Continuous equipment temperature distribution optimization control method and system

Abstract

The invention discloses a continuous equipment temperature distribution optimization control method and system, and belongs to the technical field of temperature control, and the method specifically comprises the steps: monitoring equipment production process parameters in real time, and transmitting the parameters to a control center; the control center corrects the parameters by using a compensation algorithm constructed based on an ideal gas state equation, extracts furnace temperature data from the corrected parameters, calculates a control signal according to the deviation between the furnace temperature data and a preset furnace temperature target value by adopting PID (Proportion Integration Differentiation) operation, and adjusts the opening degree of a gas actuator to obtain a corrected gas flow value; calculating required combustion-supporting air flow according to the value and a preset air-fuel ratio, and adjusting a combustion-supporting air actuator to stabilize heat supply in the furnace; when the furnace temperature is stable, an online temperature measurement thermal imager is used for collecting the temperatures of five point positions of the pipe body, the average value is calculated and compared with the temperature required by the process, and then the left and right temperature adjustment areas are adjusted; the method can effectively improve the stability of equipment production and the product quality.

Description

Technical Field

[0001] The present invention belongs to the technical field of temperature control, and in particular relates to a method and system for optimizing temperature distribution control of continuous equipment. Background Art

[0002] Traditional furnace temperature control in equipment uses PID control. This involves continuously measuring the furnace temperature and comparing it to a setpoint. After PID adjustment by the control center, the furnace temperature is stabilized near the setpoint by controlling the opening of actuators in the heating and holding sections, and by adjusting the speed of the cooling fans in the fast and slow cooling sections. This control method has several major drawbacks: 1) The measured furnace temperature is the furnace top temperature, not the actual tube annealing temperature, which can result in suboptimal annealing results; 2) Temperature adjustment is based on the opening of the actuator, which cannot guarantee an optimal combustion ratio and wastes energy; 3) There are no temperature and pressure sensors on the pipelines, resulting in inaccurate flow rate measurements; 4) Equipment production data is manually recorded every hour, which is time-consuming, inaccurate, and prone to data loss; 5) The setpoint temperatures in each zone of the equipment must be manually adjusted based on changes in tube composition, resulting in lags in the adjustment. Consequently, a continuous equipment temperature distribution optimization control method and system has been developed to ensure accurate temperature control and maximize energy utilization, reducing production costs. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present invention proposes a continuous equipment temperature distribution optimization control method and system, which monitors the equipment production process parameters in real time and transmits them to the control center; the control center uses a compensation algorithm constructed based on the ideal gas state equation to correct the parameters, extracts the furnace temperature data from the corrected parameters, and uses PID calculation to calculate the control signal according to its deviation from the preset furnace temperature target value, and adjusts the opening of the gas actuator to obtain the corrected gas flow value; then, based on this value and the preset air-fuel ratio, the required combustion-supporting air flow is calculated, and the combustion-supporting air actuator is adjusted to stabilize the heat supply in the furnace; when the furnace temperature is stable, the online temperature measuring thermal imager is used to collect the temperatures of 5 points on the tube body, the average value is calculated and compared with the process requirement temperature, and then the left and right temperature adjustment zones are adjusted; this method can effectively improve the stability of equipment production and product quality.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A method for optimizing and controlling temperature distribution of a continuous device, comprising:

[0006] Step S1: Real-time monitoring of equipment production process parameters and transmission to the control center; the equipment production process parameters include gas and combustion air flow, temperature, and pressure data collected by sensors on the gas pipeline and combustion air pipeline, and furnace temperature data collected by the furnace top thermocouple;

[0007] Step S2: The control center corrects the equipment production process parameters based on the compensation algorithm constructed based on the ideal gas state equation to obtain the corrected equipment production process parameters;

[0008] Step S3: The control center extracts the corrected furnace temperature data from the corrected equipment production process parameters, uses PID calculation to calculate a control signal based on the deviation between the corrected furnace temperature data and the preset furnace temperature target value, and adjusts the gas actuator opening according to the control signal to obtain a corrected gas flow value;

[0009] Step S4: Calculate the required combustion air flow rate based on the corrected gas flow rate and the preset air-fuel ratio. The control center adjusts the combustion air actuator based on the obtained combustion air flow rate to stabilize the heat supply in the furnace.

[0010] Step S5: When the furnace temperature of the equipment stabilizes, the temperature data of 5 points on the tube body are collected using an online temperature measuring thermal imager and transmitted to the control center. The control center calculates the average value of points 1, 2, and 3 as the first average value, and calculates the average value of points 3, 4, and 5 as the second average value. The first and second average values ​​are compared with the process required temperature, and the left and right temperature adjustment zones are adjusted according to the comparison results.

[0011] Specifically, the specific steps of step S2 include:

[0012] S2.1: Obtain equipment production process parameters;

[0013] S2.2: Construct compensation algorithm based on ideal gas state equation , where P represents pressure, T represents Kelvin temperature, and Q represents flow rate under actual measurement conditions. represents the flow rate after compensation, Indicates the pressure under standard conditions, Indicates the temperature under standard conditions, Indicates the pressure after compensation, Indicates the actual measured pressure. represents the reference temperature, represents the temperature after compensation, Indicates the actual measured temperature. Indicates the temperature correction value obtained based on experimental data;

[0014] S2.3: According to the constructed compensation algorithm, compensation calculation is performed on the acquired equipment production process parameters to obtain compensated equipment production process parameters, and the compensated equipment production process parameters are output as corrected equipment production process parameters, including corrected flow, corrected pressure, and corrected temperature.

[0015] Specifically, the specific steps of step S3 include:

[0016] S3.1: The control center extracts the corrected furnace temperature data from the equipment production process parameters corrected by the compensation algorithm ;

[0017] S3.2: Compare the extracted corrected furnace temperature data with the pre-set furnace temperature target value Perform difference calculation to obtain furnace temperature deviation value , where k represents the index of the time sampling point;

[0018] S3.3: Use time series analysis algorithm to analyze the furnace temperature deviation Perform trend prediction and obtain deviation trend prediction results.

[0019] Specifically, the specific steps of step S3 also include:

[0020] S3.4: According to The control signal is calculated by using the improved PID control algorithm integrating multiple parameters based on the prediction results of the deviation trend. ; The improved PID control algorithm logic is:

[0021] Calculate the product of the proportional coefficient and the current deviation to obtain the first part of the parameters;

[0022] Calculate the product of the integral coefficient and the cumulative result of multiplying all deviations from the initial moment to the current moment by the sampling period to obtain the second part of the parameters;

[0023] Calculate the product of the differential coefficient and the current moment deviation minus the previous moment deviation divided by the sampling period to obtain the third part of the parameters;

[0024] Calculate the product of the thermal inertia compensation coefficient, the thermal inertia parameter and the current deviation change rate to obtain the fourth part of the parameters;

[0025] Calculate the product of the ambient temperature compensation coefficient and the ambient temperature to obtain the fifth part of the parameters;

[0026] Calculate the product of the noise compensation coefficient and the current system noise to obtain the sixth part of the parameters;

[0027] Calculate the sum of the first, second, third, fourth, and fifth parameters, subtract the sixth parameter, and multiply by the corresponding adaptive weighting factor of each parameter to obtain the control signal at the kth moment;

[0028] S3.5: The calculated control signal Convert it into the corresponding gas actuator opening adjustment instruction, and change the gas flow through the actuator;

[0029] S3.6: Enter the next sampling cycle, add 1 to the k value, repeat steps S3.1-S3.5, and obtain the corrected gas flow value.

