Method and system for adjusting parameters of aluminum-based intermediate alloy smelting equipment

Abstract

The invention relates to the technical field of non-ferrous metal smelting, in particular to an aluminum-based intermediate alloy smelting equipment parameter adjusting method and system.The aluminum-based intermediate alloy smelting equipment parameter adjusting method comprises the following steps that molten metal level height data in aluminum-based intermediate alloy smelting equipment are collected, and the molten aluminum surface height variation is collected within a fixed time interval; and the liquid level height difference value, the fluctuation amplitude and the fluctuation trend are recognized, and the metal liquid level fluctuation state is obtained. According to the method, the heat load distribution is further optimized by adjusting the power of the heating electrode, keeping the temperature stability, collecting the adjusted temperature data of the furnace wall of the smelting equipment and calculating the heat stress distribution, so that the energy waste is reduced, the smelting efficiency is improved, and the electromagnetic stirring efficiency is improved by adjusting the electromagnetic stirring mode and time. And the flowing state of molten aluminum is optimized, so that metal is more uniform, the product quality is improved, the smelting time is dynamically adjusted, the continuity and efficiency of the smelting process are ensured, and the economical efficiency of the whole smelting process and the product quality are remarkably improved.

Description

Technical Field

[0001] The invention relates to the technical field of nonferrous metal smelting, and in particular to a method and system for adjusting parameters of aluminum-based master alloy smelting equipment. Background Art

[0002] The field of non-ferrous metal smelting technology includes the extraction and processing of various non-ferrous metal raw materials to the preparation of alloys. The core content covers key steps such as raw material preparation, smelting, refining and casting. The main purpose of the field of non-ferrous metal smelting technology is to improve the purity and performance of metals to meet the needs of industry and applications. The technologies involved in the smelting process include temperature control, chemical composition adjustment, impurity removal and precise addition of alloying elements, all of which are aimed at optimizing the physical and chemical properties of metals.

[0003] Among them, the parameter adjustment method of aluminum-based master alloy smelting equipment refers to a method for scientifically adjusting the operating parameters of the smelting equipment in the aluminum alloy production process. The technical matters targeted by this patent subject include temperature setting, smelting time control, alloy component ratio and precise control of cooling rate. By adjusting the parameters, the stability of the smelting process and the quality consistency of the finished alloy can be ensured, which is achieved through a computer control system to ensure precise adjustment of parameters and automation of the process.

[0004] The existing technology faces the problems of inaccurate temperature control and low energy utilization in the smelting process. Due to the inaccurate temperature control, the performance of the metal will be unstable, affecting the quality and application of the product. The inefficient use of energy not only increases the production cost, but also creates a greater burden on the environment. The existing technology lacks real-time data support for the adjustment of the operating parameters of the smelting equipment, resulting in a lag in adjustment, affecting the continuity and flexibility of production. All these shortcomings limit the improvement of production efficiency and the stability of product quality, making it difficult for non-ferrous metal smelting companies to meet the market demand for high-performance metal materials. Summary of the invention

[0005] In order to solve the problems of inaccurate temperature control and low energy utilization in the prior art, the inaccurate temperature control will lead to unstable metal performance, affecting the quality and application of the product. The inefficient use of energy not only increases production costs, but also imposes a greater burden on the environment. The prior art lacks real-time data support for the adjustment of the operating parameters of the smelting equipment, resulting in a lag in the adjustment, affecting the continuity and flexibility of production. The shortcomings limit the improvement of production efficiency and the stability of product quality, making it difficult for non-ferrous metal smelting companies to meet the market demand for high-performance metal materials. The embodiment of the present invention provides a method and system for adjusting the parameters of aluminum-based master alloy smelting equipment. The technical solution is as follows:

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

[0007] S1: Collect the metal liquid level data in the aluminum-based master alloy smelting equipment, collect the aluminum liquid surface height change at a fixed time interval, identify the liquid level height difference, fluctuation amplitude and fluctuation trend, and obtain the metal liquid level fluctuation state;

[0008] S2: Calculate the temperature change rate based on the metal liquid level fluctuation state and the temperature data of the smelting equipment, analyze the smelting temperature change trend, adjust the heating electrode power, and obtain the smelting temperature adjustment result;

[0009] S3: Based on the smelting temperature adjustment result, the temperature data of the furnace wall of the smelting equipment after the adjustment is collected, the temperature difference of the furnace wall between multiple points is calculated, the thermal stress distribution is identified, the influence of the thermal stress on the energy transfer is evaluated, and the thermal load distribution of the smelting equipment is obtained;

[0010] S4: using the heat load distribution of the smelting equipment, identifying the influence of electromagnetic stirring on the flow state of aluminum liquid, calculating the liquid level fluctuation contribution data, adjusting the electromagnetic stirring mode and time, and obtaining the electromagnetic stirring adjustment result;

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

[0012] As a further scheme of the present invention, the metal liquid level fluctuation state includes the liquid level height difference, 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 the temperature gradient of the heated area; the electromagnetic stirring adjustment result includes the adjustment amplitude of the stirring intensity, the stirring time arrangement, and the selection result of the stirring mode; the smelting time adjustment result includes the set heat conduction rate threshold, the screened smelting time, and the smelting time compensation amount.

