Control system for rapid hardening sheet smelting equipment

Abstract

The invention provides a control system for rapid hardening sheet smelting equipment, and belongs to the technical field of industrial control, the control system comprises a sensor group and a rapid hardening sheet smelting control module, and the execution steps of the control module are as follows: firstly, collecting temperature, vacuum degree, water pressure, water temperature and copper roller rotating speed data of the sensor group; checking a furnace door closing state and a remote control allowing state; starting a smelting procedure according to a preset heating power curve, a pouring power curve, a pouring tilting curve and a copper roller rotating speed parameter, and starting smelting after the vacuum degree reaches the standard; the system automatically judges the full melting time point of the molten steel and sends out a temperature measurement prompt, and the power is adjusted to 120 kilowatts according to an instruction for temperature measurement; the power is reduced to 50 kilowatts after the target temperature is reached; after the water temperature reaches the standard, the crucible is controlled to be overturned to a preset angle; and finally, the pouring process is controlled according to the pouring power curve, the rotating speed of the copper roller is monitored in real time, and an alarm is given in time when the deviation exceeds 5%. The technical problem of unstable product quality in the prior art is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of industrial control, and in particular relates to a control system for quick-setting sheet smelting 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, quick-setting sheet smelting equipment mainly adopts the following control methods in industrial production:

[0003] First, the traditional manual experience control mode still dominates in many companies. Operators need to judge key indicators such as molten steel temperature, vacuum degree, water cooling system parameters based on experience, and manually adjust the smelting power, tilting angle and copper roller speed. This control method has the following limitations: First, human judgment is subjective, and it is difficult to ensure the precise control of process parameters; second, the skill levels of operators vary, resulting in large fluctuations in product quality; third, manual operation has a slow response speed, making it difficult to handle process abnormalities in a timely manner.

[0004] Secondly, some enterprises use simple PID control systems. Although such systems realize basic automatic control functions, their control strategies are relatively simple and cannot adapt to complex process requirements. Specifically, they are: first, the control parameters are fixed and lack self-adaptation; second, each control loop is independent of each other and lacks system coordination; third, it is impossible to establish a correlation model between process parameters and product quality.

[0005] As the quality requirements of quick-setting sheets in downstream application fields continue to increase, the existing control technology has been unable to meet the needs of industrial development. Due to the large fluctuations in process parameters and the difficulty in precise adjustment, product quality is unstable. Summary of the invention

[0006] In view of this, the present invention provides a control system for quick-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 arranged in a water cooling system, a water temperature sensor and a rotation speed sensor arranged at 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 speed data of the copper roller;

[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 allowed 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 drops to a lowering stage, and the power is adjusted to 50 kilowatts for lowering the temperature;

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

[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 quick-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 rotation 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 according to power data in 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, generating 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 changing law of the tilting angle during the pouring stage;

[0032] S303, generating a pouring tilting 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 temperature of the molten steel;

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

[0037] Furthermore, the standard for judging the time point when the molten steel is fully melted is that 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 sends 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 of water temperature;

[0040] The water temperature and quick-setting tablet quality relationship equation is used to characterize the influence of water temperature on the quick-setting tablet quality, reflects the temperature reference effect through the power function term, and describes the optimal temperature point effect through the exponential function term, so as to realize the quantitative correlation between water temperature and product quality;

[0041] The water temperature and cooling efficiency relationship equation is used to describe the influence mechanism of water temperature on 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, and realizes multi-objective optimization by 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 a tilting angle and a pouring flow relationship equation, a tilting angle and a pouring stability relationship equation, and a tilting angle comprehensive optimization objective function;

[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, taking into account the influence of factors such as gravitational potential energy, pressure potential energy and outlet area on the flow rate, to achieve 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, and the pouring stability is characterized by parameters such as angular velocity, angular acceleration and Reynolds number, so as to provide 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 equation group is specifically expressed as follows:

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

[0049] ;