[0030] Specifically, the specific steps of S3.5 include:

[0031] S3.51: Get the calculated control signal , and determine the range of the control signal and actuator opening range ,in, and Represent the minimum and maximum values ​​of the control signal, respectively. and Respectively represent the minimum and maximum values ​​of the actuator opening;

[0032] S3.52: Establish the mapping relationship between the control signal and the actuator opening;

[0033] S3.53: Design a linear transformation algorithm based on the mapping relationship between the control signal and the actuator opening, and Substitute it into the linear transformation algorithm to obtain the corresponding gas actuator opening adjustment instruction;

[0034] S3.54: Convert the calculated actuator opening value y into the instruction format received by the actuator, and send the adjustment instruction to the gas actuator through the serial port. The actuator adjusts the opening according to the received instruction.

[0035] The instruction format received by the executor is a byte sequence;

[0036] S3.55: After the actuator is activated, the furnace temperature change is monitored in real time and the furnace temperature information is fed back to the control center. The control center adjusts the control signal again based on the difference between the fed-back furnace temperature and the target value.

[0037] Specifically, the specific process of S3.52 includes:

[0038] During the operation of the device, starting from the minimum value of the control signal, a fixed step size is added each time , wait for the actuator to stabilize and then record the opening value;

[0039] The iteration is repeated until the control signal reaches the maximum value, thereby obtaining multiple sets of control signal-actuator opening data pairs.

[0040] Specifically, the specific steps of step S4 include:

[0041] S4.1: Obtain the corrected gas flow value from S3.6 and obtain the preset air-fuel ratio from the system parameter settings;

[0042] S4.2: Based on the corrected gas flow rate and gas density The product of the gas mass per unit time is obtained. ;

[0043] S4.3: Based on the quality of gas per unit time The product of the preset air-fuel ratio is the mass of the combustion air required per unit time. ;

[0044] S4.4: Pass and the density of the combustion air The required combustion air flow rate is calculated by ;

[0045] S4.5: The control center converts the calculated combustion air flow value into a corresponding control signal and sends the control signal to the combustion air actuator through the serial port. The actuator adjusts the opening according to the received signal to change the combustion air flow;

[0046] S4.6: Real-time monitoring of the combustion conditions and temperature changes in the furnace to obtain the actual combustion air flow value and the heat supply status in the furnace;

[0047] S4.7: Calculation and The difference between the two values ​​is used to obtain the combustion air flow control signal according to the improved PID control algorithm that integrates multiple parameters in S3.4. ;

[0048] S4.8: The control center controls the signal based on the combustion air flow rate Adjust the opening of the combustion air actuator.

[0049] Specifically, the specific steps of step S5 include:

[0050] S5.1: When the furnace temperature of the equipment stabilizes, the online temperature measurement thermal imager starts working to collect temperature data at five points on the pipe body and transmits the collected temperature data from the five points to the control center via the wireless network;

[0051] S5.2: After receiving the temperature data, the control center calculates the average value of points 1, 2, and 3 as the first average value Calculate the average of points 3, 4, and 5 as the second average ;

[0052] S5.3: and and furnace temperature target value Perform difference calculation to obtain two temperature differences and ;

[0053] S5.4: Based on the temperature difference and , adjust the left and right temperature control zones according to a preset adjustment strategy; the preset adjustment strategy includes:

[0054] like , it means that the temperature of the left temperature control zone where points 1, 2, and 3 are located is too high, so the power of the left temperature control zone is reduced;

[0055] like , it means that the temperature of the left temperature control zone where points 1, 2, and 3 are located is too low, so the temperature of the left temperature control zone is increased;

[0056] like , it means that the temperature of the right temperature control zone where points 3, 4, and 5 are located is too high, so the power of the right temperature control zone is reduced;

[0057] like , it means that the temperature of the right temperature control zone where points 3, 4, and 5 are located is too low, so the temperature of the right temperature control zone is increased.

[0058] Specifically, the flow, temperature and pressure data of the gas and combustion-supporting air collected in step S1 are collected by installing flow meters on the gas pipeline and the combustion-supporting air pipeline, and installing temperature measuring resistors and pressure transmitters behind the flow meters.

[0059] A continuous equipment temperature distribution optimization control system, including: programmable control, gas electric actuator, combustion air electric actuator, thermocouple and thermal resistor, online temperature measurement thermal imager, gas and combustion air flow meter, gas and combustion air pressure transmitter, data acquisition and analysis system, cooling fan;

[0060] The programmable control is configured by isolating an analog quantity to stably collect sensor signals. The heating section and the heat preservation section of the continuous equipment adjust the flow of gas and combustion air through the PID control actuator according to the difference between the set value and the actual temperature value. The fast cooling section and the slow cooling section of the continuous equipment adjust the speed of the cooling fan through the reaction of the PID regulation according to the difference between the set value and the actual temperature value.

[0061] The gas electric actuator is used to control the flow of gas passing through the pipeline;

[0062] The combustion-supporting air electric actuator is used to control the flow of the combustion-supporting air through the pipeline;

[0063] The thermocouple and thermal resistor are used to detect the furnace temperature. The detection signal is connected to the control center through the transmitter. After the control center receives the furnace temperature signal, it compares it with the set value and makes adjustments;

[0064] The online temperature measuring thermal imager is used to detect the temperature of the tube during annealing;

[0065] The gas and combustion-supporting air flowmeters are used to detect the flow of gas in the pipeline;

[0066] The gas and combustion air pressure transmitters are used to detect the pressure of the gas in the pipeline;

[0067] The data acquisition and analysis system is used to collect equipment production process parameters, including furnace temperature, gas and combustion air pressure, flow data, and perform real-time online detection of furnace temperature and tube temperature;

[0068] The cooling fan adjusts the atmosphere and temperature distribution in the equipment by sending cooling air into the equipment.

