Casting disc temperature gradient intelligent control device for aluminum bar continuous casting

Abstract

The invention discloses a casting disc temperature gradient intelligent control device for aluminum bar continuous casting, and relates to the technical field of molten metal casting processing, the device comprises a casting disc body, one end of the casting disc body is provided with an aluminum water inlet launder, and the other end of the casting disc body is provided with an aluminum discharge launder; a casting disc hot end is arranged at one end of the inner side of the casting disc body, a casting disc cold end is arranged at the other end of the inner side of the casting disc body, and a plurality of silicon carbide rods which are linearly arranged are arranged at the bottom end of the inner side of the casting disc body; the diameter of the silicon carbide rod is gradually reduced from the cold end of the casting disc to the hot end of the casting disc, electric lead copper sheets are arranged at two ends of the silicon carbide rod, the electric lead copper sheet at one end of the silicon carbide rod is connected with the pulse width regulator, and the electric lead copper sheet at the other end of the silicon carbide rod is connected with the negative electrode of the power supply. A silicon carbide rod heating mode with diameter gradient distribution is adopted, so that the temperature of molten aluminum of the whole casting disc tends to be consistent, and dynamic balance of a temperature field in the casting process is ensured.

Description

Technical Field

[0001] The invention relates to the technical field of molten metal casting processing, and in particular to a casting plate temperature gradient intelligent control device for continuous casting of aluminum bars. Background Art

[0002] The aluminum rod continuous casting process is an important production process in the molten metal processing industry. Among them, deep well casting technology has become the mainstream process for aluminum rod production due to its advantages such as high production efficiency and stable product quality. In the deep well casting process, molten aluminum at about 720°C is usually injected into the casting plate, and the aluminum rod is crystallized and formed through the mold plate, shaping graphite ring, casting machine traction system and other devices, combined with water spray cooling when the ingot head moves downward; in this process, the casting plate is a key device for carrying molten aluminum and performing initial molding, and its temperature field distribution directly affects the quality and production efficiency of the casting product. Therefore, the temperature control technology of the casting plate has always been the focus of industry research.

[0003] At present, the casting plate preheating methods commonly used in industrial production mainly include natural gas heating and electric fan heating. The natural gas heating method directly heats the surface of the casting plate through the burner, which has the characteristics of fast heating and simple operation; the electric fan heating uses hot air to heat the casting plate as a whole, and the heat distribution is more uniform. Both preheating methods have been widely used in actual production and have formed relatively complete operating procedures; especially in the semi-continuous casting process, the preheating quality of the casting plate has an important influence on the stability of the subsequent casting process.

[0004] However, traditional preheating methods have obvious technical limitations. Natural gas heating, as the flame directly acts on the surface of the casting plate, is prone to local overheating, resulting in uneven heating and cracking of the refractory material, significantly shortening the service life of the refractory material; although the temperature distribution of electric fan preheating is relatively uniform, the preheating time is long and the energy utilization efficiency is low; more importantly, these two preheating methods cannot continue to heat the casting plate after the casting begins, resulting in the aluminum liquid temperature at the cold end of the casting plate being usually 5-10°C lower than the hot end during semi-continuous casting. This temperature gradient not only affects the stability of the metallurgical quality of the cast rod, but also increases the energy consumption of the production process.

[0005] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0006] In response to the problems in the related art, the present invention proposes an intelligent control device for the temperature gradient of a casting plate for continuous casting of aluminum rods, which is capable of heating silicon carbon rods with a diameter gradient distribution, so that the temperature of the aluminum liquid in the entire casting plate tends to be consistent, ensuring the dynamic balance of the temperature field during the casting process, thereby solving the problems in the prior art of easy cracking of refractory materials, low preheating efficiency, high energy consumption and unstable metallurgical quality of cast rods.

[0007] To this end, the specific technical solution adopted by the present invention is as follows:

[0008] A casting plate temperature gradient intelligent control device for aluminum rod continuous casting, the casting plate temperature gradient intelligent control device for aluminum rod continuous casting comprising a casting plate body, one end of the casting plate body is provided with an aluminum water inlet flow channel, the other end of the casting plate body is provided with an aluminum discharge flow channel, one end of the inner side of the casting plate body is provided with a casting plate hot end matched with the aluminum water inlet flow channel, the other end of the inner side of the casting plate body is provided with a casting plate cold end matched with the aluminum discharge flow channel, and the inner bottom end of the casting plate body is provided with a plurality of linearly arranged silicon carbon rods;

[0009] The diameter of the silicon carbon rod gradually decreases from the cold end of the casting disk to the hot end of the casting disk. Silicon felt wool is arranged on the top and bottom of the silicon carbon rod. Electric conductor copper sheets are arranged on both ends of the silicon carbon rod. The electric conductor copper sheet at one end of the silicon carbon rod is connected to the pulse width regulator, and the electric conductor copper sheet at the other end of the silicon carbon rod is connected to the negative electrode of the power supply.

[0010] A plurality of temperature measuring thermocouples are arranged on one side of the casting plate body, a multi-channel temperature acquisition module is arranged at one end of the temperature measuring thermocouple, a PID control element is arranged at one end of the multi-channel temperature acquisition module, one end of the PID control element is connected to the pulse width regulator, and the other end of the PID control element is connected to the positive pole of the power supply.

[0011] Furthermore, the casting plate temperature gradient intelligent control device for aluminum rod continuous casting comprises:

[0012] S1. Using the temperature field partition control algorithm, the target temperature values ​​and temperature weight coefficients at different positions of the casting disk are obtained, a weighted temperature data set is established, and the partition temperature deviation values ​​of the cold end of the casting disk, the middle of the casting disk body, and the hot end of the casting disk are obtained through temperature compensation correction and regional correlation analysis;

[0013] S2. Based on the silicon carbon rod resistance calculation model, the inherent resistance value of the silicon carbon rod in each area is calculated, and the power density of each area is analyzed in combination with the partition temperature deviation value. The overall power supply duty cycle is calculated using the regional power density to generate the optimal PWM control signal;

[0014] S3. According to the optimal PWM control signal, the overall power supply of the silicon carbon rod is adjusted in real time through the pulse width regulator.

[0015] Furthermore, the temperature field partition control algorithm is used to obtain the target temperature values ​​and temperature weight coefficients at different positions of the casting disk, establish a weighted temperature data set, and obtain the partition temperature deviation values ​​of the cold end of the casting disk, the middle of the casting disk body, and the hot end of the casting disk through temperature compensation correction and regional correlation analysis. The steps include:

[0016] S11. Based on the casting process parameter requirements, the target temperature values ​​at different positions of the casting plate are obtained through the temperature field partition control algorithm, and the temperature weight coefficient is solved in combination with the diameter of the silicon carbon rod to establish a regional temperature dynamic balance model;

[0017] S12, according to the different sampling periods of the cold end of the casting plate, the middle of the casting plate body and the hot end of the casting plate, the multi-channel temperature acquisition module is used to collect data from each temperature measuring thermocouple, and a weighted temperature data set is established in combination with the temperature weight coefficient;

[0018] S13. Based on the weighted temperature data set, the temperature characteristic value of each area is obtained, and through temperature compensation correction and regional correlation analysis, the zone temperature deviation values ​​of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk are obtained.

