A control system for rapid-setting sheet melting equipment

Abstract

The present invention provides a control system for rapid-setting sheet melting equipment, belonging to the field of industrial control technology. The control module includes a sensor group and a rapid-setting sheet melting control module. The control module performs the following steps: first, collecting temperature, vacuum, water pressure, water temperature, and copper roller speed data from the sensor group, checking the furnace door closing status and remote control permission status; then, starting the melting process according to preset heating power curve, pouring power curve, pouring tilt curve, and copper roller speed parameters, and starting melting after the vacuum level reaches the standard; the system automatically determines the time when the molten steel is fully melted and issues a temperature measurement prompt, adjusting the power to 120 kilowatts according to the instruction to measure the temperature; after reaching the target temperature, reducing the power to 50 kilowatts; after the water temperature reaches the standard, controlling the crucible to flip to a preset angle; finally, controlling the pouring process according to the pouring power curve, monitoring the copper roller speed in real time, and promptly issuing an alarm when the deviation exceeds 5%. This solves the technical problem of unstable product quality in the prior art.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial control, and in particular relates to a control system for rapid-setting sheet melting equipment. Background Art

[0002] As an important metal material, quick-setting sheet has broad application prospects in aerospace, new energy vehicles, high-end equipment manufacturing and other fields. In the preparation process of quick-setting sheet, the smelting control link directly affects the quality and performance of the product. At present, the quick-setting sheet smelting equipment mainly adopts the following control methods in industrial production:

[0003] First, the traditional manual experience-based control model still dominates in many companies. Operators rely on their experience to determine key indicators such as molten steel temperature, vacuum level, and water cooling system parameters, and manually adjust the melting power, tilt angle, and copper roller speed. This control method has the following limitations: First, human judgment is subjective, making it difficult to ensure precise control of process parameters; second, the uneven skill levels of operators lead to significant fluctuations in product quality; and third, manual operation is slow to respond, making it difficult to promptly address process anomalies.

[0004] Secondly, some companies use simple PID control systems. While these systems achieve basic automatic control functions, their control strategies are relatively simple and cannot adapt to complex process requirements. Specifically, they suffer from fixed control parameters and lack adaptability; independent control loops lack system coordination; and an inability to establish a correlation model between process parameters and product quality.

[0005] As downstream application fields have increasingly higher requirements for the quality of quick-setting sheets, existing control technologies have been unable to meet the needs of industrial development. Due to large fluctuations in process parameters and difficulty in precise adjustment, product quality has become unstable. Summary of the Invention

[0006] In view of this, the present invention provides a control system for rapid-setting sheet smelting equipment, which can solve the technical problem of unstable product quality caused by large fluctuations in process parameters and difficulty in precise adjustment in the prior art.

[0007] The present invention is achieved in that:

[0008] The present invention provides a control system for quick-setting sheet smelting equipment, comprising a sensor group and a quick-setting sheet smelting control module; the sensor group comprises a temperature sensor arranged in a smelting furnace, a vacuum degree sensor arranged in a vacuum system, a water pressure sensor and a water temperature sensor arranged in a water cooling system, and a speed sensor arranged on a copper roller; the quick-setting sheet smelting control module is used to control the quick-setting sheet smelting equipment to perform automatic smelting operation, and the quick-setting sheet smelting control module is used to perform the following steps:

[0009] S10, collecting data signals collected by the sensor group, including temperature data in the smelting furnace, vacuum degree data of the vacuum system, water pressure data and water temperature data of the water cooling system, and copper roller speed data;

[0010] S20, performing furnace door status detection according to preset process parameters to confirm that the furnace door is in a closed state and the remote control switch is in an enabled state;

[0011] S30, starting the smelting program according to the preset heating power curve, pouring power curve, pouring tilting curve and copper roller speed parameters;

[0012] S40, controlling the vacuum system to perform a vacuum operation, and automatically starting smelting after the vacuum degree sensor detects that the vacuum degree reaches a preset vacuum degree value;

[0013] S50, judging the time point when the molten steel is fully melted according to the temperature data detected by the temperature sensor, and sending a temperature measurement prompt signal when the preset temperature is reached;

[0014] S60: After receiving the temperature measurement instruction, the power is adjusted to 120 kilowatts, the temperature measuring rod is controlled to descend to a preset position to measure the temperature, and the measured temperature data is recorded;

[0015] S70, when the temperature data reaches the target temperature, the temperature is lowered and the power is adjusted to 50 kilowatts for cooling;

[0016] S80, controlling the water cooling system to start, and after the water temperature sensor detects that the water temperature reaches a preset water temperature value, controlling the tilting mechanism to flip the crucible to a preset angle;

[0017] S90: During the pouring process, the copper roller speed is controlled according to the preset pouring power curve, and the speed is monitored in real time and compared with the preset speed to ensure the consistency of the thickness of the quick-setting sheet. When the deviation between the actual speed and the preset speed exceeds 5%, an alarm signal is issued.

