A continuous equipment temperature distribution optimization control method and system

Abstract

The application discloses a continuous equipment temperature distribution optimization control method and system, and belongs to the technical field of temperature control, and specifically comprises the following steps: real-time monitoring of equipment production process parameters and transmission to a control center; the control center uses a compensation algorithm based on an ideal gas state equation to correct the parameters, extracts furnace temperature data from the corrected parameters, and uses PID operation to calculate a control signal according to the deviation of the furnace temperature data from a preset furnace temperature target value, adjusts the opening degree of a coal gas actuator to obtain a corrected coal gas flow value; then, according to the value and a 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, an online temperature measurement thermal imager is used to collect the temperatures of five points on the pipe body, the average value is calculated and compared with the process requirement temperature, and then the left and right temperature adjustment zones are adjusted; the method can effectively improve the stability of equipment production and product quality.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of temperature control, in particular to a continuous equipment temperature distribution optimization control method and system. BACKGROUND

[0002] The furnace temperature control of the traditional equipment is to use PID control, through continuously measuring the furnace temperature and comparing with the set value, after the PID adjustment of the control center, the opening degree of the heating section and the holding section is adjusted through the control actuator, the speed of the cooling fan is adjusted in the rapid cooling section and the slow cooling section, and then the furnace temperature is adjusted to make it stable around the set value, which has several main shortcomings: 1) the collected furnace temperature is the furnace top temperature, not the actual annealing temperature of the pipe, which may lead to poor annealing effect; 2) the temperature adjustment is completed by the opening degree of the actuator, which cannot guarantee the best combustion ratio, resulting in energy waste; 3) there is no temperature and pressure detection on the pipeline, resulting in inaccurate measured flow value; 4) the production data of the equipment is manually copied once an hour, which is time-consuming and cannot guarantee the accuracy of the data, and is easy to lose; 5) the set temperature of each zone of the equipment needs to be adjusted manually according to the composition change of the pipe, and the adjustment has hysteresis. In this case, a continuous equipment temperature distribution optimization control method and system is developed, which can guarantee the accurate control of the temperature and the maximum utilization of the energy, and reduce the production cost. SUMMARY

[0003] In view of the deficiencies of the prior art, the application provides a continuous equipment temperature distribution optimization control method and system, which can effectively improve the stability of equipment production and product quality.

[0004] To achieve the above purpose, the application provides the following technical scheme:

[0005] A continuous equipment temperature distribution optimization control method, comprising:

[0006] 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 the coal gas and combustion air collected by the sensors on the coal gas pipeline and combustion air pipeline, and the 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 corrected equipment production process parameters;

[0008] Step S3: The control center extracts the corrected furnace temperature data from the corrected equipment production process parameters, calculates the control signal according to the deviation of the corrected furnace temperature data from the pre-set furnace temperature target value using PID operation, and adjusts the coal gas actuator opening degree according to the control signal, to obtain a corrected coal gas flow value;

[0009] Step S4: According to the corrected coal gas flow value and the pre-set air-fuel ratio, the required combustion-supporting air flow is calculated, and the control center adjusts the combustion-supporting air actuator according to the obtained combustion-supporting air flow to stabilize the heat supply in the furnace;

[0010] Step S5: When the equipment furnace temperature is stable, the temperature data of 5 points on the pipe body is collected by the online temperature measurement 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 the average value of points 3, 4 and 5 as the second average value, compares the first average value and the second average value with the process requirement temperature, and adjusts the left and right temperature adjustment zones according to the comparison result.

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

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

[0013] S2.2: According to the ideal gas state equation, a compensation algorithm is constructed , wherein P represents pressure, T represents Kelvin temperature, Q represents flow under actual measurement state, represents the compensated flow, represents the pressure under standard state, represents the temperature under standard state, represents the compensated pressure, represents the pressure under actual measurement, represents the reference temperature, represents the compensated temperature, represents the temperature under actual measurement, represents the temperature correction value obtained according to experimental data;

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

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

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

[0017] S3.2: Difference calculation is performed on the extracted corrected furnace temperature data and the pre-set furnace temperature target value to obtain a furnace temperature deviation value , wherein k represents the index of the time sampling point;

[0018] S3.3: Trend prediction is performed on the furnace temperature deviation value using a time series analysis algorithm to obtain a deviation trend prediction result.