[0019] Furthermore, based on the casting process parameter requirements, the target temperature values ​​at different positions of the casting plate are obtained through the temperature field partition control algorithm, and the temperature weight coefficient is solved in combination with the diameter of the silicon carbon rod. The regional temperature dynamic balance model is established, including the following steps:

[0020] S111, according to the casting process parameter requirements, using the temperature field partition control algorithm to solve the target temperature values ​​at different positions of the casting plate;

[0021] The expression of temperature field partition control algorithm is:

[0022] T(x)=T 0 +k×(xL / 2)

[0023] Where T(x) is the target temperature, T 0 is the overall target temperature of the casting plate, x is the horizontal distance from the measuring point to the inner wall of the hot end side of the casting plate body, L is the internal horizontal length of the casting plate body, and k is the temperature gradient coefficient;

[0024] S112, based on the target temperature values ​​at different positions of the casting disk and in combination with the diameter distribution of the silicon carbon rods, the power compensation coefficient of each area of ​​the casting disk is calculated, and the target temperature threshold is determined through regional temperature mapping;

[0025] The expression of the power compensation coefficient of each area of ​​the casting plate is:

[0026] P(d)=(d / d min ) 2

[0027] Where P(d) is the power compensation coefficient of the silicon carbon rod with a diameter of d, min It is the minimum diameter reference value of silicon carbon rod;

[0028] S113. According to the power compensation coefficient of each area, the temperature weight coefficient is obtained through weighted calculation, and the target temperature values ​​and temperature weight coefficients at different positions of the casting plate are used to construct a regional temperature dynamic balance model.

[0029] Furthermore, the expression of the temperature weight coefficient is:

[0030] W(i)=P(d) i ×[1+α×(Lx i ) / L]

[0031] Where W(i) is the temperature weight coefficient of the i-th silicon carbon rod, P(d) i is the power compensation coefficient of the i-th silicon carbon rod, α is the position compensation factor, x i is the horizontal distance from the center of the i-th silicon carbon rod to the inner wall of the hot end side of the casting plate body, and L is the horizontal length of the inner side of the casting plate body;

[0032] The expression of the regional temperature dynamic balance model is:

[0033] T bla (i) = T(x) i ×W(i)

[0034] Where, T bla (i) is the equilibrium temperature of the i-th silicon carbon rod position, T(x) i is the target temperature of the i-th silicon carbon rod.

[0035] Furthermore, according to the different sampling periods of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk, a multi-channel temperature acquisition module is used to collect data from each temperature measuring thermocouple, and a weighted temperature data set is established in combination with a temperature weight coefficient, including the following steps:

[0036] S121, based on the cold and hot end temperature difference compensation requirement, using the cold and hot end area sampling algorithm, obtain the difference sampling period of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk;

[0037] The expression of the cold and hot end area sampling algorithm is:

[0038] Ts(z)=T 0 s×[1+η×σ(z) / σ max]

[0039] Where Ts(z) is the difference sampling period of region z, T 0 s is the reference sampling period, η is the fluctuation response coefficient, σ(z) is the temperature standard deviation in the preset time window of area z, σ max is the maximum allowed temperature standard deviation;

[0040] S122, using the difference sampling period, collecting data from each temperature measuring thermocouple through a multi-channel temperature acquisition module to obtain an original temperature data sequence, and performing data preprocessing;

[0041] S123, performing regional temperature weighting operation according to the preprocessed temperature data by using the temperature weight coefficient to obtain a weighted temperature data set;

[0042] The expression of regional temperature weighted operation is:

[0043] T w (z) = T raw (z)×W(z)×Q(z)

[0044] Where, T w (z) is the weighted temperature of region z, T raw (z) is the original sampling temperature of region z, W(z) is the temperature weight coefficient of region z, and Q(z) is the data quality coefficient of region z.

[0045] Furthermore, based on the weighted temperature data set, the temperature characteristic value of each region is obtained, and through temperature compensation correction and regional correlation analysis, the partition temperature deviation values ​​of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk are obtained, which includes the following steps:

[0046] S131, establishing a real-time temperature feature sequence for each region according to the weighted temperature data set, and obtaining a temperature feature value for each region using a sliding window method, wherein the temperature feature value includes an average feature temperature and a temperature fluctuation range;

[0047] S132, based on the temperature characteristic value of each area, using the preset temperature threshold of each area to calculate the initial temperature deviation data, and perform temperature compensation correction;

[0048] S133. According to the corrected temperature deviation data, the zone temperature deviation values ​​of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk are obtained through regional correlation analysis.

[0049] Furthermore, the expression of temperature compensation correction is:

[0050] ΔT raw (z) = T char (z) / W(z)-T set(z)

[0051] ΔT mod (z) = ΔT raw (z)×[1+θ×V char (z) / V max ]

[0052] In the formula, ΔT raw (z) is the original temperature deviation of region z, ΔT mod (z) is the temperature deviation data after temperature compensation correction in area z, T char (z) is the average characteristic temperature of region z, T set (z) is the target temperature threshold of area z, θ is the fluctuation compensation coefficient, V max is the maximum allowable temperature fluctuation range, W(z) is the temperature weight coefficient of region z;

[0053] The expression of regional correlation analysis is:

[0054] ΔT final (z) = ΔT mod (z)+λ×[ΔT mod (z-1)+ΔT mod (z+1)] / 2

[0055] In the formula, ΔT final (z) is the partition temperature deviation value of area z, λ is the regional correlation coefficient, and z-1 and z+1 represent the area on one side and the area on the other side adjacent to area z, respectively.

[0056] Furthermore, based on the silicon carbon rod resistance calculation model, the inherent resistance value of the silicon carbon rod in each region is calculated, and the power density of each region is analyzed in combination with the partition temperature deviation value. The overall power supply duty cycle is calculated using the regional power density, and the optimal PWM control signal is generated, including the following steps:

[0057] S21, according to the diameter distribution data of the silicon carbon rod, the inherent resistance value of the silicon carbon rod in each area is obtained by using the silicon carbon rod resistance calculation model;

[0058] S22. Analyze the power density of each silicon carbon rod based on the inherent resistance value of the silicon carbon rods in each region, and analyze the regional power density of each region in combination with the zone temperature deviation value;

[0059] S23, calculating the overall power supply duty cycle of the casting disk temperature gradient intelligent control device for aluminum rod continuous casting according to the regional power density of each area, and outputting the optimal PWM control signal through the pulse width regulator 4.

[0060] Furthermore, the expression of the silicon carbon rod resistance calculation model is:

[0061] R(di ,T)=ρ(T)×L / [π×(d i / 2) 2 ]

[0062] In the formula, R(d i ,T) is the resistance value of the i-th silicon carbon rod at temperature T, ρ(T) is the resistivity at temperature T, L is the effective length of the silicon carbon rod, d i is the diameter of the i-th silicon carbon rod;

[0063] The power density of each silicon carbon rod is expressed as:

[0064] P(d i )=U 2 / [R(d i ,T)×π×(d i / 2) 2 ]

[0065] In the formula, P(d i ) is the power density of the i-th silicon carbon rod, and U is the supply voltage;

[0066] The expression of regional power density is:

[0067] P(z)=[∑P(d i )]×[1+B×ΔT final (z) / ΔT max ]

[0068] Where P(z) is the regional power density of region z, ∑P(d i ) is the sum of the power densities of all silicon carbon rods in area z, B is the temperature compensation coefficient, ΔT final (z) is the zone temperature deviation value of area z, ΔT max is the maximum allowable temperature deviation.