[0018] The target temperature is specifically 1600 degrees Celsius; the preset position is specifically 10 mm from the temperature measuring rod to the surface of the molten steel. The preset vacuum value is specifically Pa.

[0019] On the basis of the above technical solution, the control system for the rapid-setting sheet smelting equipment of the present invention can also be improved as follows:

[0020] The preset process parameters specifically include a melting temperature range, a vacuum range, a water pressure range, a water temperature range, and a copper roller speed range.

[0021] Furthermore, the steps of establishing the preset heating power curve specifically include:

[0022] S101, collecting heating power data from historical smelting data;

[0023] S102, establishing a time-power function relationship based on power data of different time periods;

[0024] S103: Generate a heating power curve according to the time-power function relationship.

[0025] Furthermore, the steps of establishing the preset pouring power curve specifically include:

[0026] S201, collecting power data during historical pouring processes;

[0027] S202, establishing a time-power function relationship according to the power variation law in the pouring stage;

[0028] S203: Generate a pouring power curve according to the time-power function relationship.

[0029] Furthermore, the steps of establishing the preset pouring tilting curve specifically include:

[0030] S301, collecting tilt angle data during historical pouring processes;

[0031] S302, establishing a time-angle function relationship according to the tilting angle variation rule during the pouring stage;

[0032] S303: Generate a pouring tilt curve according to the time-angle function relationship.

[0033] Furthermore, the steps of determining the preset copper roller speed parameters specifically include:

[0034] S401, determining a reference rotation speed according to a target thickness of the quick-setting sheet;

[0035] S402, correcting the reference speed according to the molten steel temperature;

[0036] S403. Determine the copper roller speed parameter according to the corrected value.

[0037] Furthermore, the criterion for judging the time point when the molten steel is fully melted is: the temperature in the melting furnace reaches 1500 degrees Celsius and remains stable for 5 minutes.

[0038] Furthermore, the copper roller speed sensor monitors the copper roller speed for: real-time monitoring of the copper roller speed and comparison with the preset speed to ensure the consistency of the thickness of the quick-setting sheet, and issues an alarm signal when the actual speed deviates from the preset speed by more than 5%.

[0039] Furthermore, the preset water temperature value is obtained by solving an optimal water temperature equation group; the optimal water temperature equation group includes an equation for the relationship between water temperature and quick-setting sheet quality, an equation for the relationship between water temperature and cooling efficiency, and a comprehensive optimization objective function for water temperature;

[0040] The water temperature and quick-setting tablet quality relationship equation is used to characterize the influence of water temperature on the quality of quick-setting tablets. The power function term reflects the temperature reference effect, and the exponential function term describes the optimal temperature point effect, thereby achieving a quantitative correlation between water temperature and product quality.

[0041] The water temperature and cooling efficiency relationship equation is used to describe the mechanism by which water temperature affects the efficiency of the cooling system. Based on the principles of thermodynamics, a linear relationship model between water temperature and cooling efficiency is established by comprehensively considering factors such as temperature difference, flow rate, density, and specific heat capacity.

[0042] The water temperature comprehensive optimization objective function is used to weigh the influence of three aspects: the quality of the quick-setting sheet, the cooling efficiency and the operating cost. Multi-objective optimization is achieved through weighted summation to determine the optimal water temperature preset value.

[0043] Furthermore, the preset value of the tilting angle is obtained by solving an optimal tilting angle equation group, wherein the optimal tilting angle equation group includes an equation for the relationship between the tilting angle and the pouring flow rate, an equation for the relationship between the tilting angle and the pouring stability, and a comprehensive optimization objective function of the tilting angle;

[0044] The equation for the relationship between the tilting angle and the pouring flow rate is used to establish a quantitative relationship between the tilting angle and the pouring flow rate. Based on the principles of fluid mechanics, the equation takes into account the effects of factors such as gravitational potential energy, pressure potential energy, and outlet area on the flow rate, thereby achieving precise control of the pouring flow rate.

[0045] The relationship equation between the tilting angle and the pouring stability is used to evaluate the dynamic characteristics of the pouring process. The pouring stability is characterized by parameters such as angular velocity, angular acceleration and Reynolds number, providing a basis for process optimization.

[0046] The tilting angle comprehensive optimization objective function is used to balance the influence of three aspects: pouring flow, pouring stability and energy consumption. The importance of each factor is adjusted by a weighted coefficient to determine the optimal tilting angle preset value.

[0047] The water temperature optimization empirical equations are specifically expressed as follows:

[0048] The relationship equation between water temperature and quick-setting sheet quality:

[0049] ;

[0050] Where, It is the quality scoring index of quick-setting tablets, with a value range of 0-100; is the water temperature, unit is ℃; is the reference water temperature, which is 15℃; is the theoretical optimal water temperature, unit: °C; is the coefficient to be determined; is the temperature impact index; is the temperature sensitivity coefficient; is the random error term. The first term in the formula The power function is used to reflect the basic influence of water temperature deviation from the reference temperature on the quality. It reflects the nonlinear characteristics of the impact; the second The Gaussian function form is used to describe the quality change law near the optimal temperature point, reflecting the physical essence of the existence of the optimal temperature point.