[0013] As a further solution of the present invention, the step of obtaining the metal liquid level fluctuation state is specifically:

[0014] S101: obtaining the metal liquid level data in the aluminum-based master alloy smelting equipment, detecting the height of the aluminum liquid surface at fixed time intervals, recording the liquid level height values ​​corresponding to multiple time nodes, calculating the height changes at consecutive time nodes, and obtaining the liquid level height change data;

[0015] S102: using the liquid level height change data, calculating the height change values ​​of adjacent time nodes to obtain the liquid level height difference in multiple time periods, analyzing the liquid level fluctuation trend based on the height difference data in each time period, identifying the fluctuation period and fluctuation amplitude, screening out abnormal values ​​beyond the normal range, deleting the abnormal data, and obtaining a liquid level fluctuation period and amplitude data set;

[0016] S103: According to the liquid level fluctuation period and amplitude data set, evaluate the fluctuation stability in the time series, identify whether the liquid level fluctuation state in the differentiated time period is stable, analyze the characteristics of the liquid level fluctuation, and obtain the metal liquid level fluctuation state.

[0017] As a further solution of the present invention, the step of obtaining the smelting temperature adjustment result is specifically:

[0018] S201: obtaining the temperature measurement value within a set period through the metal liquid level fluctuation state, establishing a temperature data sequence in chronological order, calculating the temperature change rate between adjacent time nodes, analyzing the temperature change rate and fluctuation amplitude within the time period, evaluating the stability of the temperature change, and obtaining the temperature change rate and stability data;

[0019] S202: Analyze the temperature change trend according to the temperature change rate and stability data, adjust the heating electrode power output, identify the relationship between the power adjustment amplitude and the time parameter, perform power adjustment, match the temperature change requirements, and obtain the melting temperature adjustment result.

[0020] As a further solution of the present invention, the power output of the heating electrode is adjusted using the formula:

[0021]

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

[0023] As a further solution of the present invention, the step of obtaining the heat load distribution of the smelting equipment is specifically as follows:

[0024] S301: using the smelting temperature adjustment result, collecting the adjusted smelting equipment furnace wall temperature data, selecting multiple temperature measuring points for measurement, recording the temperature values ​​of the multiple points, calculating the temperature difference of the temperature measuring points, identifying the temperature difference distribution between the temperature measuring points, and obtaining the furnace wall temperature difference distribution area;

[0025] S302: Based on the furnace wall temperature difference distribution area, analyzing the change trend of the furnace wall temperature difference value in the differentiated area, identifying the temperature difference change, evaluating the thermal stress action range, and obtaining thermal stress gradient change information;

[0026] S303: According to the thermal stress gradient change information, the influence of the furnace wall thermal stress on the heat transfer is evaluated, the distribution of the heat load in the differentiated area is analyzed, and the heat load distribution of the smelting equipment is obtained.

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

[0028] S401: analyzing the correlation between the stirring magnetic field action area and the aluminum liquid flow rate through the heat load distribution of the smelting equipment, identifying the variation range of the aluminum liquid flow rate under the differentiated intensity, extracting the influence characteristics of the stirring magnetic field on the aluminum liquid flow, and obtaining the aluminum liquid flow rate variation information;

[0029] S402: Based on the aluminum liquid flow rate change information, evaluate the influence of the stirring magnetic field on the liquid level change, calculate the correlation index between the magnetic field intensity change curve and the liquid level fluctuation curve, identify the contribution degree of the differentiated stirring mode to the liquid level fluctuation, and obtain the liquid level fluctuation contribution degree data;

[0030] S403: According to the liquid level fluctuation contribution data, the operation mode of electromagnetic stirring is adjusted, the matching degree between the magnetic field intensity and the duration is evaluated, the control parameters of electromagnetic stirring are corrected, and the electromagnetic stirring adjustment result is obtained.

[0031] As a further solution of the present invention, the correlation index between the magnetic field intensity variation curve and the liquid level fluctuation curve is calculated using the formula:

[0032]

[0033] Among them, RQ represents the correlation index between the magnetic field intensity change curve and the liquid level fluctuation curve, B o represents the magnetic field strength at the oth measurement moment, Represents the average magnetic field strength at the time of measurement, H o represents the liquid level at the oth measurement moment, represents the average liquid level height at the measurement time, and G represents the total number of measurement times.