[0069] The beneficial effects of the present invention are:

[0070] (1) The intelligent control device for the temperature gradient of the casting plate for continuous casting of aluminum rods provided by the present invention realizes precise control of the temperature field of the entire casting plate by installing silicon carbon rods with diameters ranging from large to small at the bottom of the casting plate and using silicon felt wool for heat insulation treatment, combined with real-time temperature monitoring and PWM control system. The present invention not only overcomes the technical defects of traditional natural gas heating and electric fan heating methods such as local overheating and long preheating time, but also significantly improves the service life of the refractory material of the casting plate and reduces the energy consumption of the production process.

[0071] (2) The present invention effectively solves the technical problem that the aluminum liquid temperature at the cold end is 5-10°C lower than that at the hot end in the traditional casting process by configuring silicon carbide rods with larger diameters in the cold end area of ​​the casting disk and silicon carbide rods with smaller diameters in the hot end area. This gradient heating method makes the aluminum liquid temperature in each area of ​​the casting disk tend to be consistent, significantly improves the uniformity of the metallurgical quality of the cast rods, effectively avoids the inconsistency of compound size and dendrite spacing in the metallurgy of the cast rods, and provides a reliable technical guarantee for improving the overall quality of aluminum alloy cast rods. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0073] Figure 1 is a structural schematic diagram of a casting plate temperature gradient intelligent control device for aluminum rod continuous casting according to an embodiment of the present invention;

[0074] Figure 2 is a front view of a casting plate temperature gradient intelligent control device for aluminum rod continuous casting according to an embodiment of the present invention;

[0075] Figure 3 2 is a left view of a casting plate temperature gradient intelligent control device for aluminum rod continuous casting according to an embodiment of the present invention;

[0076] Figure 4 The present invention is a schematic diagram of the working process of a casting disk temperature gradient intelligent control device for continuous casting of aluminum bars according to an embodiment of the present invention.

[0077] In the figure:

[0078] 1. Silicon carbon rod; 2. Electric conductor copper sheet; 3. Temperature measuring thermocouple; 4. Pulse width regulator; 5. PID control element; 6. Hot end of casting plate; 7. Aluminum liquid inlet flow channel; 8. Aluminum discharge flow channel; 9. Cold end of casting plate; 10. Casting plate body; 11. Positive pole of power supply; 12. Negative pole of power supply; 13. Silicon felt wool; 14. Multi-channel temperature acquisition module. DETAILED DESCRIPTION

[0079] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention and are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, ordinary technicians in the field should be able to understand other possible implementations and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0080] According to an embodiment of the present invention, a casting disk temperature gradient intelligent control device for continuous casting of aluminum bars is provided.

[0081] The present invention is further described with reference to the accompanying drawings and specific embodiments. Figure 1-Figure 3 As shown, according to one embodiment of the present invention, a casting plate temperature gradient intelligent control device for aluminum rod continuous casting is provided, the casting plate temperature gradient intelligent control device for aluminum rod continuous casting comprises a casting plate body 10, one end of the casting plate body 10 is provided with an aluminum water inlet flow channel 7, the other end of the casting plate body 10 is provided with an aluminum discharge flow channel 8, one end of the inner side of the casting plate body 10 is provided with a casting plate hot end 6 matched with the aluminum water inlet flow channel 7, the other end of the inner side of the casting plate body 10 is provided with a casting plate cold end 9 matched with the aluminum discharge flow channel 8, and the inner bottom end of the casting plate body 10 is provided with a plurality of linearly arranged silicon carbon rods 1;

[0082] The diameter of the silicon carbon rod 1 gradually decreases from the cold end 9 of the casting disk to the hot end 6 of the casting disk. Silicon felt wool 13 is provided at the top and bottom of the silicon carbon rod 1. Electric conductor copper sheets 2 are provided at both ends of the silicon carbon rod 1. The electric conductor copper sheet 2 at one end of the silicon carbon rod 1 is connected to the pulse width regulator 4, and the electric conductor copper sheet 2 at the other end of the silicon carbon rod 1 is connected to the negative electrode 12 of the power supply.

[0083] A plurality of temperature measuring thermocouples 3 are arranged on one side of the casting disk body 10, a multi-channel temperature acquisition module 14 is arranged at one end of the temperature measuring thermocouple 3, a PID control element 5 is arranged at one end of the multi-channel temperature acquisition module 14, one end of the PID control element 5 is connected to the pulse width regulator 4, and the other end of the PID control element 5 is connected to the positive pole 11 of the power supply.

[0084] Specifically, in this embodiment, a total of 10 silicon carbon rods 1 are arranged at the inner bottom end of the casting disk body 10, and the diameters of the silicon carbon rods 1 from the cold end 9 of the casting disk to the hot end 6 of the casting disk are: 40mm, 38mm, 35mm, 32mm, 30mm, 28mm, 25mm, 22mm, 20mm, and 18mm.

[0085] Specifically, in this embodiment, there are a total of three temperature measuring thermocouples 3 arranged on the casting disk body 10, including one in the cold end 9 area of ​​the casting disk (corresponding to the 40-32mm silicon carbon rod area), one in the middle area of ​​the casting disk body 10 (corresponding to the 30-25mm silicon carbon rod area), and one in the hot end 6 area of ​​the casting disk (corresponding to the 22-18mm silicon carbon rod area).

[0086] Specifically, the present invention installs an electrically heated silicon carbon rod 1 at the bottom of the inner side of the casting plate body 10, and the diameters of the silicon carbon rods 1 are arranged in descending order from the cold end to the hot end. Since the silicon carbon rods 1 with large diameters have high power and high heat generation, the heating temperature of the cold end 9 of the casting plate is higher than that of the hot end 6 of the casting plate, thereby compensating for the problem that the aluminum water temperature at the cold end is lower than that at the hot end during the casting process, and making the aluminum water temperature in the entire casting plate tend to be consistent; in addition, since the heating method of the silicon carbon rods 1 is more uniform than that of natural gas heating, it can reduce problems such as cracking of the refractory material of the casting plate, which is beneficial to improving the service life of the refractory material of the casting plate.

[0087] Specifically, when the prior art uses natural gas for preheating, the refractory material of the casting plate is prone to local rapid heating, resulting in greater thermal expansion and contraction at the heated position than at the unheated position, which is likely to cause cracking and damage to the refractory material after long-term use, reducing its service life. The present invention uses electric heating to enable the refractory material to absorb heat evenly, effectively extending the service life of the refractory material; at the same time, the present invention uses components such as a pulse width regulator 4 and a temperature measuring thermocouple 3 to control the aluminum liquid temperature or preheating temperature on the casting plate in real time, which not only improves the temperature control accuracy, but also enables the casting plate to reach the predetermined temperature faster.

[0088] In one embodiment, the intelligent control device for the temperature gradient of the casting plate for continuous casting of aluminum rods comprises:

[0089] S1. Using the temperature field partition control algorithm, the target temperature values ​​and temperature weight coefficients at different positions of the casting disk are obtained, a weighted temperature data set is established, and the partition temperature deviation values ​​of the cold end 9 of the casting disk, the middle part of the casting disk body 10 and the hot end 6 of the casting disk are obtained through temperature compensation correction and regional correlation analysis;

[0090] S2. Based on the silicon carbon rod resistance calculation model, the inherent resistance value of the silicon carbon rod 1 in each area is calculated, and the power density of each area is analyzed in combination with the partition temperature deviation value. The overall power supply duty cycle is calculated using the regional power density to generate the optimal PWM control signal;

[0091] S3. According to the optimal PWM control signal, the overall power supply of the silicon carbon rod 1 is adjusted through the pulse width regulator 4, and the power distribution is automatically realized based on the gradient diameter design of the silicon carbon rod 1 (thick at the cold end and thin at the hot end), and a dynamic balanced control system of the global temperature field of the casting disk is established.

