liquid level fluctuation trend, identify the fluctuation period and fluctuation amplitude, filter out abnormal values ​​that exceed the normal range, and delete the abnormal data to obtain the liquid level fluctuation period and amplitude dataset. S103: Based on the liquid surface fluctuation period and amplitude dataset, evaluate the fluctuation stability in the time series, identify whether the liquid surface fluctuation state is stable in different time periods, analyze the characteristics of the liquid surface fluctuation, and obtain the metal liquid surface fluctuation state.

4. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 1, characterized in that, The specific steps for obtaining the melting temperature adjustment result are as follows: S201: Based on the fluctuation state of the molten metal surface, obtain the temperature measurement value within a set period, establish a temperature data sequence according to the time order, calculate the temperature change rate between adjacent time nodes, analyze the temperature change rate and fluctuation amplitude within the time period, evaluate the stability of temperature change, and obtain temperature change rate and stability data. S202: Based on the temperature change rate and stability data, analyze the temperature change trend, adjust the power output of the heating electrode, identify the relationship between the power adjustment range and the time parameter, adjust the power to match the temperature change requirements, and obtain the melting temperature adjustment result.

5. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 4, characterized in that, The adjustment of the heating electrode power output is achieved using the following formula: Among them, P t The power adjustment value at time t, T i T represents the temperature value at time i. i-1 k represents the temperature value at time i-1. i The coefficient representing the influence of temperature change at time i, t i τ represents the time interval at time i. i represents the temperature stability time constant at time i, and n represents the total number of temperature sampling points.

6. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 1, characterized in that, The specific steps for obtaining the heat load distribution of the smelting equipment are as follows: S301: Using the smelting temperature adjustment result, collect the adjusted furnace wall temperature data of the smelting equipment, select multiple temperature measurement points for measurement, record the temperature values ​​of multiple points, calculate the temperature difference between the temperature measurement points, identify the temperature difference distribution between the temperature measurement points, and obtain the furnace wall temperature difference distribution area. S302: Based on the furnace wall temperature difference distribution area, analyze the changing trend of furnace wall temperature difference value in the differential area, identify the temperature difference change, assess the range of thermal stress, and obtain thermal stress gradient change information. S303: Based on the thermal stress gradient change information, assess the degree of influence of furnace wall thermal stress on heat transfer, analyze the distribution of heat load in the differentiated region, and obtain the heat load distribution of the smelting equipment.

7. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 1, characterized in that, The specific steps for obtaining the electromagnetic stirring adjustment results are as follows: S401: By analyzing the heat load distribution of the smelting equipment, the correlation between the area of ​​action of the stirring magnetic field and the flow rate of the molten aluminum is analyzed, the variation range of the flow rate of the molten aluminum under different intensities is identified, the influence characteristics of the stirring magnetic field on the flow of the molten aluminum are extracted, and the information on the change of the flow rate of the molten aluminum is obtained. S402: Based on the information on the change in the flow rate of the molten aluminum, evaluate the influence of the stirring magnetic field on the change in the liquid level, calculate the correlation index between the magnetic field strength change curve and the liquid level fluctuation curve, identify the contribution of different stirring methods to the liquid level fluctuation, and obtain the liquid level fluctuation contribution data. S403: Based on the liquid level fluctuation contribution data, adjust the operation mode of the electromagnetic stirrer, evaluate the matching degree between the magnetic field strength and duration, correct the control parameters of the electromagnetic stirrer, and obtain the adjustment results of the electromagnetic stirrer.

8. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 7, characterized in that, The correlation index between the magnetic field intensity change curve and the liquid surface fluctuation curve is calculated using the following formula: Where RQ represents the correlation index between the magnetic field intensity change curve and the liquid surface fluctuation curve, B o This represents the magnetic field strength at the o-th measurement moment. H represents the average magnetic field strength at the time of measurement. o This represents the liquid level height at the o-th measurement time. G represents the average liquid level height at the measurement time, and G represents the total number of measurement times.

9. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 1, characterized in that, The specific steps for obtaining the smelting time adjustment result are as follows: S501: Using the electromagnetic stirring adjustment results, calculate the heat transfer rate of the heating zone of the smelting equipment, filter the heat transfer rate data within a set period, calculate the change in heat transfer rate at adjacent time nodes, identify time points that exceed the threshold range, and obtain the abnormal heat transfer rate interval. S502: Based on the abnormal range of heat conduction rate, compare the melting time with the trend of heat conduction rate, calculate the melting time compensation value, adjust the total melting time, correct the uneven state of heat transfer during the melting process, and obtain the melting time adjustment result.

10. A parameter adjustment system for aluminum-based master alloy smelting equipment, characterized in that, The method for adjusting parameters of aluminum-based master alloy smelting equipment according to any one of claims 1-9, wherein the system comprises: The liquid level fluctuation monitoring module acquires aluminum liquid level height data, collects data on changes in aluminum liquid level height, calculates the liquid level height difference, filters abnormal fluctuation data, extracts fluctuation period and amplitude, calculates liquid level fluctuation stability index, and obtains the metal liquid level fluctuation state. The temperature fluctuation analysis module obtains the furnace temperature measurement value through the fluctuation state of the molten metal surface, calculates the temperature change rate, filters data that exceed the melting temperature fluctuation threshold, analyzes the influence of heating electrode power output on temperature fluctuation, adjusts the heating electrode power, corrects the power adjustment amplitude and time parameters, and obtains the melting temperature adjustment result. The furnace wall heat load assessment module uses the smelting temperature adjustment results to calculate the temperature difference value of the furnace wall temperature measuring points, identify the furnace wall temperature difference distribution, analyze the range of thermal stress, analyze the trend of furnace wall heat load change, and obtain the heat load distribution of the smelting equipment. The electromagnetic stirring optimization module evaluates the impact of electromagnetic stirring on the flow rate and liquid level of molten aluminum based on the heat load distribution of the smelting equipment, adjusts the electromagnetic stirring mode and duration, and obtains the electromagnetic stirring adjustment results. The melting time adjustment module uses the electromagnetic stirring adjustment results to calculate the change in melting heat conduction rate, filter data that exceeds the heat conduction rate threshold, calculate the melting time compensation value, adjust the total melting time, and obtain the melting time adjustment result.

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