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

[0020] S3.4: According to and the deviation trend prediction result, an improved PID control algorithm for fusing multiple parameters is used to calculate a control signal ; the improved PID control algorithm logic is:

[0021] The product of the proportional coefficient and the current time deviation is calculated to obtain a first part parameter;

[0022] The product of the integral coefficient and the cumulative result of multiplying all deviations from the initial time to the current time by the sampling period is calculated to obtain a second part parameter;

[0023] The product of the derivative coefficient and the result of subtracting the last time deviation from the current time deviation and then dividing by the sampling period is calculated to obtain a third part parameter;

[0024] The product of the thermal inertia compensation coefficient, the thermal inertia parameter, and the current time deviation rate is calculated to obtain a fourth part parameter;

[0025] The product of the ambient temperature compensation coefficient and the ambient temperature is calculated to obtain a fifth part parameter;

[0026] The product of the noise compensation coefficient and the current time system noise is calculated to obtain a sixth part parameter;

[0027] The sum of the first part parameter, the second part parameter, the third part parameter, the fourth part parameter, and the fifth part parameter is calculated, and then the sixth part parameter is subtracted, and multiplied by the corresponding adaptive weighting factor of each part parameter to obtain the control signal at the kth time;

[0028] S3.5: The calculated control signal converts the calculated control signal into corresponding gas actuator opening degree adjustment instruction, and changes the flow of the gas through the actuator;

[0029] S3.6: Entering the next sampling period, k value is added by 1, repeating steps S3.1-S3.5 to obtain the corrected gas flow value.

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

[0031] S3.51: Obtaining the calculated control signal and determining the range of the control signal and the range of the actuator opening degree , wherein, and respectively represent the minimum and maximum values of the control signal, and respectively represent the minimum and maximum values of the actuator opening degree;

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

[0033] S3.53: Designing a linear transformation algorithm according to the mapping relationship between the control signal and the actuator opening degree, and substituting into the linear transformation algorithm to obtain the corresponding gas actuator opening degree adjustment instruction;

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

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

[0036] S3.55: After the actuator acts, the change of the furnace temperature is monitored in real time, and the furnace temperature information is fed back to the control center, and the control center adjusts the control signal again according to the difference between the feedback 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, each time a fixed step is added, and the opening degree value is recorded after the actuator stabilizes;

[0039] Iterative repetition until the control signal reaches the maximum value, thereby obtaining a plurality of control signal-actuator opening degree data pairs.

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

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

[0042] S4.2: Obtain the mass of gas per unit time according to the product of the corrected gas flow value and the density of the gas ;

[0043] S4.3: Obtain the mass of required combustion air per unit time according to the product of the mass of gas per unit time and the preset air-fuel ratio ;

[0044] S4.4: Calculate the required combustion air flow by the ratio of and the density of the combustion air ;

[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 degree according to the received signal to change the combustion air flow;

[0046] S4.6: Real-time monitor the combustion situation and temperature change in the furnace to obtain the actual combustion air flow value and the heat supply state in the furnace;

[0047] S4.7: Calculate the difference between and , and obtain the combustion air flow control signal according to the improved PID control algorithm of S3.4 ;

[0048] S4.8: The control center adjusts the opening degree of the combustion air actuator according to the combustion air flow control signal .

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

[0050] S5.1: When the equipment furnace temperature is stable, the online temperature thermal imager starts working to collect temperature data of 5 points on the pipe body, and transmits the collected temperature data of the 5 points to the control center through the wireless network;

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

[0052] S5.3: Calculate the difference between and​​​ with the furnace temperature target value carrying out difference calculation to obtain two temperature differences and ;

[0053] S5.4: according to the temperature differences and , adjusting the left and right temperature adjustment zones according to a preset adjustment strategy; the preset adjustment strategy includes:

[0054] if , it indicates that the temperature of the left temperature adjustment zone where the 1, 2, 3 points are located is too high, so the power of the left temperature adjustment zone is reduced;

[0055] if , it indicates that the temperature of the left temperature adjustment zone where the 1, 2, 3 points are located is too low, so the temperature of the left temperature adjustment zone is increased;

[0056] if , it indicates that the temperature of the right temperature adjustment zone where the 3, 4, 5 points are located is too high, so the power of the right temperature adjustment zone is reduced;

[0057] if , it indicates that the temperature of the right temperature adjustment zone where the 3, 4, 5 points are located is too low, so the temperature of the right temperature adjustment zone is increased.