[0092] In one embodiment, the temperature field partition control algorithm is used to obtain the target temperature values ​​and temperature weight coefficients at different positions of the casting disk, establish a weighted temperature data set, and obtain the partition temperature deviation values ​​of the cold end 9 of the casting disk, the middle part of the casting disk body 10, and the hot end 6 of the casting disk through temperature compensation correction and regional correlation analysis, including the following steps:

[0093] S11, using the temperature field partition control algorithm, obtaining the target temperature values ​​and temperature weight coefficients at different positions of the casting disk, establishing a weighted temperature data set, and obtaining the partition temperature deviation values ​​of the cold end 9 of the casting disk, the middle part of the casting disk body 10, and the hot end 6 of the casting disk through temperature compensation correction and regional correlation analysis;

[0094] S12, according to the different sampling periods of the cold end 9 of the casting disk, the middle part of the casting disk body 10 and the hot end 6 of the casting disk, the multi-channel temperature acquisition module 14 is used to collect data from each temperature measuring thermocouple 3, and a weighted temperature data set is established in combination with the temperature weight coefficient;

[0095] S13. Based on the weighted temperature data set, the temperature characteristic value of each area is obtained, and through temperature compensation correction and regional correlation analysis, the zone temperature deviation values ​​of the cold end 9 of the casting disk, the middle part of the casting disk body 10 and the hot end 6 of the casting disk are obtained.

[0096] In one embodiment, the temperature field partition control algorithm is used to obtain the target temperature values ​​and temperature weight coefficients at different positions of the casting disk, establish a weighted temperature data set, and obtain the partition temperature deviation values ​​of the cold end 9 of the casting disk, the middle part of the casting disk body 10, and the hot end 6 of the casting disk through temperature compensation correction and regional correlation analysis, including the following steps:

[0097] S111, according to the casting process parameter requirements, using the temperature field partition control algorithm to solve the target temperature values ​​at different positions of the casting plate;

[0098] Specifically, in this embodiment, the overall target temperature T of the casting plate is set based on the casting process parameter requirements. 0 The temperature is 720°C, and the temperature field partition control algorithm adopts a linear gradient model to calculate the target temperature at any position in the casting disk body 10 through the following expression:

[0099] T(x)=T 0 +k×(xL / 2)

[0100] Wherein, T(x) is the target temperature, x is the horizontal distance from the measuring point to the inner wall of the hot end side of the casting plate body 10, L is the horizontal length of the inner side of the casting plate body 10 (800 mm in this embodiment), k is the temperature gradient coefficient (-5°C / m in this embodiment), and the value range of x is [0, L]. When x = 0, it corresponds to the inner wall position of the hot end side of the casting plate body 10; when x = L, it corresponds to the inner wall position of the cold end side of the casting plate body 10.

[0101] Specifically, in the above embodiment, when x=200 mm (i.e., 200 mm from the inner wall of the hot end side of the casting disk body 10), the target temperature at this position is calculated to be T(0.2)=720+(-5)×(0.2-0.4)=721°C.

[0102] S112, based on the target temperature values ​​at different positions of the casting disk and in combination with the diameter distribution of the silicon carbon rods 1 (Φ40 mm to Φ18 mm), the power compensation coefficient of each area of ​​the casting disk is calculated, and the target temperature threshold is determined through regional temperature mapping;

[0103] Specifically, according to the diameter distribution characteristics of the silicon carbon rod 1, the power compensation coefficient is calculated using a square relationship, and the expression is:

[0104] P(d)=(d / d min ) 2

[0105] Where P(d) is the power compensation coefficient of a silicon carbon rod with a diameter of d mm, d min It is the minimum diameter reference value of the silicon carbon rod 1 (18 mm in this embodiment).

[0106] Specifically, in this embodiment:

[0107] The cold end area (40mm silicon carbon rod) is P(40)=(40 / 18)^2=4.94;

[0108] The middle area (28 mm silicon carbon rod) is P(28) = (28 / 18)^2 = 2.42;

[0109] The hot end area (18mm silicon carbon rod) is P(18)=(18 / 18)^2=1.00.

[0110] Specifically, based on the power compensation coefficient, a regional temperature mapping relationship is established:

[0111] Target temperature threshold of cold end area (40, 38, 35, 32 mm) = 725°C (T 0 +5℃);

[0112] Target temperature threshold for the middle area (30, 28, 25 mm) = 720°C (T0 );

[0113] Target temperature threshold of hot end area (22, 20, 18 mm) = 718°C (T 0 -2℃).

[0114] S113. According to the power compensation coefficient of each area, the temperature weight coefficient is obtained through weighted calculation, and the target temperature values ​​at different positions of the casting plate and the temperature weight coefficient matrix are used to construct a regional temperature dynamic balance model.

[0115] Specifically, the expression of the temperature weight coefficient is:

[0116] W(i)=P(d) i ×[1+α×(Lx i ) / L]

[0117] Where W(i) is the temperature weight coefficient of the i-th silicon carbon rod, P(d) i is the power compensation coefficient of the i-th silicon carbon rod, α is the position compensation factor (the value is 0.2 in this embodiment), x i is the horizontal distance from the center of the silicon carbon rod to the inner wall of the hot end side of the casting plate body 10, and L is the horizontal length of the inner side of the casting plate body 10, which is 800 mm.

[0118] Specifically, in this embodiment, taking the first silicon carbon rod (40 mm) at the cold end as an example, position x i =800mm, P(40)=4.94, W(1)=4.94×[1+0.2×(800-800) / 800]=4.94 is calculated, and the regional temperature dynamic balance model is finally established, and the expression is:

[0119] T bla (i) = T(x) i ×W(i)

[0120] Where, T bla (i) is the equilibrium temperature of the i-th silicon carbon rod position, T(x) i is the target temperature of the i-th silicon carbon rod.

[0121] Specifically, the equilibrium temperature T at the 40mm silicon carbon rod position at the cold end is calculated through the regional temperature dynamic equilibrium model. bla (1) = 725 × 4.94 = 3581.5 (unnormalized temperature value). These calculation results will be used as the basic parameters for subsequent temperature control.

[0122] In one embodiment, according to the difference sampling periods of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk, the multi-channel temperature acquisition module 14 is used to collect data from each temperature measuring thermocouple 3, and the weighted temperature data set is established in combination with the temperature weight coefficient, including the following steps:

[0123] S121, based on the cold and hot end temperature difference compensation requirement, using the cold and hot end area sampling algorithm, obtain the difference sampling period of the casting disk cold end 9, the middle of the casting disk body 10 and the casting disk hot end 6;

[0124] The expression of the cold and hot end area sampling algorithm is:

[0125] Ts(z)=T 0 s×[1+η×σ(z) / σ max ]

[0126] Where Ts(z) is the difference sampling period of region z (ms), T 0 s is the reference sampling period (100ms in this embodiment), η is the fluctuation response coefficient (2.0 in this embodiment), σ(z) is the temperature standard deviation within the preset time window of area z (the most recent 20 samples in this embodiment), σ max is the maximum allowable temperature standard deviation (5°C in this embodiment).