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] 1. The present invention proposes a method for optimizing and controlling the temperature distribution of continuous equipment. By real-time monitoring of parameters such as the flow rate, temperature, pressure, and furnace temperature of coal gas and combustion-supporting air, and correcting them using a compensation algorithm based on the ideal gas state equation, the accuracy of parameter measurement can be effectively improved. The method also combines PID calculation to adjust the opening of the coal gas actuator, and adjusts the combustion-supporting air actuator according to the air-fuel ratio, thereby ensuring a stable heat supply in the furnace and accurately controlling the furnace temperature. This is beneficial to improving the quality stability of the product during the annealing process and reducing product defects caused by furnace temperature fluctuations.

[0071] 2. The present invention proposes a continuous equipment temperature distribution optimization control method. After the furnace temperature stabilizes, the temperature data of specific points on the tube body is collected with the help of an online temperature measuring thermal imager. The average value is calculated and compared with the temperature required by the process, and then the left and right temperature adjustment zones are adjusted in a targeted manner. This refined temperature monitoring and control method can further optimize the heating uniformity of different parts of the tube body, meet the strict requirements of complex processes for temperature distribution, enhance the adaptability and controllability of the equipment production process, and at the same time help reduce energy consumption and improve production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 This is a schematic diagram of a method for optimizing temperature distribution control of a continuous device according to the present invention;

[0073] Figure 2 This is a principle flow chart of a continuous equipment temperature distribution optimization control method of the present invention;

[0074] Figure 3This is a flow chart of parameter correction during the production process of the equipment of the present invention;

[0075] Figure 4 This is a flow chart of the control signal adjustment of the present invention;

[0076] Figure 5 This is a flow chart of temperature adjustment in the temperature adjustment zone of the present invention;

[0077] Figure 6 This is a control system diagram for the heating section and the heat preservation section in a continuous equipment temperature distribution optimization control system of the present invention;

[0078] Figure 7 This is a control system diagram for the rapid cooling section and the heat preservation section of a continuous equipment temperature distribution optimization control system of the present invention. DETAILED DESCRIPTION

[0079] Example 1

[0080] See also Figure 1 and Figure 2 The present invention provides an embodiment: a method for optimizing and controlling the temperature distribution of a continuous device. In the present invention, the device refers to an annealing furnace. The method includes steps S1 to S5, including the following steps:

[0081] Step S1: Real-time monitoring of equipment production process parameters and transmission to the control center; the equipment production process parameters include the flow, temperature, and pressure data of gas and combustion air collected by the gas pipeline and combustion air pipeline, and the furnace temperature data collected by the furnace top thermocouple;

[0082] Step S2: The control center corrects the equipment production process parameters based on the compensation algorithm constructed based on the ideal gas state equation to obtain the corrected equipment production process parameters;

[0083] Step S3: The control center extracts the corrected furnace temperature data from the corrected equipment production process parameters, uses PID calculation to calculate a control signal based on the deviation between the corrected furnace temperature data and the preset furnace temperature target value, and adjusts the gas actuator opening according to the control signal to obtain a corrected gas flow value;

[0084] Step S4: Calculate the required combustion air flow rate based on the corrected gas flow rate and the preset combustion ratio. The control center adjusts the combustion air actuator based on the obtained combustion air flow rate to stabilize the heat supply in the furnace.

[0085] Step S5: When the furnace temperature of the equipment stabilizes, the temperature data of 5 points on the tube body are collected using an online temperature measuring thermal imager and transmitted to the control center. The control center calculates the average value of points 1, 2, and 3 as the first average value, and calculates the average value of points 3, 4, and 5 as the second average value. The first and second average values ​​are compared with the process required temperature, and the left and right temperature adjustment zones are adjusted according to the comparison results.

[0086] Example 2

[0087] See also Figure 3 In this embodiment, the specific steps of step S2 include:

[0088] S2.1: Obtain equipment production process parameters;

[0089] S2.2: According to the ideal gas state equation , build compensation algorithm , where P represents pressure, T represents Kelvin temperature, V represents the volume of the gas, R represents the gas constant, n represents the amount of substance, that is, the number of molecules contained in the gas, and Q represents the flow rate under the actual measurement state. represents the flow rate after compensation, Indicates the pressure under standard conditions, Indicates the temperature under standard conditions, Indicates the pressure after compensation, Indicates the actual measured pressure. represents the reference temperature, represents the temperature after compensation, Indicates the actual measured temperature. Indicates the temperature correction value obtained based on experimental data;

[0090] It should be noted that according to the ideal gas state equation , the density can be obtained , and the flow Q is related to the density Inversely proportional, that is , when pressure and temperature change, density will also change, so the flow rate after compensation The relationship between the flow rate Q, pressure P, and temperature T under the actual measurement state is: , where N represents the molar mass, Indicates the proportional sign, Expresses flow rate Q and density Proportional to the reciprocal of .

[0091] At the same time, assuming that there is a functional relationship between the pressure measurement value and the temperature, when the temperature deviates from the reference temperature, the pressure measurement value will deviate. According to the actual situation and experimental data, based on the temperature characteristic analysis and experimental calibration of the pressure measurement system, the compensation formula can be obtained. , temperature compensation is performed on the pressure measurement value, eliminating or reducing the influence of temperature on pressure measurement, and improving the accuracy of pressure measurement. Therefore, accurate pressure measurement is crucial for flow compensation and the stable operation of the entire equipment control center, and helps to more accurately control gas supply and furnace temperature.

[0092] Finally, the temperature compensation formula is derived based on the principle of temperature measurement and the influencing factors in practical applications. For example, the ambient temperature may have a thermal conductivity effect on the temperature sensor, resulting in a deviation in the measured value. The deviation is determined through experiments and analysis. , thus obtaining the compensation formula By compensating the furnace temperature measurement value, the accuracy of temperature measurement is improved. It can be seen that accurate furnace temperature data is the key to equipment control, which helps to achieve more precise temperature control, improve product quality, and reduce product defects and energy waste caused by temperature errors.

[0093] Regarding flow compensation, for example, in a large chemical production plant, the flow of the reaction gas needs to be precisely controlled to ensure the stability of the chemical reaction and the consistency of the product quality. The gas flow is measured by an orifice flow meter. However, in the actual production process, the pressure and temperature of the gas will fluctuate greatly, affecting the accuracy of the flow measurement. In this application, the measured value of the uncompensated flow is known. , pressure under standard conditions Kilopascals, unit kPa, pressure kPa, temperature , the unit is K, that is, Kelvin temperature, the temperature under standard conditions , then according to the flow compensation formula of the present invention, we can get , because the traditional method considers that the flow is , and the actual flow rate is calculated after compensation as Through the flow compensation formula of this application, the influence of pressure and temperature on gas flow can be accurately considered, and a flow value that is more in line with the actual situation can be provided. This is crucial for scenarios in chemical production that require extremely high flow accuracy. It can effectively avoid problems such as reaction out of control and product quality fluctuations caused by inaccurate flow, which are impossible to achieve with traditional uncompensated flow measurement technology.