[0051] Parameter acquisition method:

[0052] 1) The data is collected in real time by PT100 temperature sensor with a sampling frequency of 10Hz;

[0053] 2) The value is determined by statistical analysis of historical data and is 15°C;

[0054] 3) Obtained by fitting historical data using the least squares method;

[0055] 4) Determined by log-linear regression method;

[0056] 5) Obtained through iterative solution of optimization algorithm;

[0057] 6) Determined by orthogonal test method.

[0058] The relationship equation between water temperature and cooling efficiency:

[0059] ;

[0060] Where, For cooling efficiency; is the cooling water temperature rise, unit is ℃; is the cooling water flow rate, in m / s; is the water density, unit is kg / m³; is the specific heat capacity of water, unit is J / (kg·℃); is the coefficient to be determined; is a random error term. The linear superposition form is used in the formula, based on the thermodynamic heat transfer theory, and the temperature difference ( ), flow rate( ),density( ) and specific heat capacity ( ) on cooling efficiency.

[0061] Parameter acquisition method:

[0062] 1) Obtained through measurement of inlet and outlet water temperature sensors;

[0063] 2) Calculated by flow meter;

[0064] 3) Obtained by looking up the table;

[0065] 4) Obtained through multiple linear regression.

[0066] Water temperature comprehensive optimization objective function:

[0067] ;

[0068] Where, To optimize the objective function value; is the cooling cost function; is the weight coefficient and satisfies The weighted summation form is adopted in the formula to achieve the quality ( ),efficiency( ) and cost ( ) for multi-objective optimization.

[0069] Parameter acquisition method:

[0070] 1) Weight coefficient Determined through the analytic hierarchy process;

[0071] 2) Cost Function Calculated through energy consumption model.

[0072] The tilt angle optimization empirical equations are specifically expressed as follows:

[0073] The relationship equation between tilting angle and pouring flow rate:

[0074] ;

[0075] Where, is the pouring flow rate, unit is kg / s; is the tilt angle, unit is rad; is the liquid level height, in m; is the acceleration due to gravity, which is 9.81 m / s²; is the outlet area, in m²; is the density of molten steel, unit is kg / m³; is the coefficient to be determined; is the random error term. The first term in the formula Describes the direct effect of gravity; the second term represents the flow rate under Torricelli's law; the third term Reflects the export area effect.

[0076] Parameter acquisition method:

[0077] 1) Real-time measurement through angle sensor;

[0078] 2) Measured by level sensor;

[0079] 3) Obtained through actual measurement;

[0080] 4) Fitted by nonlinear least squares method.

[0081] The relationship equation between tilting angle and pouring stability:

[0082] ;

[0083] Where, It is an indicator of casting stability; is the angular velocity, in rad / s; is the angular acceleration, in rad / s²; is the Reynolds number; is the coefficient to be determined; is the random error term. The formula adopts the form of dynamic equation, taking into account the influence of the quadratic terms of angular velocity and angular acceleration, as well as the influence of Reynolds number on flow stability.

[0084] Parameter acquisition method:

[0085] 1) Angular velocity and angular acceleration are calculated by differentiating the angle data;

[0086] 2) Calculated by fluid parameters;

[0087] 3) Obtained through system identification methods.

[0088] Comprehensive optimization objective function of tilt angle:

[0089] ;

[0090] Where, To optimize the objective function value; is the energy consumption function; is the weight coefficient and satisfies The linear weighted form is used to achieve the flow rate ( ),stability( ) and energy consumption ( ) balance.

[0091] Parameter acquisition method:

[0092] 1) Weight coefficient Determined by fuzzy analytic hierarchy process;

[0093] 2) Energy consumption function Calculated through the tilting mechanism power model.

[0094] The optimal water temperature solution is 15 to 20 degrees Celsius.

[0095] The optimal tilt angle solution is 32 degrees.

[0096] Furthermore, the weight coefficients in the water temperature optimization equations are The determination of the analytic hierarchy process (AHP) is adopted. First, it is necessary to establish a hierarchical structure including the target layer (comprehensive optimization of water temperature), the criterion layer (quality of quick-setting sheets A, cooling efficiency B, operating cost C) and the scheme layer (different water temperature schemes). Then, a judgment matrix is ​​constructed based on the expert scoring method using the 1-9 scale method. By calculating the maximum eigenvalue of the judgment matrix And solve the characteristic equation , normalizing the result to get the weight vector Finally, a consistency test is required to calculate the consistency index CI= , find the corresponding average random consistency index RI, calculate the consistency ratio CR=CI / RI, when CR<0.1, it means that the consistency test has passed.