[0127] Specifically, in the above embodiment, the following is calculated:

[0128] Cold end 9 area (z = 1) σ = 3.2 ° C, Ts = 100 × [1 + 2.0 × 3.2 / 5] = 228ms

[0129] Middle area (z = 2) σ = 2.1 ° C, Ts = 100 × [1 + 2.0 × 2.1 / 5] = 184ms

[0130] Hot end 6 area (z=3) σ=1.5°C, Ts=100×[1+2.0×1.5 / 5]=160ms.

[0131] S122, using a differentiated sampling period, collecting data from each temperature measuring thermocouple 3 through a multi-channel temperature acquisition module 14, obtaining an original temperature data sequence, and performing data preprocessing;

[0132] Specifically, in this embodiment, a sliding window method is used for data preprocessing, and the expression is:

[0133] Q(z)=exp(-|T raw (z)-T avg (z)| / T dev (z))

[0134] Where Q(z) is the data quality coefficient of region z, T raw (z) is the original sampling temperature of area z, T avg (z) is the average temperature of the most recent N (N=20) valid samples in area z, T dev (z) is the allowable temperature deviation of zone z (7°C in the cold end zone, 5°C in the middle zone, and 3°C in the hot end zone).

[0135] Specifically, in the above embodiment, taking the cold end 9 area of ​​the casting disk as an example, it is obtained that: T raw (1) = 725°C, T avg (1) = 722 °C, T dev (1) = 7°C, and the final calculation yields Q(1) = exp(-|725-722| / 7) = 0.65.

[0136] S123. Perform regional temperature weighting calculation based on the preprocessed temperature data using a temperature weight coefficient to obtain a weighted temperature data set.

[0137] Specifically, the temperature data is weighted based on the weight coefficient, and the expression is:

[0138] T w (z) = T raw (z)×W(z)×Q(z)

[0139] Where, T w (z) is the weighted temperature of region z, T raw (z) is the original sampling temperature of area z, W(z) is the temperature weight coefficient of area z. In this embodiment, it is determined by the W(i) value of the silicon carbon rod in the area. The cold end 9 area of ​​the casting disk adopts the W(i) value of the 40 mm silicon carbon rod in the area, that is, W(cold end) = 4.94, the middle area of ​​the casting disk body 10 adopts the W(i) value of the 28 mm silicon carbon rod in the area, that is, W(middle) = 2.42, and the hot end 6 area of ​​the casting disk adopts the W(i) value of the 18 mm silicon carbon rod in the area, that is, W(hot end) = 1.00. Q(z) is the data quality coefficient of area z.

[0140] Specifically, in the above embodiment, the following is calculated:

[0141] ① Casting plate cold end 9 area, T raw (cold end) = 725 ° C, W (cold end) = 4.94, Q (cold end) = 0.65, and the final weighted temperature T is calculated. w (cold end) = 725 × 4.94 × 0.65 = 2328;

[0142] ② The middle area of ​​the casting plate body 10, T raw(middle) = 720 ° C, W (middle) = 2.42, Q (middle) = 0.72, and the weighted temperature T is finally calculated. w (middle) = 720 × 2.42 × 0.72 = 1253;

[0143] ③ Casting plate hot end 6 area, T raw (hot end) = 718 °C, W (hot end) = 1.00, Q (hot end) = 0.80, and the final weighted temperature is: T w (hot end) = 718 × 1.00 × 0.80 = 574.

[0144] Specifically, the complete weighted temperature data set is:

[0145] Cold end 9 area of ​​the casting plate: 2328 (unnormalized temperature value);

[0146] The middle area of ​​the casting plate body 10: 1253 (unnormalized temperature value);

[0147] Casting disk hot end 6 area: 574 (unnormalized temperature value).

[0148] In one embodiment, based on the weighted temperature data set, the temperature characteristic value of each region is obtained, and the zone temperature deviation values ​​of the cold end 9 of the casting disk, the middle part of the casting disk body 10 and the hot end 6 of the casting disk are obtained through temperature compensation correction and regional correlation analysis, including the following steps:

[0149] S131, establishing a real-time temperature feature sequence for each region according to the weighted temperature data set, and obtaining a temperature feature value for each region using a sliding window method, wherein the temperature feature value includes an average feature temperature and a temperature fluctuation range;

[0150] Specifically, based on the weighted temperature data set, firstly, the weighted temperature data of the most recent 20 times in each area are arranged in chronological order, and the real-time temperature characteristic sequence of the 9 areas at the cold end of the casting disk is obtained as follows:

[0151] [2328,2330,2327,2329,2331,2328,2332,2329,2330,2328,2331,2327,2329,2330,2328,2331,2329,2332,2328,2330];

[0152] The real-time temperature characteristic sequence of the middle area of ​​the casting plate body is:

[0153] [1253,1255,1252,1254,1253,1255,1251,1254,1253,1255,1252,1254,1253,1255,1252,1254,1253,1255,1252,1254];

[0154] The real-time temperature characteristic sequence of the hot end 6 area of ​​the casting disk is:

[0155] [574,576,573,575,574,576,573,575,574,576,573,575,574,576,573,575,574,576,573,575].

[0156] Specifically, the temperature characteristic value of each region is calculated by the sliding window method (window size N=10), and the expression of the temperature characteristic value is:

[0157] T char (z)=[∑T w (z,k)] / N, k∈[t-N+1,t]

[0158] V char (z) = max(T w (z,k))-min(T w (z,k)), k∈[t-N+1,t]

[0159] Where, T char (z) is the average characteristic temperature of region z, V char (z) is the temperature fluctuation range of region z, T w (z,k) is the weighted temperature of region z at time k, t is the current time, and N is the sliding window size.

[0160] Specifically, in the above embodiment, the following is calculated:

[0161] Casting plate cold end 9 area T char (cold end) = 2329.6, V char (cold end) = 5; middle area of ​​the casting plate body T char (middle) = 1253.4, V char (middle) = 4; casting disk hot end 6 area T char (hot end) = 574.5, V char (hot end) = 3.

[0162] S132, based on the temperature characteristic value of each area, using the preset temperature threshold of each area to calculate the initial temperature deviation data, and perform temperature compensation correction;

[0163] Specifically, the initial temperature deviation is calculated based on the temperature characteristic value and dynamic compensation is performed. The expression is:

[0164] ΔT raw (z) = T char (z) / W(z)-T set (z)

[0165] ΔT mod (z) = ΔT raw (z)×[1+θ×V char (z) / V max ]

[0166] In the formula, ΔT raw (z) is the original temperature deviation of region z, ΔT mod (z) is the temperature deviation data after temperature compensation correction in area z, T set (z) is the target temperature threshold of area z (cold end 725°C, middle 720°C, hot end 718°C), θ is the fluctuation compensation coefficient (the value is 0.15 in this embodiment), V max is the maximum allowable temperature fluctuation range (10° C. in this embodiment), and W(z) is the temperature weight coefficient of region z.

[0167] Specifically, in the above embodiment, the following is calculated:

[0168] Casting plate cold end 9 area ΔT raw (cold end) = 2329.6 / 4.94-725 = -253.4°C, ΔT mod (cold end) = -253.4 × [1 + 0.15 × 5 / 10] = -272.4 ° C;

[0169] The middle area of ​​the casting plate body ΔT raw (middle) = 1253.4 / 2.42-720 = -202.1°C, ΔT mod (middle) = -202.1 × [1 + 0.15 × 4 / 10] = -214.2 ° C;

[0170] Casting disk hot end 6 area ΔT raw (hot end) = 574.5 / 1.00-718 = -143.5°C, ΔT mod (hot end) = -143.5 × [1 + 0.15 × 3 / 10] = -150.0 ° C.