[0094] Regarding pressure compensation, for example, in oil and gas pipelines, it is necessary to monitor the pressure in the pipeline in real time to ensure transportation safety. The pressure sensor is installed on the pipeline, but its measured value will be affected by changes in ambient temperature. Assuming that the actual measured pressure value is known kPa, temperature , reference temperature According to the pressure compensation formula in the present invention, we can know Kilopascals. Since traditional measurements may directly use 800 kilopascals as the pipeline pressure, and after pressure compensation, the actual pressure is found to be 873.72 kilopascals. Therefore, the pressure compensation formula of this application can effectively eliminate the influence of ambient temperature on pressure measurement and provide more accurate data for pipeline pressure monitoring. This is of great significance for ensuring the safe and stable operation of oil and gas pipelines. Compared with traditional pressure measurement technology that does not consider the influence of temperature, it can more accurately reflect the actual pressure conditions in the pipeline and avoid safety hazards and economic losses caused by misjudgment of pressure.

[0095] Regarding temperature compensation, for example, in the semiconductor chip manufacturing process, the precise control of the furnace temperature directly affects the performance and yield of the chip. Thermocouples are used to measure the temperature in the furnace, but the measurement of thermocouples will be affected by factors such as the installation position and the airflow in the furnace, resulting in deviations in the measured temperature. Assuming that , determine the temperature correction value through experiments and data analysis According to the temperature compensation formula in the present invention, we can know Since traditional measurements would assume the furnace temperature is 723 Kelvin, while the actual temperature is determined to be 728 Kelvin after compensation, the temperature compensation formula of this application can effectively correct the deviation in the thermocouple measurement process by introducing a temperature correction value, providing more accurate furnace temperature data for semiconductor chip manufacturing. This greatly improves the accuracy of temperature control in the chip manufacturing industry, which has almost stringent requirements on temperature accuracy, and reduces the chip defective rate caused by temperature errors, which is difficult to achieve with traditional simple temperature measurement technology.

[0096] S2.3: According to the constructed compensation algorithm, compensation calculation is performed on the acquired equipment production process parameters to obtain compensated equipment production process parameters, and the compensated equipment production process parameters are output as corrected equipment production process parameters, including corrected flow, corrected pressure, and corrected temperature.

[0097] Example 3

[0098] See also Figure 4 In this embodiment, the specific steps of step S3 include:

[0099] S3.1: The control center extracts the corrected furnace temperature data from the equipment production process parameters corrected by the compensation algorithm ;

[0100] S3.2: Compare the extracted corrected furnace temperature data with the pre-set furnace temperature target value Perform difference calculation to obtain furnace temperature deviation value , where k represents the index of the time sampling point;

[0101] S3.3: Use time series analysis algorithm to analyze the furnace temperature deviation Perform trend prediction and obtain deviation trend prediction results;

[0102] Furthermore, the specific steps of S3.3 include:

[0103] S3.31: Collect historical data of furnace temperature deviation from the equipment control center;

[0104] S3.32: Load a pre-built autoregressive integrated moving average model. The autoregressive integrated moving average model is a prior art in this field and is not an inventive solution of the present application, so it will not be described in detail here.

[0105] S3.33: Use the historical data of the furnace temperature deviation value to train the pre-built autoregressive integrated moving average model to obtain a trained autoregressive integrated moving average model;

[0106] S3.34: Input the latest furnace temperature deviation data into the trained autoregressive integral sliding average model. The trained autoregressive integral sliding average model outputs a trend prediction result of the furnace temperature deviation based on the input latest furnace temperature deviation data.

[0107] S3.4: According to The control signal is calculated by using the improved PID control algorithm integrating multiple parameters based on the prediction results of the deviation trend. ; The improved PID control algorithm logic is:

[0108] Calculate the product of the proportional coefficient and the current deviation to obtain the first part of the parameters;

[0109] Calculate the product of the integral coefficient and the cumulative result of multiplying all deviations from the initial moment to the current moment by the sampling period to obtain the second part of the parameters;

[0110] Calculate the product of the differential coefficient and the current moment deviation minus the previous moment deviation divided by the sampling period to obtain the third part of the parameters;

[0111] Calculate the product of the thermal inertia compensation coefficient, the thermal inertia parameter and the current deviation change rate to obtain the fourth part of the parameters;

[0112] Calculate the product of the ambient temperature compensation coefficient and the ambient temperature to obtain the fifth part of the parameters;

[0113] Calculate the product of the noise compensation coefficient and the current system noise to obtain the sixth part of the parameters;

[0114] Calculate the sum of the first, second, third, fourth, and fifth parameters, subtract the sixth parameter, and multiply by the corresponding adaptive weighting factor of each parameter to obtain the control signal at the kth moment;

[0115] Furthermore, the specific formula of the improved PID control algorithm using the fusion of multiple parameters is: Calculating control signals ,in, represents the adaptive weighting factor, represents the proportionality coefficient, represents the integral coefficient, represents the differential coefficient, Indicates the furnace temperature deviation value at the last sampling moment, represents the thermal inertia compensation coefficient, H represents the thermal inertia parameter, represents the ambient temperature compensation coefficient, E represents the ambient temperature influence parameter, represents the noise compensation coefficient, represents the estimated value of system noise, M represents the sampling period, Indicates the furnace temperature deviation value at the i-th sampling moment;

[0116] Furthermore, in the present invention, 、 and The Ziegler-Nichols method is used for adjustment. First, the critical gain of the system is obtained through experiments. and critical period , then according to the formula calculate 、 and The initial value is set and finally fine-tuned according to the actual system operation conditions.

[0117] For the thermal inertia compensation coefficient The thermal inertia parameter H is set by experimental modeling. In a laboratory environment or actual production, a series of temperature change experiments are carried out on the equipment to record the response curves of the furnace temperature under different inputs, such as gas flow changes. By analyzing these curves, the thermal inertia characteristics of the equipment can be obtained. Using system identification methods, such as the least squares method, a thermal inertia model is established to determine the thermal inertia parameter H. The thermal inertia compensation coefficient Through experimental adjustment, we can observe the control effect of the system after adding the thermal inertia compensation term and find the one that makes the system respond fastest and most stable. value.

[0118] For the ambient temperature effect parameter E, multiple ambient temperature sensors are installed around the equipment to monitor the ambient temperature changes in real time and analyze the relationship between the ambient temperature and the furnace temperature. For example, the fluctuation of the furnace temperature under different ambient temperatures is recorded experimentally, and a mathematical model of the influence of the ambient temperature and the furnace temperature is established to obtain the ambient temperature effect parameter E. The ambient temperature compensation coefficient By conducting experiments under different ambient temperature conditions, the control effect of the system is observed and the The value of can make the system maintain good control performance at different ambient temperatures, that is, the furnace temperature can reach the target value quickly and stably. Among them, optimization algorithms, such as genetic algorithms, can be used to automatically search for the optimal value.