[0097] Water temperature system cost function The calculation is based on the energy consumption model Carry out, where the pump power , including flow rate Q, head H, pump efficiency , operating time t and electricity price coefficient These parameters are collected in real time by a flow meter, head is measured by a pressure sensor, pump efficiency is queried through performance curves, operating time is recorded by a PLC timer, and the electricity price coefficient is set according to local electricity price standards. Accurate system operating costs can be obtained through the comprehensive calculation of these real-time data and fixed parameters.

[0098] Weight coefficients in the tilt optimization equations The fuzzy analytic hierarchy process (FAHP) was used to determine the importance of the criteria. First, the experts evaluated the importance of the criteria based on the linguistic variables (absolutely important (7, 9, 9), very important (5, 7, 9), important (3, 5, 7), slightly important (1, 3, 5), and equally important (1, 1, 3)) and constructed a triangular fuzzy number judgment matrix. . Then calculate the row geometric mean and fuzzy weights Finally, the center of gravity method is used to defuzzify and obtain the clear weight value .

[0099] Energy consumption function of tilting mechanism The calculation uses the power model , where the instantaneous power , including institutional quality , friction coefficient , moment of inertia and tilt angle These parameters are obtained by calculating the mass of the mechanism using design drawings, determining the friction coefficient experimentally, calculating the moment of inertia using the CAD model, and measuring the angle and angular acceleration using sensors. The total energy consumption is calculated using a numerical integration method with a time step of 0.1s and a trapezoidal integration formula. The innovation of this method lies in the introduction of fuzzy theory to address the uncertainty of expert judgment, considering energy consumption changes during dynamic processes, establishing a complete parameter acquisition system, and effectively combining theoretical models with actual operations. This method has achieved significant results in improving the scientific nature of weight determination, optimizing the accuracy of energy consumption calculations, enhancing the reliability of system operation, and improving the adaptability of control strategies.

[0100] Compared with existing technologies, the control system for rapid-setting sheet melting equipment provided by the present invention has the following beneficial effects: First, the control system utilizes a variety of sensor configurations, including temperature sensors, vacuum sensors, water pressure sensors, water temperature sensors, and speed sensors, enabling real-time data collection of various process parameters, providing reliable input for subsequent automated control. Second, the system designs corresponding automated control strategies for different process stages, such as heating power curve control, pouring power curve control, pouring tilt angle control, and copper roller speed control, ensuring that various parameters operate stably within the optimal range.

[0101] Crucially, this control system integrates theoretical advances in process modeling and parameter optimization. For example, by analyzing historical process data, a model was established to determine the impact of water temperature on product quality and cooling efficiency. This model then solved a multi-objective optimization problem to determine the optimal preset water temperature. Similarly, a quantitative relationship model was established between the tilting angle, pouring flow rate, and pouring stability, determining the optimal tilting angle. This resolves the existing technical issue of unstable product quality due to large fluctuations in process parameters and the difficulty in precise adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] Figure 1 A flow chart of the method provided by the present invention. DETAILED DESCRIPTION

[0103] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0104] The present invention provides a control system for a quick-setting sheet smelting device, comprising a sensor group and a quick-setting sheet smelting control module; the sensor group comprises a temperature sensor arranged in a smelting furnace, a vacuum degree sensor arranged in a vacuum system, a water pressure sensor and a water temperature sensor arranged in a water cooling system, and a speed sensor arranged at a copper roller; the quick-setting sheet smelting control module is used to control the quick-setting sheet smelting device to perform automatic smelting operations, such as Figure 1 As shown, the quick-setting sheet melting control module is used to perform the following steps:

[0105] S10, collecting data signals collected by the sensor group, including temperature data in the smelting furnace, vacuum degree data of the vacuum system, water pressure data and water temperature data of the water cooling system, and copper roller speed data;

[0106] S20, performing furnace door status detection according to preset process parameters to confirm that the furnace door is in a closed state and the remote control switch is in an enabled state;

[0107] S30, starting the smelting program according to the preset heating power curve, pouring power curve, pouring tilting curve and copper roller speed parameters;

[0108] S40, controlling the vacuum system to perform a vacuum operation, and automatically starting smelting after the vacuum degree sensor detects that the vacuum degree reaches a preset vacuum degree value;

[0109] S50, judging the time point when the molten steel is fully melted according to the temperature data detected by the temperature sensor, and sending a temperature measurement prompt signal when the preset temperature is reached;

[0110] S60: After receiving the temperature measurement instruction, the power is adjusted to 120 kilowatts, the temperature measuring rod is controlled to descend to a preset position to measure the temperature, and the measured temperature data is recorded;

[0111] S70, when the temperature data reaches the target temperature, the cooling phase begins, and the power is adjusted to 50 kilowatts for cooling;

[0112] S80, controlling the water cooling system to start, and after the water temperature sensor detects that the water temperature reaches a preset water temperature value, controlling the tilting mechanism to flip the crucible to a preset angle;

[0113] S90: During the pouring process, the copper roller speed is controlled according to the preset pouring power curve, and the speed is monitored in real time and compared with the preset speed to ensure the consistency of the thickness of the quick-setting sheet. When the deviation between the actual speed and the preset speed exceeds 5%, an alarm signal is issued.