[0171] S133. According to the corrected temperature deviation data, the zone temperature deviation values ​​of the cold end 9 of the casting disk, the middle of the casting disk body 10 and the hot end 6 of the casting disk are obtained through regional correlation analysis.

[0172] Specifically, considering the correlation between regions, the final partition temperature deviation value is calculated, and the expression of regional correlation analysis is:

[0173] ΔT final (z) = ΔT mod (z)+λ×[ΔT mod (z-1)+ΔT mod (z+1)] / 2

[0174] In the formula, ΔT final (z) is the partition temperature deviation value of area z, λ is the area correlation coefficient (in this embodiment, the value is 0.2), z-1 and z+1 respectively represent the area on one side and the area on the other side adjacent to area z. If the area does not exist, the corresponding temperature deviation data of area z after temperature compensation correction is 0.

[0175] Specifically, in the above embodiment, the following is calculated:

[0176] The cold end 9 area of ​​the casting plate ΔTfinal (cold end) = -272.4 + 0.2 × (-214.2 + 0) / 2 = -293.8 ° C;

[0177] The middle area of ​​the casting disk body ΔTfinal (middle) = -214.2 + 0.2 × (-272.4-150.0) / 2 = -256.5 ° C;

[0178] The casting disk hot end 6 area ΔTfinal(hot end) = -150.0 + 0.2 × (0-214.2) / 2 = -171.4 °C.

[0179] Specifically, these final partition temperature deviation values ​​will be used as input parameters for subsequent PWM control signal duty cycle adjustment.

[0180] In one embodiment, based on the silicon carbon rod resistance calculation model, the inherent resistance value of the silicon carbon rod 1 in each region is calculated, and the power density of each region is analyzed in combination with the partition temperature deviation value, and the overall power supply duty cycle is calculated using the regional power density. Generating the optimal PWM control signal includes the following steps:

[0181] S21, according to the diameter distribution data of the silicon carbon rod 1, the inherent resistance value of the silicon carbon rod 1 in each area is obtained by using the silicon carbon rod resistance calculation model;

[0182] The expression of the silicon carbon rod resistance calculation model is:

[0183] R(d i ,T)=ρ(T)×L / [π×(d i / 2) 2 ]

[0184] In the formula, R(d i,T) is the resistance value of the i-th silicon carbon rod at temperature T, ρ(T) is the resistivity at temperature T, L is the effective length of the silicon carbon rod (400 mm in this embodiment), d i is the diameter of the i-th silicon carbon rod;

[0185] Specifically, the resistivity at temperature T is ρ(T) = ρ 0 ×[1+A×(TT 0 )]; where ρ 0 The resistivity of the silicon carbon rod at 20°C (in this embodiment, the value is 45×10 -6 Ω·m), A is the temperature coefficient (in this embodiment, the value is 8×10 -3 / ℃).

[0186] S22, based on the inherent resistance value of the silicon carbon rod 1 in each region, analyzing the power density of each silicon carbon rod 1, and combining the partition temperature deviation value to analyze the regional power density of each region;

[0187] The power density of each silicon carbon rod is expressed as:

[0188] P(d i )=U 2 / [R(d i ,T)×π×(d i / 2) 2 ]

[0189] In the formula, P(d i ) is the power density of the i-th silicon carbon rod, and U is the supply voltage (380 V in this embodiment);

[0190] The expression of regional power density is:

[0191] P(z)=[∑P(d i )]×[1+B×ΔT final (z) / ΔT max ]

[0192] Where P(z) is the regional power density of region z, ∑P(d i ) is the sum of the power densities of all silicon carbon rods in region z, B is the temperature compensation coefficient (the value is 0.25 in this embodiment), ΔT final (z) is the zone temperature deviation value of zone z obtained in step S133, ΔT max is the maximum allowable temperature deviation (300°C in this embodiment).

[0193] Specifically, in the above embodiment, the power density of a single silicon carbon rod 1 is calculated according to the inherent resistance value of the silicon carbon rod 1. In this embodiment, a total of 10 silicon carbon rods are arranged on the casting plate from the cold end to the hot end, which are divided into three areas:

[0194] ① The cold end 9 area of ​​the casting plate contains 4 silicon carbon rods (with diameters of 40mm, 38mm, 35mm, and 32mm respectively). The power density of these 4 silicon carbon rods is calculated to be 26.2W / cm 2 、23.8W / cm 2 、22.4W / cm 2 、21.0W / cm 2 The power density of the four silicon carbon rods is summed up to get the sum of the power density of all silicon carbon rods in the cold end area ∑P(d i ) is 93.4W / cm 2 ;

[0195] ② The middle area of ​​the casting plate body 10 contains three silicon carbon rods (with diameters of 30 mm, 28 mm, and 25 mm, respectively). The power density of these three silicon carbon rods is 20.5 W / cm 2 、19.2W / cm 2 、18.7W / cm 2 , the sum of the power densities of all silicon carbon rods in the middle area is obtained by adding them up ∑P(d i ) is 58.4W / cm 2 ;

[0196] ③ The hot end 6 area of ​​the casting disk contains three silicon carbon rods (diameters are 22mm, 20mm, and 18mm respectively). The power density of these three silicon carbon rods is 17.5W / cm 2 、16.1W / cm 2 、15.2W / cm 2 , the sum of the power densities of all silicon carbon rods in the hot end area is obtained by adding up ∑P(d i ) is 48.8W / cm 2 .

[0197] Specifically, combined with the partition temperature deviation value (ΔT final (cold end) = -293.8°C, ΔT final (middle) = -256.5°C, ΔT final (hot end) = -171.4°C), substitute into the regional power density expression, and get the final regional power density of each region:

[0198] ① In the cold end 9 area of ​​the casting plate, P(z)=93.4×[1+0.25×(-293.8 / 300)]=70.4W / cm 2 ;

[0199] ② In the middle area of ​​the casting plate body 10, P(z)=58.4×[1+0.25×(-256.5 / 300)]=45.7W / cm 2 ;

[0200] ③ Casting plate hot end 6 area, P(z) = 48.8 × [1 + 0.25 × (-171.4 / 300)] = 42.4 W / cm 2 .

[0201] S23, calculating the overall power supply duty cycle of the casting disk temperature gradient intelligent control device for aluminum rod continuous casting according to the regional power density of each area, and outputting the optimal PWM control signal through the pulse width regulator 4.

[0202] The expression of the overall power supply duty cycle is:

[0203] D=K×P total / P rated

[0204] Where D is the overall power supply duty cycle, K is the proportionality coefficient (the value is 0.95 in this embodiment), P total The total power density (158.5 W / cm2) of the cold end area of ​​the casting disk, the middle area of ​​the casting disk body, and the hot end area of ​​the casting disk obtained in step S22 2 ), P rated is the rated power density (180 W / cm 2 ); In the above embodiment, the final calculation results in D=0.95×158.5 / 180=0.84.

[0205] In one embodiment, the overall power supply power of the silicon carbon rod 1 is adjusted in real time through the pulse width regulator 4 according to the overall power supply duty cycle.

[0206] It should be noted that the pulse width regulator 4 is a power electronic device that converts a DC voltage into an adjustable duty cycle pulse signal, and its basic working principle is to adjust the average power supply voltage of the load by changing the on-off time ratio (duty cycle) of the output pulse. In the present invention, the pulse width regulator 4 receives a control signal from the PID control element 5, modulates the 380V DC voltage into a pulse signal of a specific frequency (usually 50-200Hz), and realizes power supply control of the silicon carbon rod 1 by adjusting the duty cycle (usually in the range of 0-95%). This is a prior art and will not be described in detail here.