[0119] System noise estimate The Kalman filter algorithm is used to process the sensor measurement data. The Kalman filter algorithm uses two steps, prediction and update, to combine the system's dynamic model and measurement noise model to make the best estimate of the system state. In this process, the estimated value of the system noise can be obtained. ; Noise compensation coefficient It is determined based on the characteristics of the system noise and the degree of influence on the control performance , we can observe the noise suppression effect of the system after adding the noise compensation term through experiments, and adjust The value of , so that the system can still operate stably in the presence of noise interference.

[0120] In order to adjust the weight of each control item at different operation stages, the adaptive weighting parameter is introduced , and satisfies ,in, represents a constant that controls the convergence rate, express The autocorrelation matrix can dynamically adjust the weight of each control item according to the system's operating stage and state, so that the system can achieve the best control effect under different working conditions. For example, during the equipment startup phase, increasing the weight of the proportional term can make the system respond quickly to deviations; during the stable operation phase, enhancing the role of the integral term can eliminate steady-state errors.

[0121] In summary, considering the thermal inertia characteristics of the equipment, thermal inertia will cause a delay in the furnace temperature change. In order to compensate for this delay in advance, the thermal inertia compensation term is introduced. , can predict the trend of furnace temperature changes in advance, reduce the control lag caused by thermal inertia, enable the furnace temperature to reach the target value more quickly and accurately, and improve the control accuracy. At the same time, changes in ambient temperature will affect the heat dissipation and heating process of the equipment. In order to eliminate this effect, the ambient temperature compensation item is introduced , taking into account the influence of ambient temperature on furnace temperature, the ambient temperature compensation term can eliminate the interference of ambient temperature changes on the control effect, so that the system can maintain stable control performance under different ambient temperatures. Finally, in order to reduce the influence of sensor measurement noise on the control signal, the noise compensation term is introduced , which can effectively suppress the influence of sensor measurement noise on the control signal, reduce the control error caused by noise, and further improve the control accuracy.

[0122] For example, in an industrial device, the temperature in the furnace needs to be controlled to ensure the annealing quality of the metal material. The traditional PID controller often has poor control effect when dealing with complex working conditions. For example, the thermal inertia of the furnace, the change of ambient temperature and the noise of the sensor will cause the furnace temperature to fluctuate greatly, affecting the product quality. To control, can better adapt to these complex situations;

[0123] Assuming the traditional PID parameters , , , thermal inertia compensation coefficient , thermal inertia parameter H=20, ambient temperature compensation coefficient , noise compensation coefficient , sampling period M=1s, adaptive weighting parameters In the equipment startup phase, it is set to 1.2, in the stable operation phase, it is set to 1, and the furnace temperature target value , initial furnace temperature , initial deviation , ambient temperature affects parameters , the system noise estimated by Kalman filtering , when simulating the control process, since it is the initial moment, ,and , , substitute the formula in the present invention to calculate the control signal , this control signal will be converted into the opening adjustment instruction of the gas actuator, increasing the gas flow and making the furnace temperature rise rapidly. After running for a period of time, such as k=10, assuming that after 10 sampling cycles, the furnace temperature , then the deviation , and assuming , To accumulate the previously calculated values, , at this time the adaptive weighting parameter , substitute into the formula to calculate the control signal At this time, the value of the control signal decreases, and the opening of the gas actuator decreases accordingly, which slows down the rise of the furnace temperature and approaches the target temperature.

[0124] It should be noted that the value of the Celsius temperature plus 273.15 can be used to obtain the corresponding Kelvin temperature.

[0125] S3.5: The calculated control signal Convert it into the corresponding gas actuator opening adjustment instruction, change the gas flow through the actuator, and thus change the furnace temperature towards the target value;

[0126] S3.6: Enter the next sampling cycle, add 1 to the k value, repeat steps S3.1-S3.4, and obtain the corrected gas flow value.

[0127] The specific steps of S3.5 include:

[0128] S3.51: Get the calculated control signal , and determine the range of the control signal and actuator opening range ,in, and Represent the minimum and maximum values ​​of the control signal, respectively. and Respectively represent the minimum and maximum values ​​of the actuator opening;

[0129] Among them, the range of the control signal is determined by checking the manuals of the actuator, controller and other related equipment, and the mechanical structure of the actuator itself determines the limit of its opening. In the present invention, the range of the control signal is determined according to the requirements of the equipment process for adjustment accuracy and adjustment amplitude. If the process requires high furnace temperature control accuracy, the control signal range is reduced to achieve more precise adjustment; if the furnace temperature adjustment allows a fluctuation range, the control signal range is increased. For example, the furnace temperature fluctuation range is required to be within ±1°C. In order to achieve such a small furnace temperature fluctuation by accurately adjusting the gas flow, the adjustment amplitude of the gas flow may be between 0.1% and 1% of its full range; the minimum and maximum values ​​of the actuator opening are determined according to the requirements of the medium flow, such as gas and combustion air flow, during the equipment process. For example, the process requires the combustion air flow to be within Interval, through conversion, the range of the actuator opening can be obtained as .

[0130] S3.52: Establish the mapping relationship between the control signal and the actuator opening;

[0131] S3.53: Design a linear transformation algorithm based on the mapping relationship between the control signal and the actuator opening , and Substitute into the linear transformation algorithm to obtain the corresponding gas actuator opening adjustment instruction, where y represents the actuator opening value;

[0132] S3.54: Convert the calculated actuator opening value into a command format that the actuator can receive, and send the adjustment command to the gas actuator through the serial port. The actuator adjusts the opening according to the received command.

[0133] The instruction format received by the executor is a byte sequence;

[0134] The specific process of converting the calculated actuator opening value into the instruction format received by the actuator includes:

[0135] (1) According to the provisions of the actuator data format, convert the calculated opening value into the corresponding numerical value. For example, assuming that the actuator opening range is 0-100%, and the calculated opening is 50%, if the 16-bit unsigned integer representation in the Modbus protocol is used, then the corresponding value is 65535×0.5=32767.5, rounded up to 32768;

[0136] (2) For a 16-bit unsigned integer, split it into two 8-bit bytes, namely the high 8 bits and the low 8 bits. Taking 32768 as an example, its hexadecimal representation is 0x8000, then the high 8-bit byte is 0x80 and the low 8-bit byte is 0x00. In this way, a byte sequence containing two bytes [0x80, 0x00] is obtained, which is the byte sequence that the actuator can receive to indicate 50% opening.

[0137] The process of adjusting the opening of the actuator includes:

[0138] (1) Analyze the response information returned by the actuator to determine whether the instruction is executed successfully. If the response information shows that the actuator has received the instruction and started to adjust the opening, proceed to the next step;

[0139] (2) The gas actuator adjusts its opening according to the received instructions and changes the gas flow. During the actuator operation, the actual opening information of the actuator is obtained in real time through the monitoring equipment to verify the adjustment effect.