[0050] In the formula, 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 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] In the formula, For cooling efficiency; is the cooling water temperature rise, unit: °C; is the cooling water flow rate, in m / s; is the water density, in kg / m³; is the specific heat capacity of water, in 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 the 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] In the formula, 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 analytic hierarchy process;

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

[0072] The tilt angle optimization empirical equation group is specifically expressed as follows:

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

[0074] ;

[0075] In the formula, is the pouring flow rate, unit is kg / s; is the tilt angle, unit is rad; is the liquid level, in m; is the acceleration due to gravity, take 9.81m / s²; is the outlet area, in m²; is the density of molten steel, unit: kg / m³; is the coefficient to be determined; is the random error term. The first term 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] In the formula, It is an indicator of pouring 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] In the formula, To optimize the objective function value; is the energy consumption function; is the weight coefficient and satisfies The linear weighted form is used in the formula to achieve 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 using the tilting mechanism power model.

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

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

[0096] Furthermore, the weight coefficient in the water temperature optimization equation group The determination of the analytic hierarchy process (AHP) is adopted. First, a hierarchical structure including the target layer (comprehensive optimization of water temperature), the criterion layer (quality of quick-setting tablets A, cooling efficiency B, operating cost C) and the scheme layer (different water temperature schemes) needs to be established. 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 can 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 The water pump power , including flow rate Q, head H, pump efficiency , operating time t and electricity price coefficient These parameters are obtained in the following ways: flow rate is collected in real time by flow meter, head is measured by pressure sensor, pump efficiency is queried by performance curve, running time is recorded by PLC timer, and electricity price coefficient is set according to local electricity price standard. The accurate system operation cost 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, 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 weight Finally, the centroid 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 through design drawings, determining the friction coefficient through experiments, calculating the moment of inertia through CAD models, measuring the angle and angular acceleration through sensors, and calculating the total energy consumption using a numerical integration method with a time step of 0.1s and a trapezoidal integration formula. The innovation of this method is to introduce fuzzy theory to deal with the uncertainty of expert judgment, consider the energy consumption changes in the dynamic process, establish a complete parameter acquisition system, and realize the effective combination of theoretical models and actual operations. It has achieved remarkable results in improving the scientific nature of weight determination, optimizing the accuracy of energy consumption calculation, enhancing the reliability of system operation, and improving the adaptability of control strategies.

[0100] Compared with the prior art, the beneficial effects of the control system for quick-setting sheet smelting equipment provided by the present invention are as follows: first, the control system adopts a variety of sensor configurations, including temperature sensors, vacuum sensors, water pressure sensors, water temperature sensors and speed sensors, etc., which can collect various process parameter data in real time and provide reliable input for subsequent automatic control. Secondly, the system designs corresponding automatic 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, etc., to ensure that various parameters operate stably within the optimal range.

[0101] More importantly, the control system integrates the theoretical results of process modeling and parameter optimization. For example, by analyzing historical process data, a model of the influence of water temperature on product quality and cooling efficiency was established, and the multi-objective optimization problem was solved to obtain the optimal water temperature preset value. Similarly, a quantitative relationship model between the tilting angle and the pouring flow and pouring stability was established to determine the optimal tilting angle, solving the technical problem of unstable product quality caused by large fluctuations in process parameters and difficulty in precise adjustment in the existing technology. 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 solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0104] 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 arranged in a water cooling system, a water temperature sensor and a rotation speed sensor arranged at a copper roller; the quick-setting sheet smelting control module is used to control the quick-setting sheet smelting equipment to perform automatic smelting operations, such as Figure 1 As shown, the quick-setting sheet smelting 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 of the water cooling system, water temperature data, 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 allowed 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 vacuuming 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 temperature drops to a lower temperature stage, and the power is adjusted to 50 kilowatts for lowering the temperature;

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

[0114] The specific implementation methods of the above steps are 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 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, the furnace door must be in the closed state. And the remote control switch is in the enabled state Two prerequisites. Only when these two conditions are met can the subsequent smelting procedures be continued. The purpose of this step is to ensure that the equipment and process status are in a safe and reliable operating state.