[0114] The specific implementation of the above steps is described in detail below:

[0115] In step S10, various sensors in the sensor group are first used to collect key process parameter data during the smelting process. Specifically, the temperature data in the smelting furnace detected by the temperature sensor is recorded as , the vacuum system vacuum degree data detected by the vacuum sensor is recorded as ,The water pressure data of the water cooling system detected by the water pressure sensor is recorded as , the water temperature data detected by the water temperature sensor is recorded as , and the copper roller speed data detected by the speed sensor is recorded as These data reflect the changes in key parameters of the smelting process and provide necessary input for subsequent automatic control.

[0116] In step S20, first, the real-time detected temperature is adjusted according to the preset process parameter range. , vacuum degree , water pressure and water temperature The data is used to determine whether the current process status of the smelting equipment meets the conditions for allowing smelting. Specifically, it is necessary to ensure that the furnace door is in the closed state. And the remote control switch is in the allowed state Two prerequisites. Only when both conditions are met can the subsequent smelting process be continued. The purpose of this step is to ensure that the equipment and process are in a safe and reliable operating state.

[0117] In step S30, according to the pre-established heating power curve , pouring power curve , pouring tilt curve And copper roller speed parameters , start the specific execution of the smelting program. Among them, the heating power curve The time-power function relationship is established by analyzing historical smelting data and can be expressed as:

[0118] ;

[0119] function The specific form is obtained based on the fitting of a large amount of historical data. Similarly, the pouring power curve and pouring tilt curve The time-power and time-angle function relationships are established using a similar method:

[0120] ;

[0121] ;

[0122] Copper roller speed parameters The target thickness of the quick-setting sheet is , molten steel temperature The calculation process can be expressed as follows:

[0123] ;

[0124] The establishment of these preset parameters makes full use of historical process data and lays the foundation for realizing automated control.

[0125] In step S40, after starting the smelting process, the vacuum system is first controlled to perform vacuum operation. Reach the preset value Pa, the system automatically starts melting. This step can be described by the following mathematical expression:

[0126] when When , smelting begins;

[0127] when Continue to vacuum.

[0128] The purpose of this step is to ensure that the smelting process is carried out in a vacuum environment, which is beneficial to improving the purity and quality of the molten steel.

[0129] In step S50, the real-time temperature data detected by the temperature sensor is , judge the time point when the steel liquid is fully melted. Specifically, when the temperature When the temperature reaches 1500 degrees Celsius and remains stable for 5 minutes, it can be determined that the molten steel has been completely melted. This judgment condition can be expressed as:

[0130] when and maintain s, a temperature measurement prompt signal is issued.

[0131] The purpose of this step is to accurately grasp the timing of complete melting of the molten steel and provide a basis for temperature measurement.

[0132] In step S60, after receiving the temperature measurement prompt signal, the system adjusts the power to 120 kilowatts and controls the temperature measuring rod to descend to a distance from the surface of the molten steel. In this way, the actual temperature data of the current molten steel can be accurately measured. The mathematical description of this step is as follows:

[0133] When receiving the temperature measurement prompt signal,

[0134] ;

[0135] ;

[0136] Measured temperature

[0137] The purpose of this step is to obtain reliable molten steel temperature information to provide a basis for subsequent temperature control.

[0138] In step S70, when the temperature data Reach target temperature When , the system enters the cooling stage and adjusts the power to 50 kilowatts for cooling. The mathematical description of this step is as follows:

[0139] when hour, ;Enter the cooling stage.

[0140] The purpose of this step is to ensure that the temperature of the molten steel remains within the target temperature range and to prepare the temperature for subsequent pouring.

[0141] In step S80, the water cooling system is controlled to start, and when the water temperature sensor detects the water temperature Reach the preset value When the system controls the tilting mechanism, the crucible will flip to the preset angle. The mathematical description of this step is as follows:

[0142] when hour, ; Start pouring.

[0143] Among them, the water temperature preset value It is obtained by solving the optimal water temperature equations, including the relationship equation between water temperature and product quality:

[0144] ;

[0145] The relationship equation between water temperature and cooling efficiency:

[0146] ;

[0147] And the water temperature comprehensive optimization objective function:

[0148] ;

[0149] By solving the above equations, the optimal water temperature preset value can be obtained Similarly, the tilt angle preset value The optimal tilt angle is also determined by solving the optimal tilt angle equations. The calculation of these preset parameters fully considers the theoretical results of process optimization and is of great significance in improving process stability and product quality.

[0150] In step S90, according to the preset pouring power curve , real-time monitoring of copper roller speed And with the preset speed Compare to ensure the consistency of the thickness of the quick-setting sheet. Specifically, when the actual speed With preset speed When the deviation exceeds 5%, the system will issue an alarm signal. The mathematical description of this step is as follows:

[0151] when When an alarm signal is issued.

[0152] The purpose of this step is to use the copper roller speed sensor to monitor the casting process in real time, promptly discover and correct problems that may cause thickness deviation of the quick-setting sheet, and ensure the stability of product quality.