[0140] S3.55: After the actuator is activated, the furnace temperature change is monitored in real time and the furnace temperature information is fed back to the control center. The control center adjusts the control signal again based on the difference between the fed-back furnace temperature and the target value.

[0141] The specific process of S3.52 includes:

[0142] During the operation of the device, starting from the minimum value of the control signal, a fixed step size is added each time , wait for the actuator to stabilize and then record the opening value;

[0143] The iteration is repeated until the control signal reaches the maximum value, thereby obtaining multiple sets of control signal-actuator opening data pairs.

[0144] The specific steps of step S4 include:

[0145] S4.1: Obtain the corrected gas flow value from S3.6 and obtain the preset air-fuel ratio from the system parameter settings;

[0146] S4.2: Based on the corrected gas flow rate and gas density The product of the gas mass per unit time is obtained. ;

[0147] S4.3: Based on the quality of gas per unit time The product of the preset air-fuel ratio is the mass of the combustion air required per unit time. ;

[0148] S4.4: Pass and the density of the combustion air The required combustion air flow rate is calculated by ;

[0149] S4.5: The control center converts the calculated combustion air flow value into a corresponding control signal and sends the control signal to the combustion air actuator through the serial port. The actuator adjusts the opening according to the received signal to change the combustion air flow;

[0150] Furthermore, the specific steps of S4.5 include:

[0151] (1) Determine the control signal range of the actuator by consulting the product manual of the combustion air actuator;

[0152] (2) Based on the characteristics of the combustion air system and experimental data, the relationship between the combustion air flow value and the actuator opening is established. Then, combined with the control signal range of the actuator, the mapping relationship between the flow value and the control signal is determined;

[0153] Among them, establishing the relationship between the combustion air flow value and the actuator opening is achieved through a fitting model. The fitting model adopts a linear model. The linear model is the existing technology content in this field and is not the creative solution of this application, so it will not be elaborated here.

[0154] Among them, the mapping relationship between the flow value and the control signal is determined by combining the flow-opening relationship and the control signal-opening relationship through a linear interpolation method to obtain the mapping relationship between the flow value and the control signal. Among them, the linear interpolation method is the existing technology content in this field and is not the creative solution of this application, so it will not be elaborated here.

[0155] (3) Based on the calculated combustion air flow value, the corresponding control signal value is calculated using the above mapping relationship;

[0156] (4) Determine the serial port device used to communicate with the combustion air actuator, and set the communication parameters of the serial port according to the communication requirements of the actuator, including baud rate, data bits, stop bits and check bits;

[0157] (5) Convert the control signal into a byte sequence according to S3.54;

[0158] (6) Send the converted serial port data to the combustion air actuator according to the serial port communication protocol;

[0159] (7) After receiving the control signal, the combustion air actuator adjusts its opening according to the size of the signal, thereby changing the flow rate of the combustion air;

[0160] (8) The actual flow of the combustion-supporting air is monitored in real time by sensors installed on the combustion-supporting air duct, such as flow meters, and the monitoring data is fed back to the control center. The control center compares the actual flow with the target flow and makes further adjustments based on the deviation.

[0161] S4.6: Real-time monitoring of the combustion conditions and temperature changes in the furnace to obtain the actual combustion air flow value and the heat supply status in the furnace;

[0162] S4.7: Calculation and The difference between the two values ​​is used to obtain the combustion air flow control signal according to the improved PID control algorithm that integrates multiple parameters in S3.4. ;

[0163] S4.8: The control center controls the signal based on the combustion air flow rate Adjust the opening of the combustion air actuator.

[0164] Example 4

[0165] See also Figure 5 In this embodiment, the specific steps of step S5 include:

[0166] S5.1: When the furnace temperature of the equipment stabilizes, the online temperature measurement thermal imager starts working to collect temperature data at five points on the pipe body and transmits the collected temperature data from the five points to the control center via the wireless network;

[0167] S5.2: After receiving the temperature data, the control center calculates the average value of points 1, 2, and 3 as the first average value Calculate the average of points 3, 4, and 5 as the second average ;

[0168] S5.3: and and furnace temperature target value Perform difference calculation to obtain two temperature differences and ;

[0169] S5.4: Based on the temperature difference and , adjust the left and right temperature control zones according to a preset adjustment strategy; the preset adjustment strategy includes:

[0170] like , it means that the temperature of the left temperature control zone where points 1, 2, and 3 are located is too high, so the power of the left temperature control zone is reduced;

[0171] like , it means that the temperature of the left temperature control zone where points 1, 2, and 3 are located is too low, so the temperature of the left temperature control zone is increased;

[0172] like , it means that the temperature of the right temperature control zone where points 3, 4, and 5 are located is too high, so the power of the right temperature control zone is reduced;

[0173] like , it means that the temperature of the right temperature control zone where points 3, 4, and 5 are located is too low, so the temperature of the right temperature control zone is increased.

[0174] Example 5

[0175] See also Figure 6 and Figure 7 ,exist Figure 6 In the figure, BZ101 and BZ102 represent control nodes, TN430 represents online temperature measurement thermal imager, Figure 7 A represents an air outlet. Another embodiment provided by the present invention is a continuous equipment temperature distribution optimization control system, comprising: a programmable controller, a gas electric actuator, a combustion air electric actuator, a thermocouple and a thermal resistor, an online temperature measurement thermal imager, a gas and combustion air flow meter, a gas and combustion air pressure transmitter, a data acquisition and analysis system, and a cooling fan;

[0176] Programmable control uses analog isolators to stably collect sensor signals. The heating and holding sections of continuous equipment use PID control actuators to adjust the flow of gas and combustion-supporting air based on the difference between the set value and the actual temperature value to ensure the optimal combustion ratio, allowing the gas to burn fully, achieving the highest combustion value and reducing production costs. The fast cooling and slow cooling sections of continuous equipment use the reaction of PID regulation to adjust the cooling fan speed based on the difference between the set value and the actual temperature value, thereby adjusting the furnace temperature.

[0177] Gas electric actuator, used to control the flow of gas through the pipeline;

[0178] The combustion air electric actuator is used to control the flow of combustion air through the pipeline;

[0179] Among them, the gas electric actuator and the combustion air electric actuator receive the 4-20ma signal from the control center to open the actuator opening, thereby increasing or decreasing the gas flow through the pipeline. At the same time, the opening signal will also be fed back to the control center through the 4-20ma signal.

[0180] Thermocouples and thermal resistors are used to detect furnace temperature. The detection signal is connected to the control center through a transmitter. After the control center receives the furnace temperature signal, it compares it with the set value and makes adjustments;

[0181] Among them, the thermistor is used to detect the gas temperature in the pipeline. As the furnace temperature increases, the air intake pipeline will also be affected to a certain extent, and the temperature has a great influence on the flow calculation. Temperature changes will cause changes in physical properties such as gas density and viscosity, thereby affecting the measurement accuracy of the flow meter. In order to reduce the impact of temperature on the flow meter, this application adds a thermistor behind the flow meter to detect the temperature online in real time, and corrects the measurement results through the temperature compensation algorithm to ensure the measurement accuracy of the flow meter at different temperatures. Only accurate flow can guarantee the correct combustion ratio, and there is no temperature compensation in traditional equipment, which may lead to inaccurate flow.