[0207] Specifically, the overall power supply duty cycle D calculated in step S23 is used as the modulation coefficient of the PWM waveform. In this embodiment, the basic parameters of the PWM waveform are set as follows: PWM switching frequency f = 100 Hz, PWM signal period T = 1 / f = 10 ms, power-on time T on =D×T, power-off time Toff=(1-D)×T, peak voltage V peak =380V; when D = 0.84, the power-on time T is obtainedon 8.4ms, power-off time T off The pulse width regulator 4 receives these timing parameters, and in each cycle, outputs a voltage of 380V for 8.4ms and a voltage of 0V for 1.6ms, and cyclically executes the above-mentioned on-off process, thereby controlling the silicon carbon rod 1 to heat the casting disk in real time.

[0208] In order to facilitate understanding of the above technical solution of the present invention, a certain aluminum alloy round ingot production line is taken as an example for specific description as follows:

[0209] In the actual production process, the casting disk temperature gradient intelligent control device for continuous casting of aluminum rods of the present invention is installed on an aluminum alloy semi-continuous casting machine with a diameter of 800mm, the casting disk body 10 is lined with high-aluminum refractory material, the width of the aluminum liquid inlet flow channel 7 and the aluminum discharge flow channel 8 are both 100mm, the working temperature range is 680-750℃, and 10 silicon carbon rods 1 are evenly installed on the top of the inner side of the casting disk body 10 along the circumferential direction. The diameters of the silicon carbon rods 1 are 40mm, 38mm, 35mm, 32mm, 30mm, 28mm, 25mm, 22mm, 20mm, and 18mm from the cold end 9 of the casting disk to the hot end 6 of the casting disk, respectively, and the rated working voltage is 380V.

[0210] During the casting process, aluminum liquid with a temperature of 720±5°C enters the casting plate body 10 from the aluminum liquid inlet flow channel 7, passes through the casting plate hot end 6 area, flows along the inner wall of the casting plate body 10 to the casting plate cold end 9 area, and finally is discharged from the aluminum discharge flow channel 8. During the whole process, the temperature of each area of ​​the casting plate is monitored in real time by the temperature measuring thermocouple 3, the multi-channel temperature acquisition module 14 collects temperature data every 5 seconds, the PID control element 5 calculates the control parameters according to the temperature data, and the pulse width regulator 4 adjusts the power supply of the silicon carbon rod 1 in real time after receiving the control signal.

[0211] It was measured that, through the casting plate temperature gradient intelligent control device for aluminum rod continuous casting of the present invention, the temperature of the hot end 6 area of ​​the casting plate was stabilized at 718±3°C, the temperature of the middle area of ​​the casting plate body 10 was stabilized at 720±5°C, and the temperature of the cold end 9 area of ​​the casting plate was stabilized at 725±7°C. Compared with the traditional natural gas heating method, the present invention not only realizes the dynamic balanced control of the whole temperature field of the casting plate, but also extends the average service life of the refractory material from the original 3 months to more than 5 months, and reduces the energy consumption in the casting process by about 15%.

[0212] In summary, with the help of the above technical scheme of the present invention, by installing silicon carbon rods with diameters from large to small at the bottom of the casting disk, and using silicon felt wool for heat insulation treatment, combined with real-time temperature monitoring and PWM control system, the precise control of the temperature field of the entire casting disk is achieved; the present invention not only overcomes the technical defects of local overheating and long preheating time in traditional natural gas heating and electric heating fan heating, but also significantly improves the service life of the refractory material of the casting disk and reduces the energy consumption of the production process. The present invention effectively solves the technical problem that the aluminum water temperature at the cold end is 5-10°C lower than that at the hot end in the traditional casting process by configuring silicon carbon rods with larger diameters in the cold end area of ​​the casting disk and silicon carbon rods with smaller diameters in the hot end area; this gradient heating method makes the aluminum water temperature in each area of ​​the casting disk tend to be consistent, significantly improves the uniformity of the metallurgical quality of the cast rod, and effectively avoids the inconsistency of compound size and dendrite spacing in the metallurgy of the cast rod, providing a reliable technical guarantee for improving the overall quality of aluminum alloy cast rods.

[0213] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars, characterized in that: The casting plate temperature gradient intelligent control device for aluminum rod continuous casting comprises a casting plate body, one end of the casting plate body is provided with an aluminum water inlet flow channel, the other end of the casting plate body is provided with an aluminum discharge flow channel, one end of the inner side of the casting plate body is provided with a casting plate hot end matched with the aluminum water inlet flow channel, the other end of the inner side of the casting plate body is provided with a casting plate cold end matched with the aluminum discharge flow channel, and the inner bottom end of the casting plate body is provided with a plurality of linearly arranged silicon carbon rods; The diameter of the silicon carbon rod gradually decreases from the cold end of the casting disk to the hot end of the casting disk, the top and bottom of the silicon carbon rod are both provided with silicon felt wool, and both ends of the silicon carbon rod are provided with electric wire copper sheets, the electric wire copper sheet at one end of the silicon carbon rod is connected to the pulse width regulator, and the electric wire copper sheet at the other end of the silicon carbon rod is connected to the negative electrode of the power supply; A plurality of temperature measuring thermocouples are arranged on one side of the casting disk body, a multi-channel temperature acquisition module is arranged at one end of the temperature measuring thermocouple, a PID control element is arranged at one end of the multi-channel temperature acquisition module, one end of the PID control element is connected to the pulse width regulator, and the other end of the PID control element is connected to the positive pole of the power supply.

2. The intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars according to claim 1, characterized in that: The casting plate temperature gradient intelligent control device for aluminum rod continuous casting comprises: S1. Using the temperature field partition control algorithm, the target temperature values ​​and temperature weight coefficients at different positions of the casting disk are obtained, a weighted temperature data set is established, and the partition temperature deviation values ​​of the cold end of the casting disk, the middle of the casting disk body, and the hot end of the casting disk are obtained through temperature compensation correction and regional correlation analysis; S2. Based on the silicon carbon rod resistance calculation model, the inherent resistance value of the silicon carbon rod in each area is calculated, and the power density of each area is analyzed in combination with the partition temperature deviation value, and the overall power supply duty cycle is calculated using the regional power density; S3. According to the overall power supply duty cycle, the overall power supply power of the silicon carbon rod is adjusted in real time through a pulse width regulator.

3. The intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars according to claim 2, characterized in that: The method of using the temperature field partition control algorithm to obtain the target temperature values ​​and temperature weight coefficients at different positions of the casting disk, establish a weighted temperature data set, and obtain the partition temperature deviation values ​​of the cold end of the casting disk, the middle of the casting disk body, and the hot end of the casting disk through temperature compensation correction and regional correlation analysis includes the following steps: S11. Based on the casting process parameter requirements, the target temperature values ​​at different positions of the casting plate are obtained through the temperature field partition control algorithm, and the temperature weight coefficient is solved in combination with the diameter of the silicon carbon rod to establish a regional temperature dynamic balance model; S12, according to the different sampling periods of the cold end of the casting plate, the middle of the casting plate body and the hot end of the casting plate, the multi-channel temperature acquisition module is used to collect data from each temperature measuring thermocouple, and a weighted temperature data set is established in combination with the temperature weight coefficient; S13. Based on the weighted temperature data set, the temperature characteristic value of each area is obtained, and through temperature compensation correction and regional correlation analysis, the zone temperature deviation values ​​of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk are obtained.