[0034] As a further solution of the present invention, the step of obtaining the smelting time adjustment result is specifically:

[0035] S501: using the electromagnetic stirring adjustment result, calculating the heat conduction rate of the heating area of ​​the smelting equipment, screening the heat conduction rate data within a set period, calculating the change in the heat conduction rate of adjacent time nodes, identifying the time point beyond the threshold range, and obtaining the abnormal heat conduction rate interval;

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

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

[0038] The liquid level fluctuation monitoring module obtains the aluminum liquid level height data, collects the aluminum liquid level height change data, calculates the liquid level height difference, screens the abnormal fluctuation data, extracts the fluctuation period and amplitude, calculates the liquid level fluctuation stability index, and obtains the metal liquid level fluctuation state;

[0039] The temperature fluctuation analysis module obtains the temperature measurement value of the smelting furnace through the metal liquid level fluctuation state, calculates the temperature change rate, filters the data exceeding 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;

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

[0041] The electromagnetic stirring optimization module evaluates the influence of electromagnetic stirring on the flow rate and liquid level of aluminum liquid according to the heat load distribution of the smelting equipment, adjusts the electromagnetic stirring mode and duration, and obtains the electromagnetic stirring adjustment result;

[0042] The smelting time adjustment module uses the electromagnetic stirring adjustment result to calculate the change in smelting heat conduction rate, screens data exceeding the heat conduction rate threshold, calculates the smelting time compensation value, adjusts the total smelting time, and obtains the smelting time adjustment result.

[0043] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0044] By monitoring and analyzing the fluctuation state of the metal liquid level in the smelting equipment, the smelting temperature can be controlled more accurately, the heating electrode power can be adjusted, and the temperature stability can be maintained. By collecting the temperature data of the adjusted smelting equipment furnace wall and calculating the thermal stress distribution, the heat load distribution can be further optimized, which helps to reduce energy waste and improve smelting efficiency. By adjusting the mode and time of electromagnetic stirring, the flow state of aluminum liquid is optimized, making the metal more uniform and improving the quality of the product. The smelting time is dynamically adjusted to ensure the continuity and efficiency of the smelting process, significantly improving the economy and product quality of the entire smelting process. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0047] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0048] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0049] Figure 5 This is a detailed flow chart of S4 of the present invention;

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

[0051] Figure 7 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0052] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0053] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0054] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0055] See also Figure 1 The embodiment of the present invention provides a method for adjusting parameters of aluminum-based master alloy smelting equipment. The processing flow of the method may include the following steps:

[0056] S1: Collect the metal liquid level data in the aluminum-based master alloy smelting equipment, collect the aluminum liquid surface height change at a fixed time interval, obtain the liquid level height values ​​at multiple time nodes through continuous measurement, calculate the height difference between adjacent time nodes, analyze the liquid level fluctuation trend based on the height difference, identify the fluctuation period and amplitude, identify the liquid level fluctuation stability after eliminating abnormal values, and obtain the metal liquid level fluctuation state;

[0057] S2: Through the fluctuation state of the metal liquid level, the temperature measurement values ​​within the set period are analyzed in time series, the temperature change rate between adjacent time nodes is calculated, the temperature change rate and stability are identified, the temperature change trend is analyzed, the heating electrode power output is adjusted, the power adjustment amplitude and time parameters are corrected, and the melting temperature adjustment result is obtained;

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

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

[0060] S5: using the electromagnetic stirring adjustment result, calculating the heat conduction rate of the heating area of ​​the smelting equipment, screening the heat conduction rate data within the set period, calculating the change of the heat conduction rate, screening the time point beyond the threshold range, comparing the smelting time with the change trend of the heat conduction rate, calculating the smelting time compensation value, adjusting the total smelting time, and obtaining the smelting time adjustment result;

[0061] The fluctuation state of the metal liquid level includes the liquid level height difference, 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 in the heated area. The electromagnetic stirring adjustment results include the adjustment amplitude of the stirring intensity, the stirring time arrangement, and the selection results of the stirring mode. The smelting time adjustment results include the set heat conduction rate threshold, the screened smelting time, and the smelting time compensation amount.

[0062] See also Figure 2 , the specific steps for obtaining the metal liquid level fluctuation state are:

[0063] S101: obtaining the metal liquid level data in the aluminum-based master alloy smelting equipment, detecting the height of the aluminum liquid surface at fixed time intervals, recording the liquid level height values ​​corresponding to multiple time nodes, calculating the height changes at consecutive time nodes, and obtaining the liquid level height change data;

[0064] To obtain the metal liquid level data in the aluminum-based master alloy smelting equipment, it is necessary to use a high-precision laser rangefinder or an ultrasonic liquid level sensor installed above the smelting equipment to ensure that the measurement range can cover the entire aluminum liquid surface, and adjust the installation angle of the sensor according to the equipment structure to reduce the error of data collection. Through data collection, measurements are performed at fixed time intervals. The liquid level data obtained in each measurement can be expressed as H t , where t represents the sampling time point. The data at each time point is recorded in the database for subsequent calculation and analysis. The aluminum liquid level recorded at a certain time t1 is 1200mm, and the height recorded at the next time t2 is 1195mm. The height change can be calculated as:

[0065]

[0066] This calculation method is used to calculate the difference in liquid level heights at all adjacent time points. If the measurement period 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 are calculated. All height change data are stored in the system data and marked with a timestamp for subsequent analysis to obtain the liquid level height change data.