[0182] Online temperature measurement thermal imager, used to detect the temperature of the tube during annealing;

[0183] It should be noted that because the thermocouple is installed on the top of the furnace, there is still a certain difference between its temperature and the actual annealing zone temperature. In order to ensure the temperature requirements of the annealing process of ductile iron pipes, this application uses an online temperature measuring thermal imager to detect the temperature of the pipe during annealing online. It can collect the temperatures of five parts of the pipe to ensure that the annealing temperature requirements are met. If the furnace temperature meets the temperature requirements, but the surface temperature of the pipe does not meet the standard, precise adjustments can be made according to the surface temperature of the pipe. Among them, the annealing process is mainly to eliminate internal stress and improve the organizational structure, thereby improving the mechanical properties and processing performance of the pipe.

[0184] Gas and combustion air flow meters are used to detect the flow of gas in the pipeline;

[0185] It should be noted that the temperature regulation of traditional equipment relies on the opening of the actuator to control the combustion ratio. This can meet production requirements when the gas flow is stable. However, in the actual production process, the gas is often transported from the blast furnace. In this way, the gas flow in the actual production process is often unstable due to the influence of the blast furnace. Therefore, when the opening is the same, the gas flow may be large or small, while the combustion-supporting air is constant. In this way, too little air may lead to incomplete combustion, and some components in the gas cannot fully play their role, resulting in a decrease in the total calorific value. Too much air will dilute the gas, which also leads to a decrease in the total calorific value. Therefore, this application adds a flow meter to control the opening of the actuator according to the actual flow of the gas.

[0186] Gas and combustion air pressure transmitters are used to detect the pressure of gas in the pipeline;

[0187] It should be noted that because pressure changes have a significant impact on flow calculations, the flowmeter can maintain high measurement accuracy within a certain pressure range. However, when the fluid pressure exceeds or falls below the design range, the flowmeter reading may deviate. This is because the density and viscosity of the fluid will change with changes in pressure, thus affecting the flowmeter's measurement results. To reduce the impact of pressure on the flowmeter, this application adds a pressure transmitter behind the flowmeter to detect pressure online in real time. The measurement results are corrected using a pressure compensation algorithm to ensure the flowmeter's measurement accuracy under different pressures. Only accurate flow can guarantee a correct combustion ratio.

[0188] Data acquisition and analysis system, used to collect equipment production process parameters, including furnace temperature, gas and combustion air pressure, flow data, and perform real-time online detection of furnace temperature and tube temperature;

[0189] The data acquisition and analysis system collects data every hour and saves it in an SQL database, producing a daily report every 24 hours. It also performs real-time online detection of furnace and tube temperatures. When an abnormality occurs, an alarm is immediately generated. When an abnormality occurs in the annealed tube, the production data of the day can be retrieved for analysis.

[0190] The cooling fan adjusts the atmosphere and temperature distribution inside the equipment by sending cooling air into the equipment.

[0191] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific embodiments. The above-mentioned specific embodiments are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also change, modify, replace and modify the above-mentioned embodiments without departing from the purpose and scope of protection of the present invention. These are all protected by the present invention.

Claims

1. A method for optimizing the temperature distribution of a continuous device, characterized in that: include: Step S1: Real-time monitoring of equipment production process parameters and transmission to the control center; the equipment production process parameters include gas and combustion air flow, temperature, and pressure data collected by sensors on the gas pipeline and combustion air pipeline, and furnace temperature data collected by the furnace top thermocouple; Step S2: The control center corrects the equipment production process parameters based on the compensation algorithm constructed based on the ideal gas state equation to obtain the corrected equipment production process parameters; Step S3: The control center extracts the corrected furnace temperature data from the corrected equipment production process parameters, uses PID calculation to calculate a control signal based on the deviation between the corrected furnace temperature data and the preset furnace temperature target value, and adjusts the gas actuator opening according to the control signal to obtain a corrected gas flow value; Step S4: Calculate the required combustion air flow rate based on the corrected gas flow rate and the preset air-fuel ratio. The control center adjusts the combustion air actuator based on the obtained combustion air flow rate to stabilize the heat supply in the furnace. Step S5: When the furnace temperature of the equipment stabilizes, the temperature data of 5 points on the tube body are collected using an online temperature measuring thermal imager and transmitted to the control center. The control center calculates the average value of points 1, 2, and 3 as the first average value, and calculates the average value of points 3, 4, and 5 as the second average value. The first and second average values ​​are compared with the process required temperature, and the left and right temperature adjustment zones are adjusted according to the comparison results.

2. A method for optimizing temperature distribution of a continuous equipment according to claim 1, characterized in that: The specific steps of step S2 include: S2.1: Obtain equipment production process parameters; S2.2: Construct compensation algorithm based on ideal gas state equation , where P represents pressure, T represents Kelvin temperature, and Q represents flow rate under actual measurement conditions. represents the flow rate after compensation, Indicates the pressure under standard conditions, Indicates the temperature under standard conditions, Indicates the pressure after compensation, Indicates the actual measured pressure. represents the reference temperature, represents the temperature after compensation, Indicates the actual measured temperature. Indicates the temperature correction value obtained based on experimental data; S2.3: According to the constructed compensation algorithm, compensation calculation is performed on the acquired equipment production process parameters to obtain compensated equipment production process parameters, and the compensated equipment production process parameters are output as corrected equipment production process parameters, including corrected flow, corrected pressure, and corrected temperature.

3. A method for optimizing temperature distribution of a continuous equipment according to claim 2, characterized in that: The specific steps of step S3 include: S3.1: The control center extracts the corrected furnace temperature data from the equipment production process parameters corrected by the compensation algorithm ; S3.2: Compare the extracted corrected furnace temperature data with the pre-set furnace temperature target value Perform difference calculation to obtain furnace temperature deviation value , where k represents the index of the time sampling point; S3.3: Use time series analysis algorithm to analyze the furnace temperature deviation Perform trend prediction and obtain deviation trend prediction results.