[0153] Specifically, the principle of the present invention is:

[0154] First, regarding the control system's architectural design, this invention employs a multi-layered control structure. The bottom layer is a sensor network responsible for real-time acquisition of process parameters; the middle layer is the control algorithm, implementing parameter optimization calculations; and the top layer is the execution system, which automatically adjusts the process. This layered structure not only improves system reliability but also facilitates independent optimization and upgrades of each module.

[0155] Secondly, in establishing process curves, this invention analyzes and models them based on extensive historical data. The heating power curve describes the energy input pattern during the melting process through the time-power function; the pouring power curve reflects the power regulation characteristics during the pouring process; and the pouring tilt curve depicts the optimal trajectory of the crucible rotation. The scientific nature of these curves lies in: first, fully considering the coupling relationship between process parameters; second, reflecting the dynamic characteristics of the process; and third, incorporating the distillation and summary of operational experience.

[0156] Thirdly, in terms of parameter optimization, the present invention innovatively proposes a set of equations for optimal water temperature and optimal tilt angle. The core concept of these two equations is to unify the multiple factors affecting product quality by establishing a mathematical model to achieve overall optimal control. Water temperature optimization considers product quality, cooling efficiency, and operating costs, determining the optimal value through a weighted summation method. Tilt angle optimization balances the three objectives of pouring flow rate, pouring stability, and energy consumption, adjusting the importance of each factor through weight coefficients.

[0157] Furthermore, this invention embodies unique technical principles in its exception handling mechanism. The system establishes a rapid-response monitoring system by comparing deviations between actual parameters and preset values ​​in real time. Specifically, a 5% deviation alarm threshold is set for copper roller speed control. This threshold was determined based on the following considerations: first, ensuring uniform thickness of the quick-setting sheet; second, considering the control accuracy of the equipment itself; and third, balancing alarm sensitivity and reliability.

[0158] From the perspective of process flow, the control strategy of the present invention is consistent with the basic principle of quick-setting sheet preparation. The system first ensures that the vacuum degree reaches Pa, a fundamental requirement for ensuring smelting quality; then, the temperature is controlled to rise to 1600°C, a point that ensures sufficient melting of the molten steel without causing excessive overheating; finally, by precisely controlling the water cooling system and the speed of the copper rollers, rapid solidification of the quick-setting sheet is achieved. The parameter settings for the entire process are fully theoretically based and verified in practice.

[0159] The following is an example of a specific application scenario of the present invention: the intelligent control system of the present invention is applied to a quick-setting sheet production line at a steel company. This line utilizes a vacuum melting process with multiple adjustable key process parameters, including temperature, vacuum level, water pressure, water temperature, and copper roller speed. To achieve automated control and optimization of these parameters, the company decided to introduce the intelligent control system proposed in this invention.

[0160] During implementation, the sensor suite was first configured based on the specific needs of the production line. Specifically, a temperature sensor was installed in the melting furnace to monitor the melt temperature in real time; a vacuum level sensor was installed in the vacuum system piping to monitor changes in vacuum level; a water pressure sensor and a water temperature sensor were installed in the water cooling system piping to monitor water pressure and temperature, respectively; and a speed sensor was installed on the copper roller bearings to monitor the real-time speed of the copper roller. The process parameter data collected by these sensors is transmitted via a fieldbus to a central control unit for processing and analysis.

[0161] After completing the sensor installation and commissioning, the company's technical staff began to establish preset curves and optimization models for various process parameters. First, by analyzing the detailed production data of the production line over the past five years, they extracted the heating power curve, pouring power curve, and pouring tilt curve. The specific steps are as follows:

[0162] 1) Establishment of heating power curve

[0163] (1) Collect the power change curve of the heating stage in the historical smelting data, as shown in Table 1.

[0164] Table 1 Historical heating power data

[0165]

[0166] (2) Based on the above data, the time-power function relationship is obtained by fitting:

[0167] ;

[0168] in, is the heating power, This function can well describe the change of power from the beginning of smelting to the complete melting of molten steel.

[0169] 2) Establishment of pouring power curve

[0170] (1) Collect the power change data during the historical pouring process, as shown in Table 2.

[0171] Table 2 Historical pouring power data

[0172]

[0173] (2) Based on the above data, the time-power function relationship is obtained by fitting:

[0174] ;

[0175] in, is the pouring power, is time. This function reflects the changing trend of power during the pouring process.

[0176] 3) Establishment of pouring tilt curve

[0177] (1) Collect the tilt angle change data during the historical pouring process, as shown in Table 3.

[0178] Table 3 Historical pouring tilt angle data

[0179]

[0180] (2) According to the above data, the functional relationship between time and angle is obtained by fitting:

[0181] ;

[0182] in, is the tilt angle, is time. This function describes the changing law of the tilting angle during the pouring process.

[0183] Next, the company's technical staff further established an optimization model based on two key parameters: water temperature and tilt angle.