4. The intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars according to claim 3 is characterized in that: The method of obtaining target temperature values ​​at different positions of the casting plate based on the casting process parameter requirements through the temperature field partition control algorithm, solving the temperature weight coefficient in combination with the diameter of the silicon carbon rod, and establishing a regional temperature dynamic balance model includes the following steps: S111, according to the casting process parameter requirements, using the temperature field partition control algorithm to solve the target temperature values ​​at different positions of the casting plate; The expression of the temperature field partition control algorithm is: T(x)=T0+k×(xL / 2) Where, T(x) is the target temperature, T0 is the overall target temperature of the casting plate, x is the horizontal distance from the measuring point to the inner wall of the hot end side of the casting plate body, L is the internal horizontal length of the casting plate body, and k is the temperature gradient coefficient; S112, based on the target temperature values ​​at different positions of the casting disk and in combination with the diameter distribution of the silicon carbon rods, the power compensation coefficient of each area of ​​the casting disk is calculated, and the target temperature threshold is determined through regional temperature mapping; The expression of the power compensation coefficient of each area of ​​the casting plate is: P(d)=(d / d min ) 2 Where P(d) is the power compensation coefficient of the silicon carbon rod with a diameter of d, min It is the minimum diameter reference value of silicon carbon rod; S113. According to the power compensation coefficient of each area, the temperature weight coefficient is obtained through weighted calculation, and the target temperature values ​​and temperature weight coefficients at different positions of the casting plate are used to construct a regional temperature dynamic balance model.

5. The intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars according to claim 4 is characterized in that: The expression of the temperature weight coefficient is: W(i)=P(d) i ×[1+α×(L-x i ) / L] Where W(i) is the temperature weight coefficient of the i-th silicon carbon rod, P(d) i is the power compensation coefficient of the i-th silicon carbon rod, α is the position compensation factor, x i is the horizontal distance from the center of the i-th silicon carbon rod to the inner wall of the hot end side of the casting plate body, and L is the horizontal length of the inner side of the casting plate body; The expression of the regional temperature dynamic equilibrium model is: T bla (i)=T(x) i ×W(i) Where, T bla (i) is the equilibrium temperature of the i-th silicon carbon rod position, T(x) i is the target temperature of the i-th silicon carbon rod.

6. The intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars according to claim 3, characterized in that: The method comprises the following steps: collecting data from each temperature measuring thermocouple using a multi-channel temperature acquisition module according to the different sampling periods of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk, and establishing a weighted temperature data set in combination with a temperature weight coefficient: S121, based on the cold and hot end temperature difference compensation requirement, using the cold and hot end area sampling algorithm, obtain the difference sampling period of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk; The expression of the cold and hot end area sampling algorithm is: Ts(z)=T0s×[1+η×σ(z) / σ max ] Where Ts(z) is the difference sampling period of region z, T0s is the reference sampling period, η is the fluctuation response coefficient, σ(z) is the temperature standard deviation within the preset time window of region z, and σ max is the maximum allowed temperature standard deviation; S122, using the difference sampling period, collecting data from each temperature measuring thermocouple through a multi-channel temperature acquisition module to obtain an original temperature data sequence, and performing data preprocessing; S123, performing regional temperature weighting operation according to the preprocessed temperature data by using the temperature weight coefficient to obtain a weighted temperature data set; The expression of the regional temperature weighted operation is: T w (z)=T raw (z)×W(z)×Q(z) Where, T w (z) is the weighted temperature of region z, T raw (z) is the original sampling temperature of region z, W(z) is the temperature weight coefficient of region z, and Q(z) is the data quality coefficient of region z.

7. The intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars according to claim 3 is characterized in that: The method of obtaining the temperature characteristic value of each region based on the weighted temperature data set and obtaining the zone temperature deviation value of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk through temperature compensation correction and regional correlation analysis includes the following steps: S131, establishing a real-time temperature feature sequence for each region according to the weighted temperature data set, and obtaining a temperature feature value for each region using a sliding window method, wherein the temperature feature value includes an average feature temperature and a temperature fluctuation range; S132, based on the temperature characteristic value of each area, using the preset temperature threshold of each area to calculate the initial temperature deviation data, and perform temperature compensation correction; S133. According to the corrected temperature deviation data, the zone temperature deviation values ​​of the cold end of the casting disk, the middle of the casting disk body and the hot end of the casting disk are obtained through regional correlation analysis.

8. The intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars according to claim 7, characterized in that: The expression of the temperature compensation correction is: ΔT raw (z)=T char (z) / W(z)-T set (z) ΔT mod (z)=ΔT raw (z)×[1+θ×V char (z) / V max ] In the formula, ΔT raw (z) is the original temperature deviation of region z, ΔT mod (z) is the temperature deviation data after temperature compensation correction in area z, T char (z) is the average characteristic temperature of region z, T set (z) is the target temperature threshold of area z, θ is the fluctuation compensation coefficient, V max is the maximum allowable temperature fluctuation range, W(z) is the temperature weight coefficient of region z; The expression of the regional correlation analysis is: ΔT final (z)=ΔT mod (z)+λ×[ΔT mod (z-1)+ΔT mod (z+1)] / 2 In the formula, ΔT final (z) is the partition temperature deviation value of area z, λ is the regional correlation coefficient, and z-1 and z+1 represent the area on one side and the area on the other side adjacent to area z, respectively.

9. The intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars according to claim 2, characterized in that: The method of calculating the inherent resistance value of the silicon carbon rods in each region based on the silicon carbon rod resistance calculation model, analyzing the power density of each region in combination with the partition temperature deviation value, and calculating the overall power supply duty cycle using the regional power density includes the following steps: S21, according to the diameter distribution data of the silicon carbon rod, the inherent resistance value of the silicon carbon rod in each area is obtained by using the silicon carbon rod resistance calculation model; S22. Analyze the power density of each silicon carbon rod based on the inherent resistance value of the silicon carbon rods in each region, and analyze the regional power density of each region in combination with the zone temperature deviation value; S23. Calculate the overall power supply duty cycle of the casting disk temperature gradient intelligent control device for continuous casting of aluminum bars according to the regional power density of each region.

10. The intelligent control device for temperature gradient of a casting plate for continuous casting of aluminum bars according to claim 9, characterized in that: The expression of the silicon carbon rod resistance calculation model is: R(d i ,T)=ρ(T)×L / [π×(d i / 2) 2 ] In the formula, R(d i ,T) is the resistance value of the i-th silicon carbon rod at temperature T, ρ(T) is the resistivity at temperature T, L is the effective length of the silicon carbon rod, d i is the diameter of the i-th silicon carbon rod; The power density of each silicon carbon rod is expressed as: P(d i )=U2 / [R(d i ,T)×π×(d i / 2)2] In the formula, P(d i ) is the power density of the i-th silicon carbon rod, and U is the supply voltage; The expression of the regional power density is: P(z)=[∑P(d i )]×[1+B×ΔT final (z) / ΔT max ] Where P(z) is the regional power density of region z, ∑P(d i ) is the sum of the power densities of all silicon carbon rods in area z, B is the temperature compensation coefficient, ΔT final (z) is the zone temperature deviation value of area z, ΔT max is the maximum allowable temperature deviation.

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