4. A method for optimizing temperature distribution control of a continuous equipment according to claim 3, characterized in that: The specific steps of step S3 also include: S3.4: According to The control signal is calculated by using the improved PID control algorithm integrating multiple parameters based on the prediction results of the deviation trend. ; The improved PID control algorithm logic is: Calculate the product of the proportional coefficient and the current deviation to obtain the first part of the parameters; Calculate the product of the integral coefficient and the cumulative result of multiplying all deviations from the initial moment to the current moment by the sampling period to obtain the second part of the parameters; Calculate the product of the differential coefficient and the current moment deviation minus the previous moment deviation divided by the sampling period to obtain the third part of the parameters; Calculate the product of the thermal inertia compensation coefficient, the thermal inertia parameter and the current deviation change rate to obtain the fourth part of the parameters; Calculate the product of the ambient temperature compensation coefficient and the ambient temperature to obtain the fifth part of the parameters; Calculate the product of the noise compensation coefficient and the current system noise to obtain the sixth part of the parameters; Calculate the sum of the first, second, third, fourth, and fifth parameters, subtract the sixth parameter, and multiply by the corresponding adaptive weighting factor of each parameter to obtain the control signal at the kth moment; S3.5: The calculated control signal Convert it into the corresponding gas actuator opening adjustment instruction, and change the gas flow through the actuator; S3.6: Enter the next sampling cycle, add 1 to the k value, repeat steps S3.1-S3.5, and obtain the corrected gas flow value.

5. A method for optimizing temperature distribution control of a continuous equipment according to claim 4, characterized in that: The specific steps of S3.5 include: S3.51: Get the calculated control signal , and determine the range of the control signal and actuator opening range ,in, and Represent the minimum and maximum values ​​of the control signal, respectively. and Respectively represent the minimum and maximum values ​​of the actuator opening; S3.52: Establish the mapping relationship between the control signal and the actuator opening; S3.53: Design a linear transformation algorithm based on the mapping relationship between the control signal and the actuator opening, and Substitute it into the linear transformation algorithm to obtain the corresponding gas actuator opening adjustment instruction; S3.54: Convert the calculated actuator opening value y into the instruction format received by the actuator, and send the adjustment instruction to the gas actuator through the serial port. The actuator adjusts the opening according to the received instruction. The instruction format received by the executor is a byte sequence; S3.55: After the actuator is activated, the furnace temperature change is monitored in real time and the furnace temperature information is fed back to the control center. The control center adjusts the control signal again based on the difference between the fed-back furnace temperature and the target value.

6. A method for optimizing temperature distribution control of a continuous equipment according to claim 5, characterized in that: The specific process of S3.52 includes: During the operation of the device, starting from the minimum value of the control signal, a fixed step size is added each time , wait for the actuator to stabilize and then record the opening value; The iteration is repeated until the control signal reaches the maximum value, thereby obtaining multiple sets of control signal-actuator opening data pairs.

7. A method for optimizing temperature distribution control of a continuous equipment according to claim 6, characterized in that: The specific steps of step S4 include: S4.1: Obtain the corrected gas flow value from S3.6 and obtain the preset air-fuel ratio from the system parameter settings; S4.2: Based on the corrected gas flow rate and gas density The product of the gas mass per unit time is obtained. ; S4.3: Based on the quality of gas per unit time The product of the preset air-fuel ratio is the mass of the combustion air required per unit time. ; S4.4: Pass and the density of the combustion air The required combustion air flow rate is calculated by ; S4.5: The control center converts the calculated combustion air flow value into a corresponding control signal and sends the control signal to the combustion air actuator through the serial port. The actuator adjusts the opening according to the received signal to change the combustion air flow; S4.6: Real-time monitoring of the combustion conditions and temperature changes in the furnace to obtain the actual combustion air flow value and the heat supply status in the furnace; S4.7: Calculation and The difference between the two values ​​is used to obtain the combustion air flow control signal according to the improved PID control algorithm that integrates multiple parameters in S3.

4. ; S4.8: The control center controls the signal based on the combustion air flow rate Adjust the opening of the combustion air actuator.

8. A method for optimizing temperature distribution control of a continuous equipment according to claim 3, characterized in that: The specific steps of step S5 include: S5.1: When the furnace temperature of the equipment stabilizes, the online temperature measurement thermal imager starts working to collect temperature data at five points on the pipe body and transmits the collected temperature data from the five points to the control center via the wireless network; S5.2: After receiving the temperature data, the control center calculates the average value of points 1, 2, and 3 as the first average value Calculate the average of points 3, 4, and 5 as the second average ; S5.3: and and furnace temperature target value Perform difference calculation to obtain two temperature differences and ; S5.4: Based on the temperature difference and , adjust the left and right temperature control zones according to a preset adjustment strategy; the preset adjustment strategy includes: like , it means that the temperature of the left temperature control zone where points 1, 2, and 3 are located is too high, so the power of the left temperature control zone is reduced; like , it means that the temperature of the left temperature control zone where points 1, 2, and 3 are located is too low, so the temperature of the left temperature control zone is increased; like , it means that the temperature of the right temperature control zone where points 3, 4, and 5 are located is too high, so the power of the right temperature control zone is reduced; like , it means that the temperature of the right temperature control zone where points 3, 4, and 5 are located is too low, so the temperature of the right temperature control zone is increased.

9. A method for optimizing temperature distribution control of a continuous equipment according to claim 8, characterized in that: The flow, temperature and pressure data of the gas and combustion-supporting air collected in step S1 are collected by installing flow meters on the gas pipeline and the combustion-supporting air pipeline, and installing temperature measuring resistors and pressure transmitters behind the flow meters.

10. A continuous equipment temperature distribution optimization control system, which is used to implement a continuous equipment temperature distribution optimization control method according to any one of claims 1 to 9, characterized in that: include: Programmable control, gas electric actuator, combustion air electric actuator, thermocouple and thermal resistor, online temperature measurement thermal imager, gas and combustion air flow meter, gas and combustion air pressure transmitter, data acquisition and analysis system, cooling fan; The programmable control is configured by isolating an analog quantity to stably collect sensor signals. The heating section and the heat preservation section of the continuous equipment adjust the flow of gas and combustion air through the PID control actuator according to the difference between the set value and the actual temperature value. The fast cooling section and the slow cooling section of the continuous equipment adjust the speed of the cooling fan through the reaction of the PID regulation according to the difference between the set value and the actual temperature value. The gas electric actuator is used to control the flow of gas passing through the pipeline; The combustion-supporting air electric actuator is used to control the flow of the combustion-supporting air through the pipeline; The thermocouple and thermal resistor are used to detect the furnace temperature. The detection signal is connected to the control center through the transmitter. After the control center receives the furnace temperature signal, it compares it with the set value and makes adjustments; The online temperature measuring thermal imager is used to detect the temperature of the tube during annealing; The gas and combustion-supporting air flowmeters are used to detect the flow of gas in the pipeline; The gas and combustion air pressure transmitters are used to detect the pressure of the gas in the pipeline; The data acquisition and analysis system is used to collect equipment production process parameters, including furnace temperature, gas and combustion air pressure, flow data, and perform real-time online detection of furnace temperature and tube temperature; The cooling fan adjusts the atmosphere and temperature distribution in the equipment by sending cooling air into the equipment.

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