[0184] 1) Establishment of water temperature optimization model

[0185] (1) Relationship model between water temperature and product quality

[0186] Through the analysis of a large amount of product quality data, a relationship between water temperature and product quality was established. Relationship:

[0187] ;

[0188] in, The model adopts the superposition of power function and Gaussian function, which can accurately describe the influence of water temperature on product quality.

[0189] (2) Relationship model between water temperature and cooling efficiency

[0190] Based on the thermodynamic heat transfer theory, the relationship between water temperature and cooling system efficiency was established. Linear relationship model:

[0191] ;

[0192] in, is the cooling water temperature rise, is the cooling water flow rate, is the water density, is the specific heat capacity of water. The model comprehensively considers the effects of temperature difference, flow rate, density and specific heat capacity on cooling efficiency.

[0193] (3) Water temperature comprehensive optimization objective function

[0194] Based on the above two sub-models, the comprehensive optimization objective function of water temperature is constructed:

[0195] ;

[0196] in, is the operating cost of the water cooling system. By solving the multi-objective optimization problem, the optimal water temperature preset value is determined to be 18 degrees Celsius.

[0197] 2) Establishment of tilt angle optimization model

[0198] (1) Relationship model between tilting angle and pouring flow

[0199] Based on the theory of fluid mechanics, the tilt angle With pouring flow Quantitative relationship:

[0200] ;

[0201] in, is the liquid level, is the acceleration due to gravity, is the outlet area, is the density of molten steel. The model takes into account the influence of factors such as gravitational potential energy, pressure potential energy and outlet area on the flow rate.

[0202] (2) Relationship model between tilting angle and casting stability

[0203] The dynamic equation is used to describe the tilting angle and casting stability index Relationship:

[0204] ;

[0205] in, is the angular velocity, is the angular acceleration, is the Reynolds number. The model takes into account the effects of angular velocity, angular acceleration and Reynolds number on flow stability.

[0206] (3) Comprehensive optimization objective function of tilt angle

[0207] Based on the above two sub-models, the comprehensive optimization objective function of the tilt angle is constructed:

[0208] ;

[0209] in, is the energy consumption of the tilting mechanism. By solving the multi-objective optimization problem, the optimal preset value of the tilting angle is determined to be 32 degrees.

[0210] After obtaining the preset curves and optimization models for the above process parameters, the company began to debug the actual intelligent smelting control system. The specific operation process is as follows:

[0211] 1) Pre-startup inspection: Before starting the smelting process, the system first checks the furnace door status and remote control switch status to confirm that both are in the allowed state.

[0212] 2) Heating stage control: according to the preset heating power curve , the system automatically adjusts the power to make the furnace temperature The change over time conforms to the curve. After reaching 1500 degrees Celsius and remaining stable for 5 minutes, the system will issue a temperature measurement prompt signal.

[0213] 3) Temperature measurement: After receiving the temperature measurement prompt signal, the system adjusts the power to 120 kilowatts and controls the temperature measuring rod to descend to a position 10 mm from the surface of the molten steel to measure the actual temperature. It is 1602 degrees Celsius.

[0214] 4) Cooling stage control: the actual temperature measured Compared with the target temperature of 1600 degrees Celsius, since it is slightly higher than the target value, the system automatically adjusts the power to 50 kilowatts and enters the cooling stage.

[0215] 5) Casting process control: When the water temperature When the optimized preset value of 18 degrees Celsius is reached, the system controls the tilting mechanism to flip the crucible to 32 degrees for pouring. During the pouring process, the system monitors the speed of the copper roller in real time. , and with the preset speed Compare and ensure that the actual speed deviation does not exceed 5%.

[0216] 6) Quality Inspection: After the above-mentioned automatic control process, the quick-setting sheet products finally produced have dimensional accuracy, mechanical properties and other indicators that meet the requirements. The product qualification rate reaches 98%, which is 3 percentage points higher than before.

[0217] By implementing the intelligent control system of the present invention, enterprises have not only increased production efficiency but also significantly improved product quality. The key aspects are as follows:

[0218] 1) The sensor monitoring is comprehensive and can collect key parameter data of the smelting process in real time, providing reliable input for automated control.

[0219] 2) The process parameters are preset reasonably. The heating power curve, pouring power curve and tilting curve established by analyzing historical data can accurately describe the parameter change law of each process stage and ensure that the smelting process is stable and orderly.

[0220] 3) The optimization of key parameters is effective. The multi-objective optimization method is used to determine the optimal preset values ​​of water temperature and tilt angle, achieving a balance in improving product quality, enhancing cooling efficiency and reducing operating costs.

[0221] 4) Real-time monitoring feedback is in place. Through dynamic monitoring of the copper roller speed and deviation alarm, the consistency of the quick-setting sheet thickness is ensured, which greatly improves the stability of product quality.

[0222] It should be noted that the explanation of relevant variables is shown in Table 4 below:

[0223] Table 4 Variable Explanation Table

[0224]

[0225] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed by the present invention, which should be covered by the scope of protection of the present invention.