[0117] In step S30, according to the pre-established heating power curve , Casting 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 established by analyzing historical smelting data can be expressed as:

[0118] ;

[0119] function The specific form of is 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 in a similar way:

[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:

[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 program, the vacuum system is first controlled to perform a vacuum operation. The vacuum degree sensor detects when the vacuum degree is 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 , to determine 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 of 100 degrees 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] Measure the temperature

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

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

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

[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 started. 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 pouring is performed. The mathematical description of this step is as follows:

[0142] when hour, ; Start pouring.

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

[0144] ;

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

[0146] ;

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

[0148] ;

[0149] By solving the above equations, the optimal water temperature preset value can be obtained Similarly, the tilt angle preset value It 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 To ensure the consistency of the thickness of the quick-setting sheet, 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 pouring 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, from the perspective of the control system architecture design, the present invention adopts a multi-level control structure. The bottom layer is the sensor network, which is responsible for the real-time collection of process parameters; the middle layer is the control algorithm, which realizes the optimization calculation of parameters; the upper layer is the execution system, which completes the automatic adjustment of the process. This hierarchical structure not only improves the reliability of the system, but also facilitates the independent optimization and upgrading of each module.

[0155] Secondly, in terms of establishing the process curve, the present invention analyzes and models based on a large amount of historical data. The heating power curve describes the energy input law in the smelting process through the time-power function relationship; the pouring power curve reflects the power regulation characteristics in the pouring process; and the pouring tilting curve depicts the optimal trajectory of the crucible flipping. The scientific nature of these curves lies in: first, they fully consider the coupling relationship between process parameters; second, they reflect the dynamic characteristics of the process; and third, they contain the refinement and summary of operating experience.

[0156] Again, in terms of parameter optimization, the present invention innovatively proposes the optimal water temperature equation group and the optimal tilt angle equation group. The core idea of ​​these two equation groups is: by establishing a mathematical model, multiple factors affecting product quality are unified to achieve overall optimal control. Among them, water temperature optimization takes into account three aspects: product quality, cooling efficiency, and operating cost, and determines the optimal value by weighted summation; tilt angle optimization balances the three goals of pouring flow, pouring stability, and energy consumption, and adjusts the importance of each factor through the weight coefficient.

[0157] In addition, the present invention also embodies unique technical principles in terms of abnormal handling mechanism. The system establishes a fast-response monitoring system by comparing the deviation between the actual parameters and the preset values ​​in real time. In particular, in terms of copper roller speed control, a 5% deviation alarm threshold is set. The determination of this value is based on the following considerations: first, it meets the requirements for uniform thickness of the quick-setting sheet; second, it takes into account the control accuracy of the equipment itself; and third, it balances the sensitivity and reliability of the alarm.

[0158] From the perspective of process flow, the control strategy of the present invention conforms to the basic principle of quick-setting sheet preparation. The system first ensures that the vacuum degree reaches Pa, which is the basic condition to ensure the quality of smelting; then control the temperature to rise to 1600 degrees Celsius, this temperature point can ensure that the molten steel is fully melted without causing excessive overheating; finally, by accurately controlling the water cooling system and the speed of the copper roller, the rapid solidification of the quick-setting sheet is achieved. The parameter settings of the entire process have sufficient theoretical basis and practical verification.

[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 the quick-setting sheet production line of a certain steel enterprise. The production line adopts a vacuum melting process and has multiple adjustable key process parameters such as temperature, vacuum degree, water pressure, water temperature and copper roller speed. In order to realize the automatic control and optimization of these parameters, the enterprise decided to introduce the intelligent control system proposed by the present invention.

[0160] During the implementation process, the sensor group was first configured according to the actual situation of the production line. Specifically, a temperature sensor was installed in the smelting furnace to detect the melt temperature in real time; a vacuum sensor was installed on the vacuum system pipeline to monitor the vacuum change; a water pressure sensor and a water temperature sensor were installed on the water cooling system pipeline to monitor the water pressure and water temperature; a speed sensor was installed at the copper roller bearing to detect the real-time speed of the copper roller. The process parameter data collected by these sensors in real time will be transmitted to the central control unit through the field bus for processing and analysis.