[0067] S102: Using the liquid level height change data, calculate the height change values ​​of adjacent time nodes to obtain the liquid level height difference in multiple time periods, analyze the liquid level fluctuation trend based on the height difference data in each time period, identify the fluctuation period and fluctuation amplitude, filter out abnormal values ​​that exceed the normal range, delete the abnormal data, and obtain the liquid level fluctuation period and amplitude data set;

[0068] The height change values ​​of adjacent time nodes are calculated using the moving window analysis method through programming software (such as Python) to obtain the liquid level height difference. The analysis window length is set to N (set 5 time points), and the height difference ΔH is calculated for each time period. sum is the sum of all changes in the window, that is:

[0069]

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

[0071] ΔHsum =(-5)+3+(-2)+4+(-1)=-1;

[0072] Perform trend analysis on the data of all time periods, use the FFT (Fast Fourier Transform) method to identify the main period of liquid level fluctuation, set the fluctuation period threshold to 30 seconds to 120 seconds, and calculate the fluctuation amplitude A as the maximum change amplitude of the data point, that is:

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

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

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

[0076] Screen outliers that are beyond the normal range. The outlier screening 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 judged as an outlier and removed, and the liquid level fluctuation period and amplitude data set is obtained.

[0077] S103: based on the liquid level fluctuation period and amplitude data set, evaluating the fluctuation stability in the time series, identifying whether the liquid level fluctuation state in the differentiated time period is stable, analyzing the characteristics of the liquid level fluctuation, and obtaining the metal liquid level fluctuation state;

[0078] To evaluate the volatility stability in the time series, the sliding root mean square (RMS) calculation method is used to evaluate the volatility stability. The calculation formula is:

[0079]

[0080] If the height change data in a certain time period are -5, 3, -2, 4, and -1 mm respectively, the RMS calculation is as follows:

[0081]

[0082] The fluctuation stability judgment threshold is set. If the RMS is less than 5mm, the fluctuation is considered stable, otherwise it is judged as unstable. The RMS of data in different time periods is calculated and compared to identify whether the liquid level fluctuation state in the differentiated time periods is stable. If the RMS of a certain time period is much higher than that of the remaining time period, the RMS calculation value is set to 8mm, which indicates that the liquid level fluctuation in this time period is large. Further analyze the estimated influencing factors (such as stirring intensity, aluminum liquid replenishment frequency, etc.), combine the time series data for trend analysis, identify the characteristics of liquid level fluctuation, and obtain the metal liquid level fluctuation state.

[0083] See also Figure 3, the specific steps for obtaining the melting temperature adjustment result are:

[0084] S201: obtaining the temperature measurement value within a set period through the fluctuation state of the metal liquid level, establishing a temperature data sequence in chronological order, calculating the temperature change rate between adjacent time nodes, analyzing the temperature change rate and fluctuation amplitude within the time period, evaluating the stability of the temperature change, and obtaining the temperature change rate and stability data;

[0085] Get the temperature measurement value within the set period, arrange multiple temperature sensors during the smelting process, collect temperature data at different time nodes, and establish a temperature data sequence in chronological order. In each set time interval, such as recording the temperature value every 5 seconds, to form a complete data stream. After the temperature data sequence is established, calculate the temperature change rate between adjacent time nodes, that is, calculate the temperature change rate by calculating the temperature change in unit time. In practical applications, the sliding window method can be used to analyze the changes at multiple time points to reduce the impact of accidental errors. It is also necessary to calculate the fluctuation amplitude, that is, find the maximum and minimum temperature values ​​within the set period, and calculate the difference between the two. If the fluctuation amplitude is large, it indicates that the temperature is unstable during the smelting process and further stability analysis is required. The stability evaluation can be based on standard deviation analysis to calculate the standard deviation of the temperature change within the entire set period. If the standard deviation is small, it indicates that the temperature change is relatively stable, otherwise it is considered that there is a large fluctuation, and the temperature change rate and stability data are obtained.

[0086] S202: Analyze the temperature change trend according to the temperature change rate and stability data, adjust the power output of the heating electrode, identify the relationship between the power adjustment amplitude and the time parameter, adjust the power, match the temperature change requirements, and obtain the melting temperature adjustment result;

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

[0088]

[0089] Among them, P t Represents the power adjustment value at time t, T i Represents the temperature value at the i-th moment, T i-1 represents the temperature value at the i-1th moment, k i represents the temperature change influence coefficient at the i-th moment, t i represents the time interval of the i-th moment, τ i represents the temperature stability time constant at the i-th moment, 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 the i-th moment and the previous moment, by measuring the temperature T at each time point using a thermocouple or infrared thermometer or other equipment i and T i-1 , calculate the absolute value of the difference to obtain;

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

[0093] Time interval t i : represents the time interval at the i-th moment, 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 : It indicates the time required for the system to reach a stable temperature state. This constant can be measured experimentally and reflects the response speed of the system to temperature changes. Depending on the material and structure, τ i The value of is between 5 and 20 seconds;

[0095] Total number of sampling points n: represents the number of temperature sampling points during the calculation period, which is determined according to the monitoring frequency and total time;

[0096] Calculation example:

[0097] During the smelting process, the temperature was measured once a second using a thermocouple, and the following data (unit: degrees Celsius) were obtained: T0 = 1500, T1 = 1502, T2 = 1505, T3 = 1503, T4 = 1506;

[0098] The corresponding time interval t i The temperature change influence coefficient k is determined by experimental calibration. i Both are 1.5, 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 part:

[0105]

[0106] Calculate the denominator:

[0107]

[0108] Calculate the power adjustment value:

[0109]

[0110] The results show that in the current smelting process, based on the measured temperature changes and system characteristics, the power adjustment value calculated is approximately 23.72 units (the specific unit depends on the power measurement standard of the system). 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] See also Figure 4 , the specific steps for obtaining the heat load distribution of the smelting equipment are:

[0112] S301: using the smelting temperature adjustment result, collecting the adjusted smelting equipment furnace wall temperature data, selecting multiple temperature measuring points for measurement, recording the temperature values ​​of the multiple points, calculating the temperature difference of the temperature measuring points, identifying the temperature difference distribution between the temperature measuring points, and obtaining the furnace wall temperature difference distribution area;

[0113] Collect the adjusted furnace wall temperature data of the smelting equipment, arrange multiple temperature measuring points on the furnace wall, and select the temperature measuring points to cover different heated areas, such as the area near the heating electrode, the central area of ​​the furnace, the edge area of ​​the furnace wall, etc. Use a thermocouple or infrared thermometer to record the temperature data. The sampling interval is set to 30 seconds. The temperature data of each temperature measuring point is expressed as T i,t , where i represents the temperature measurement point number, t represents the sampling time, after obtaining the temperature data of all temperature measurement points, calculate the temperature difference between the temperature measurement points, the calculation formula is as follows:

[0114] ΔT i,j =|T i -T j |;

[0115] Taking the four temperature measurement points on the furnace wall as an example, set T1 = 850°C, T2 = 870°C, T3 = 890°C, T4 = 860°C, and calculate the temperature difference:

[0116] ΔT 1,2 =|850-870|=20℃;

[0117] ΔT2,3 =|870-890|=20℃;

[0118] ΔT 3,4 =|890-860|=30°C;

[0119] Calculate the temperature difference matrix for all temperature measurement points, analyze the temperature difference distribution between the temperature measurement points, and set the temperature difference distribution judgment threshold. i,j >25℃, the temperature difference in this area is considered to be large and is marked as a high temperature difference area. i,j If the temperature is ≤25℃, it is marked as a low temperature difference area, and the furnace wall temperature difference distribution area data set is obtained.

[0120] S302: Based on the temperature difference distribution area of ​​the furnace wall, analyzing the change trend of the furnace wall temperature difference value in the differentiated area, identifying the temperature difference change, evaluating the scope of thermal stress, and obtaining thermal stress gradient change information;

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

[0122]

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

[0124]

[0125] Calculate the temperature change rate sequence for multiple temperature measurement points, draw the temperature difference change trend curve, and identify the temperature difference fluctuation. If the temperature change rate of a certain area is much higher than that of the remaining areas (such as R Ti >0.5℃ / s), the temperature in this area changes rapidly. To further calculate the range of thermal stress, the thermal stress calculation formula is used:

[0126] σ T =E·α·ΔT;

[0127] Where E is the elastic modulus of the furnace wall material (such as 70 GPa for aluminum alloy), α is the thermal expansion coefficient (such as 23×10 -6 / ℃), if the temperature difference in a certain area 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 yield strength (such as 50 MPa), it is determined that there is a large thermal stress in this area, and the thermal stress gradient change information is obtained.

[0130] S303: According to the thermal stress gradient change information, the influence of the furnace wall thermal stress on the heat transfer is evaluated, the distribution of the heat load in the differentiated area is analyzed, and the heat load distribution of the smelting equipment is obtained;

[0131] To evaluate the influence of furnace wall thermal stress on heat transfer, the heat flux q is calculated to analyze the heat load distribution. The heat flux calculation formula 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 area is 10℃ / cm, calculate the heat flux:

[0135]

[0136] Areas with high heat flux indicate large heat loads. The heat load Q distribution is further calculated:

[0137] Q = q × A;

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

[0139] Q = -180000 × 0.5 = -90000;

[0140] Identify areas with high heat load. For example, if Q>-100000W in a certain area, it is considered that the heat load in this area is concentrated, and obtain the heat load distribution data of the smelting equipment.

[0141] See also Figure 5 , the specific steps for obtaining the electromagnetic stirring adjustment results are:

[0142] S401: Analyze the correlation between the stirring magnetic field action area and the aluminum liquid flow rate through the heat load distribution of the smelting equipment, identify the change amplitude of the aluminum liquid flow rate under the differentiated intensity, extract the influence characteristics of the stirring magnetic field on the aluminum liquid flow, and obtain the aluminum liquid flow rate change information;

[0143] The correlation between the stirring magnetic field action area and the aluminum liquid flow rate was analyzed. Multiple speed measuring points were arranged inside the smelting equipment. The aluminum liquid flow rate was measured using an electromagnetic induction velocimeter or a laser Doppler velocimeter (LDV). The measurement time interval was set to 10 seconds, and the flow rate data of each speed measuring point was recorded as v i,t, where i represents the number of the speed measurement point, and t represents the sampling time. After obtaining the flow rate data of all the speed measurement points, the relationship between the magnetic field intensity B and the aluminum liquid flow rate v is calculated, and the linear fitting method is used to determine the flow rate change trend:

[0144] v=kB+v0;

[0145] Where k is the fitting coefficient, v0 is the flow velocity without magnetic field;

[0146] When the magnetic field strength is set to 0.2T, 0.4T, and 0.6T, the measured aluminum liquid flow rates are 0.5m / s, 1.0m / s, and 1.4m / s, respectively. Then the fitting results in k≈2.5. The effect of magnetic field strength on aluminum liquid flow is determined, and the flow rate variation under different magnetic field strengths is calculated:

[0147] Δv=|v B2 -v B1 |;

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

[0149] Δv = |1.4-1.0| = 0.4 m / s;

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

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

[0152] Calculate the correlation index between the magnetic field intensity change curve and the liquid level fluctuation curve using the formula:

[0153]

[0154] Among them, RQ represents the correlation index between the magnetic field intensity change curve and the liquid level fluctuation curve, B o represents the magnetic field strength at the oth measurement moment, Represents the average magnetic field strength at the time of measurement, H o represents the liquid level at the oth measurement moment, 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 oRepresents the magnetic field strength at the oth measurement moment. Its value is collected by a magnetic field detector in Tesla T. The data comes from the record of magnetic field changes at different time points. A high-precision Hall sensor is used during the measurement process and the data is recorded once per second.

[0157] parameter Represents the average value of magnetic field strength at all measurement moments, 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,when measuring

[0161] Total number of ticks G = 5;

[0162] Calculate the average magnetic field strength:

[0163]

[0164] Parameter H o Represents the liquid level at the oth measurement moment, obtained by a laser ranging sensor in millimeters (mm). The device collects liquid level data once per second.

[0165] parameter Represents the average liquid level at all measurement moments, calculated as follows:

[0166]

[0167] The measured liquid level height data are: H1 = 150.2mm, H2 = 152.4mm, H3 = 151.8mm, H4 = 149.9mm, H5 = 150.7mm;

[0168] Calculate the average liquid level:

[0169]

[0170] Calculate the numerator part:

[0171]

[0172]

[0173] Calculate the denominator:

[0174]

[0175] Part I:

[0176]

[0177] Part II:

[0178]

[0179] Calculate the correlation index:

[0180]

[0181] The result shows that the correlation between the magnetic field intensity change curve and the liquid level fluctuation curve is 0.586, which is a medium correlation. This indicates that there is a certain linear relationship between the influence of magnetic field intensity on the fluctuation of liquid level height, but it is not completely linear. This value is used for subsequent analysis of the contribution of stirring method to liquid level fluctuation.

[0182] S403: adjusting the operation mode of electromagnetic stirring according to the liquid level fluctuation contribution data, evaluating the matching degree between the magnetic field intensity and the duration, correcting the control parameters of the electromagnetic stirring, and obtaining the electromagnetic stirring adjustment result;

[0183] Adjust the operation mode of electromagnetic stirring, select the stirring mode with high contribution, and set the initial stirring mode according to the flow characteristics of aluminum liquid. During the adjustment process, it is necessary to evaluate the matching degree of magnetic field strength and duration, that is, according to the contribution of liquid level fluctuation, calculate the appropriate magnetic field strength range and action time to avoid excessive magnetic field strength causing aluminum liquid splashing or too small magnetic field strength causing insufficient stirring. In practical applications, a dynamic adjustment strategy can be adopted, that is, according to the real-time feedback of liquid level fluctuation, the magnetic field strength is gradually corrected. If the liquid level 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 electromagnetic stirring are adjusted to optimize the magnetic field action cycle. When the liquid level fluctuation is small, the stirring time can be appropriately extended to enhance the uniform flow of aluminum liquid. When the fluctuation is large, the stirring time can be appropriately shortened to reduce liquid level instability. Through multiple rounds of optimization, the control parameters of electromagnetic stirring are corrected to ensure that the stirring effect meets the requirements of the smelting process and obtain the electromagnetic stirring adjustment results.

[0184] See also Figure 6 , the specific steps for obtaining the smelting time adjustment result are:

[0185] S501: using the electromagnetic stirring adjustment result, calculating the heat conduction rate of the heating area of ​​the smelting equipment, screening the heat conduction rate data within the set period, calculating the change of the heat conduction rate at adjacent time nodes, identifying the time point beyond the threshold range, and obtaining the abnormal heat conduction rate interval;

[0186] It is necessary to calculate the heat conduction rate of the heating area of ​​the smelting equipment. The temperature data at different positions and time points in the smelting process are collected from the temperature sensor or infrared temperature measuring equipment. The temperatures of points A, B, and C are recorded at time points such as 0 seconds, 5 seconds, and 10 seconds. The thermal conductivity k of a certain material is set to 50W / (m·K), and the distance Δx between the measuring points is 0.02m. The heat conduction rate of a certain time period is calculated according to Fourier's law of heat conduction. The formula is:

[0187]

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

[0189]

[0190] After calculating the heat conduction rate at multiple time points, filter the data within the set period and remove the outliers that exceed three times the standard deviation. If most of the data is between -60000 and -40000, and the heat conduction rate suddenly changes to -100000 at some moment, it is considered abnormal and removed. Calculate the change in adjacent time nodes:

[0191] Δq=q t+1 -q t ;

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

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

[0194] It is necessary to compare the melting time with the trend of heat conduction rate change, extract the heat conduction rate data at each time point in the abnormal interval, and analyze its change over time. In practical applications, the linear regression method can be used to fit the data and calculate the trend value of the heat conduction rate change. If the fitting result shows that the heat conduction rate is on a downward trend and the decline exceeds the set reference range, it is necessary to perform compensation calculation for the melting time. The calculation of the compensation value can be combined with the actual situation of heat loss during the melting process. In some cases, due to the uneven temperature distribution, the heat transfer efficiency in some areas is low, resulting in the temperature of some areas dropping too fast during the melting process. In order to ensure the stability of melting, it is necessary to determine the additional melting time according to the change of the heat conduction rate. When calculating the compensation time, a time compensation coefficient can be set, and the melting time length that needs to be increased can be calculated in combination with the decline in the heat conduction rate. The adjusted melting time can effectively balance the uneven state of heat transfer, 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 and obtain the melting time adjustment result.

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

[0196] The liquid level fluctuation monitoring module obtains the aluminum liquid level height data, collects the aluminum liquid level height change data, calculates the liquid level height difference, screens the abnormal fluctuation data, extracts the fluctuation period and amplitude, calculates the 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 melting furnace through the fluctuation state of the metal liquid level, calculates the temperature change rate, filters the data exceeding the melting 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 melting temperature adjustment result;

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

[0199] The electromagnetic stirring optimization module evaluates the impact of electromagnetic stirring on the flow rate and liquid level of aluminum liquid according to the heat load distribution of the smelting equipment, adjusts the electromagnetic stirring mode and duration, and obtains the electromagnetic stirring adjustment result;

[0200] The smelting time adjustment module uses the electromagnetic stirring adjustment result to calculate the change in smelting heat conduction rate, screens the data exceeding the heat conduction rate threshold, calculates the smelting time compensation value, adjusts the total smelting time, and obtains the smelting time adjustment result.

[0201] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for adjusting parameters of aluminum-based master alloy smelting equipment, characterized in that: The following steps are involved: S1: Collect the metal liquid level data in the aluminum-based master alloy smelting equipment, collect the aluminum liquid surface height change at a fixed time interval, identify the liquid level height difference, fluctuation amplitude and fluctuation trend, and obtain the metal liquid level fluctuation state; S2: Calculate the temperature change rate based on the metal liquid level fluctuation state and the temperature data of the smelting equipment, analyze the smelting temperature change trend, adjust the heating electrode power, and obtain the smelting temperature adjustment result; S3: Based on the smelting temperature adjustment result, the temperature data of the furnace wall of the smelting equipment after the adjustment is collected, the temperature difference of the furnace wall between multiple points is calculated, the thermal stress distribution is identified, the influence of the thermal stress on the energy transfer is evaluated, and the thermal load distribution of the smelting equipment is obtained; S4: using the heat load distribution of the smelting equipment, identifying the influence of electromagnetic stirring on the flow state of aluminum liquid, calculating the liquid level fluctuation contribution data, adjusting the electromagnetic stirring mode and time, and obtaining the electromagnetic stirring adjustment result; S5: Based on the electromagnetic stirring adjustment result, calculate the change in heat conduction rate of the heated area of ​​the smelting equipment, set a heat conduction rate threshold, filter the smelting time that exceeds the threshold, and obtain the smelting time adjustment result.

2. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 1, characterized in that: The metal liquid level fluctuation state includes the liquid level height difference, 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 the temperature gradient of the heated area; the electromagnetic stirring adjustment result includes the adjustment amplitude of the stirring intensity, the stirring time arrangement, and the stirring mode selection result; the smelting time adjustment result includes the set heat conduction rate threshold, the screened 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 steps for obtaining the metal liquid level fluctuation state are specifically as follows: S101: obtaining the metal liquid level data in the aluminum-based master alloy smelting equipment, detecting the height of the aluminum liquid surface at fixed time intervals, recording the liquid level height values ​​corresponding to multiple time nodes, calculating the height changes at consecutive time nodes, and obtaining the liquid level height change data; S102: using the liquid level height change data, calculating the height change values ​​of adjacent time nodes to obtain the liquid level height difference in multiple time periods, analyzing the liquid level fluctuation trend based on the height difference data in each time period, identifying the fluctuation period and fluctuation amplitude, screening out abnormal values ​​beyond the normal range, deleting the abnormal data, and obtaining a liquid level fluctuation period and amplitude data set; S103: According to the liquid level fluctuation period and amplitude data set, evaluate the fluctuation stability in the time series, identify whether the liquid level fluctuation state in the differentiated time period is stable, analyze the characteristics of the liquid level fluctuation, and obtain the metal liquid level fluctuation state.

4. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 1, characterized in that: The steps for obtaining the melting temperature adjustment result are specifically as follows: S201: obtaining the temperature measurement value within a set period through the metal liquid level fluctuation state, establishing a temperature data sequence in chronological order, calculating the temperature change rate between adjacent time nodes, analyzing the temperature change rate and fluctuation amplitude within the time period, evaluating the stability of the temperature change, and obtaining the temperature change rate and stability data; S202: Analyze the temperature change trend according to the temperature change rate and stability data, adjust the heating electrode power output, identify the relationship between the power adjustment amplitude and the time parameter, perform power adjustment, 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 power output of the heating electrode is adjusted using the formula: Among them, P t Represents the power adjustment value at time t, T i Represents the temperature value at the i-th moment, T i-1 represents the temperature value at the i-1th moment, k i represents the temperature change influence coefficient at the i-th moment, t i represents the time interval of the i-th moment, τ i represents the temperature stability time constant at the i-th moment, 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 steps for obtaining the heat load distribution of the smelting equipment are specifically as follows: S301: using the smelting temperature adjustment result, collecting the adjusted smelting equipment furnace wall temperature data, selecting multiple temperature measuring points for measurement, recording the temperature values ​​of the multiple points, calculating the temperature difference of the temperature measuring points, identifying the temperature difference distribution between the temperature measuring points, and obtaining the furnace wall temperature difference distribution area; S302: Based on the furnace wall temperature difference distribution area, analyzing the change trend of the furnace wall temperature difference value in the differentiated area, identifying the temperature difference change, evaluating the thermal stress action range, and obtaining thermal stress gradient change information; S303: According to the thermal stress gradient change information, the influence of the furnace wall thermal stress on the heat transfer is evaluated, the distribution of the heat load in the differentiated area is analyzed, and the heat load distribution of the smelting equipment is obtained.

7. The method for adjusting parameters of aluminum-based master alloy smelting equipment according to claim 1, characterized in that: The steps for obtaining the electromagnetic stirring adjustment result are specifically as follows: S401: analyzing the correlation between the stirring magnetic field action area and the aluminum liquid flow rate through the heat load distribution of the smelting equipment, identifying the variation range of the aluminum liquid flow rate under the differentiated intensity, extracting the influence characteristics of the stirring magnetic field on the aluminum liquid flow, and obtaining the aluminum liquid flow rate variation information; S402: Based on the aluminum liquid flow rate change information, evaluate the influence of the stirring magnetic field on the liquid level change, calculate the correlation index between the magnetic field intensity change curve and the liquid level fluctuation curve, identify the contribution degree of the differentiated stirring mode to the liquid level fluctuation, and obtain the liquid level fluctuation contribution degree data; S403: According to the liquid level fluctuation contribution data, the operation mode of electromagnetic stirring is adjusted, the matching degree between the magnetic field intensity and the duration is evaluated, the control parameters of electromagnetic stirring are corrected, and the electromagnetic stirring adjustment result is obtained.

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 variation curve and the liquid level fluctuation curve is calculated using the formula: Among them, RQ represents the correlation index between the magnetic field intensity change curve and the liquid level fluctuation curve, B o represents the magnetic field strength at the oth measurement moment, Represents the average magnetic field strength at the time of measurement, H o represents the liquid level at the oth measurement moment, 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 steps for obtaining the smelting time adjustment result are specifically as follows: S501: using the electromagnetic stirring adjustment result, calculating the heat conduction rate of the heating area of ​​the smelting equipment, screening the heat conduction rate data within a set period, calculating the change in the heat conduction rate of adjacent time nodes, identifying the time point beyond the threshold range, and obtaining the abnormal heat conduction rate interval; S502: Based on the abnormal heat transfer rate interval, compare the smelting time with the change trend of the heat transfer rate, calculate the smelting time compensation value, adjust the total smelting time, correct the unbalanced state of heat transfer during the smelting process, and obtain the smelting time adjustment result.

10. Aluminum-based master alloy smelting equipment parameter adjustment system, characterized in that: According to any one of claims 1 to 9, the method for adjusting parameters of aluminum-based master alloy smelting equipment comprises: The liquid level fluctuation monitoring module obtains the aluminum liquid level height data, collects the aluminum liquid level height change data, calculates the liquid level height difference, screens the abnormal fluctuation data, extracts the fluctuation period and amplitude, calculates the liquid level fluctuation stability index, and obtains the metal liquid level fluctuation state; The temperature fluctuation analysis module obtains the temperature measurement value of the smelting furnace through the metal liquid level fluctuation state, calculates the temperature change rate, filters the data exceeding 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; The furnace wall heat load assessment module uses the smelting temperature adjustment result to calculate the temperature difference of the furnace wall temperature measurement points, identify the furnace wall temperature difference distribution, analyze the thermal stress action range, analyze the furnace wall heat load change trend, and obtain the smelting equipment heat load distribution; The electromagnetic stirring optimization module evaluates the influence of electromagnetic stirring on the flow rate and liquid level of aluminum liquid according to the heat load distribution of the smelting equipment, adjusts the electromagnetic stirring mode and duration, and obtains the electromagnetic stirring adjustment result; The smelting time adjustment module uses the electromagnetic stirring adjustment result to calculate the change in smelting heat conduction rate, screens data exceeding the heat conduction rate threshold, calculates the smelting time compensation value, adjusts the total smelting time, and obtains the smelting time adjustment result.

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