Claims

1. A control system for a rapid-setting sheet melting device, characterized in that: It includes a sensor group and a quick-setting sheet smelting control module; the sensor group includes a temperature sensor set in the smelting furnace, a vacuum degree sensor set in the vacuum system, a water pressure sensor set in the water cooling system, a water temperature sensor and a speed sensor set at the copper roller; the quick-setting sheet smelting control module is used to control the quick-setting sheet smelting equipment to perform automatic smelting operation, and the quick-setting sheet smelting control module is used to perform the following steps: S10, collecting data signals collected by the sensor group, including temperature data in the smelting furnace, vacuum degree data of the vacuum system, water pressure data and water temperature data of the water cooling system, and copper roller speed data; S20, performing furnace door status detection according to preset process parameters to confirm that the furnace door is in a closed state and the remote control switch is in an enabled state; S30, starting the smelting program according to the preset heating power curve, pouring power curve, pouring tilting curve and copper roller speed parameters; S40, controlling the vacuum system to perform a vacuum operation, and automatically starting smelting after the vacuum degree sensor detects that the vacuum degree reaches a preset vacuum degree value; S50, judging the time point when the molten steel is fully melted according to the temperature data detected by the temperature sensor, and sending a temperature measurement prompt signal when the preset temperature is reached; S60: After receiving the temperature measurement instruction, the power is adjusted to 120 kilowatts, the temperature measuring rod is controlled to descend to a preset position to measure the temperature, and the measured temperature data is recorded; S70, when the temperature data reaches the target temperature, the temperature is lowered and the power is adjusted to 50 kilowatts for cooling; S80, controlling the water cooling system to start, and after the water temperature sensor detects that the water temperature reaches a preset water temperature value, controlling the tilting mechanism to flip the crucible to a preset angle; S90: During the pouring process, the copper roller speed is monitored in real time according to the preset pouring power curve and compared with the preset speed to ensure the consistency of the thickness of the quick-setting sheet. When the deviation between the actual speed and the preset speed exceeds 5%, an alarm signal is issued; The preset water temperature value is obtained by solving the optimal water temperature equation group; the optimal water temperature equation group includes the relationship equation between water temperature and quick-setting sheet quality, the relationship equation between water temperature and cooling efficiency, and the water temperature comprehensive optimization objective function; The method further includes solving an optimal tilting angle equation group to obtain a preset tilting angle value, wherein the optimal tilting angle equation group includes an equation for the relationship between the tilting angle and the pouring flow rate, an equation for the relationship between the tilting angle and the pouring stability, and a tilting angle comprehensive optimization objective function; wherein, the equation for the relationship between the tilting angle and the pouring flow rate is: ; Where, is the pouring flow rate, is the tilt angle, is the liquid level, is the acceleration due to gravity, The outlet area is the density of molten steel, is the coefficient to be determined; is the random error term.

2. A control system for rapid-setting sheet smelting equipment according to claim 1, characterized in that: The preset process parameters specifically include a melting temperature range, a vacuum range, a water pressure range, a water temperature range, and a copper roller speed range.

3. A control system for rapid-setting sheet smelting equipment according to claim 2, characterized in that: The steps for establishing the preset heating power curve specifically include: S101, collecting heating power data from historical smelting data; S102, establishing a time-power function relationship based on power data of different time periods; S103: Generate a heating power curve according to the time-power function relationship.

4. A control system for rapid-setting sheet smelting equipment according to claim 3, characterized in that: The steps for establishing the preset pouring power curve include: S201, collecting power data during historical pouring processes; S202, establishing a time-power function relationship according to the power variation law in the pouring stage; S203: Generate a pouring power curve according to the time-power function relationship.

5. A control system for rapid-setting sheet smelting equipment according to claim 4, characterized in that: The steps for establishing the preset pouring tilting curve include: S301, collecting tilt angle data during historical pouring processes; S302, establishing a time-angle function relationship according to the tilting angle variation rule during the pouring stage; S303: Generate a pouring tilt curve according to the time-angle function relationship.

6. A control system for rapid-setting sheet smelting equipment according to claim 5, characterized in that: The steps for determining the preset copper roller speed parameters specifically include: S401, determining a reference rotation speed according to a target thickness of the quick-setting sheet; S402, correcting the reference speed according to the molten steel temperature; S403. Determine the copper roller speed parameter according to the corrected value.

7. A control system for rapid-setting sheet smelting equipment according to claim 6, characterized in that: The standard for judging the time point when the molten steel is fully melted is: the temperature in the melting furnace reaches 1500 degrees Celsius and remains stable for 5 minutes.

8. A control system for rapid-setting sheet smelting equipment according to claim 7, characterized in that: The copper roller speed sensor monitors the copper roller speed and is used to: monitor the copper roller speed in real time and compare it with the preset speed to ensure the consistency of the thickness of the quick-setting sheet. When the deviation between the actual speed and the preset speed exceeds 5%, an alarm signal is issued.

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