[0161] After completing the installation and debugging of the sensor, the company's technical staff set out 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, the heating power curve, pouring power curve and pouring tilting curve were extracted. 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 functional relationship between time and power is obtained by fitting:

[0167] ;

[0168] in, is the heating power, is time. This function can well describe the change law 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 functional relationship between time and power 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 tilting curve

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

[0178] Table 3 Historical pouring tilt angle data

[0179]

[0180] (2) Based on 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 form 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 influence of factors such as temperature difference, flow rate, density and specific heat capacity on cooling efficiency.

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

[0194] According to 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 rate

[0199] Based on the theory of fluid mechanics, the tilt angle is established 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 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] According to 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] With the preset curves and optimization models of 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 program, the system first checks the furnace door status and remote control switch status to confirm that they are both in the permitted 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 sends 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 drop 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 the preset speed Compare and ensure that the actual speed deviation does not exceed 5%.

[0216] 6) Quality inspection: After the above automatic control process, the quick-setting sheet products finally produced have dimensional accuracy, mechanical properties and other indicators that meet the requirements, and 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 can improve production efficiency and significantly improve product quality. The key is reflected in the following aspects:

[0218] 1) The sensor monitoring is comprehensive and can collect key parameter data of the smelting process in real time, providing reliable input for automatic 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 optimal preset values ​​of water temperature and tilt angle are determined by using a multi-objective optimization method, 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, greatly improving 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 implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A control system for a quick-setting sheet smelting device, characterized in that: It includes a sensor group and a quick-setting sheet smelting control module; the sensor group includes a temperature sensor arranged in the smelting furnace, a vacuum degree sensor arranged in the vacuum system, a water pressure sensor arranged in the water cooling system, a water temperature sensor and a speed sensor arranged 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 speed data of the copper roller; 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 allowed 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 drops to a lowering stage, and the power is adjusted to 50 kilowatts for lowering the temperature; 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 pouring power curve is controlled according to the preset, the copper roller speed is monitored in real time and compared with the preset speed to ensure the consistency of the thickness of the quick-setting sheet, and an alarm signal is issued when the deviation between the actual speed and the preset speed exceeds 5%.

2. A control system for a rapid-setting sheet smelting device 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 rotation speed range.

3. A control system for a rapid-setting sheet smelting device 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 according to power data in 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 specifically 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, generating 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 specifically include: S301, collecting tilt angle data during historical pouring processes; S302, establishing a time-angle function relationship according to the change law of the tilting angle 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 of 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 temperature of the molten steel; S403, determining the copper roller speed parameter according to the corrected value.

7. A control system for a rapid-setting sheet smelting device 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 actual speed deviates from the preset speed by more than 5%, an alarm signal is issued.

9. A control system for rapid-setting sheet smelting equipment according to claim 8, characterized in that: 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 comprehensive optimization objective function of water temperature; The water temperature and quick-setting tablet quality relationship equation is used to characterize the influence of water temperature on the quick-setting tablet quality, reflects the temperature reference effect through the power function term, and describes the optimal temperature point effect through the exponential function term, so as to realize the quantitative correlation between water temperature and product quality; The water temperature and cooling efficiency relationship equation is used to describe the influence mechanism of water temperature on 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. 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, and realizes multi-objective optimization by weighted summation to determine the optimal water temperature preset value.

10. A control system for rapid-setting sheet smelting equipment according to claim 9, characterized in that: 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; 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, taking into account the influence of factors such as gravitational potential energy, pressure potential energy and outlet area on the flow rate, to achieve precise control of the pouring flow rate; The relationship equation between the tilting angle and the pouring stability is used to evaluate the dynamic characteristics of the pouring process, and the pouring stability is characterized by parameters such as angular velocity, angular acceleration and Reynolds number, so as to provide a basis for process optimization; 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.

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