[0058] Specifically, the flow, temperature and pressure data of the coal gas and combustion air collected in the step S1 are collected by installing a flowmeter on the coal gas pipeline and the combustion air pipeline, and installing a temperature measuring thermistor and a pressure transmitter after the flowmeter.

[0059] A continuous equipment temperature distribution optimization control system, comprising: a programmable control, a coal gas electric actuator, a combustion air electric actuator, a thermocouple and a thermistor, an online temperature measuring thermal imager, a coal gas and combustion air flowmeter, a coal gas and combustion air pressure transmitter, a data acquisition and analysis system, and a cooling fan.

[0060] The programmable control stably collects the signals of the sensors through an analog quantity configuration isolator, and adjusts the flow of the coal gas and the combustion air in the heating section and the holding section of the continuous equipment through the PID control actuator according to the difference between the set value and the actual temperature value, and adjusts the speed of the cooling fan in the rapid cooling section and the slow cooling section of the continuous equipment through the reaction of the PID adjustment according to the difference between the set value and the actual temperature value.

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

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

[0063] The thermocouple and the thermal resistance are used for detecting the furnace temperature, and a detection signal is input into a control center through a transmitter.

[0064] The online temperature measurement thermal imager is used for detecting the temperature in the annealing of the pipe.

[0065] The coal gas and combustion air flow meter is used for detecting the flow of the gas in the pipeline.

[0066] The coal gas and combustion air pressure transmitter is used for detecting the pressure of the gas in the pipeline.

[0067] The data acquisition and analysis system is used for acquiring equipment production process parameters, including furnace temperature, coal gas and combustion air pressure and flow data, and performing real-time online detection on the furnace temperature and the pipe 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 application has the following beneficial effects:

[0070] 1. The present application provides a continuous equipment temperature distribution optimization control method, which can effectively improve the accuracy of parameter measurement by real-time monitoring of parameters such as the flow, temperature and pressure of coal gas and combustion air, and furnace temperature, and correcting by using a compensation algorithm based on the ideal gas state equation; combining PID operation to adjust the opening degree of the coal gas actuator, and adjusting the combustion air actuator according to the air-fuel ratio, to ensure the stability of the heat supply in the furnace, accurately control the furnace temperature, and improve the quality stability of the product in the annealing process, and reduce product defects caused by furnace temperature fluctuations.

[0071] 2. The present application provides a continuous equipment temperature distribution optimization control method, which collects temperature data of specific points of the pipe body by means of an online temperature measurement thermal imager after the furnace temperature is stable, compares the average value with the process required temperature, and then adjusts the left and right temperature adjustment zones accordingly. This fine temperature monitoring and regulation method can further optimize the heating uniformity of different parts of the pipe body, meet the strict requirements of complex processes on temperature distribution, enhance the adaptability and controllability of the equipment production process, and help reduce energy consumption and improve production efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0072] Figure 1 It is a schematic diagram of the continuous equipment temperature distribution optimization control method of the present application.

[0073] Figure 2 It is a principle flow chart of the continuous equipment temperature distribution optimization control method of the present application.

[0074] Figure 3The flow chart of the production process parameter correction of the device of the present application;

[0075] Figure 4 The flow chart of the control signal adjustment of the present application;

[0076] Figure 5 The flow chart of the temperature adjustment of the temperature adjustment zone of the present application;

[0077] Figure 6 The control system diagram of the heating section and the holding section in the temperature distribution optimization control system of the continuous device of the present application;

[0078] Figure 7 The control system diagram of the fast cooling section and the holding section in the temperature distribution optimization control system of the continuous device of the present application. DETAILED DESCRIPTION

[0079] Embodiment 1

[0080] Please refer to Figure 1 and Figure 2 An embodiment of the present application provides a continuous device temperature distribution optimization control method, wherein the device refers to an annealing furnace, and the method comprises steps S1-S5, including the following steps:

[0081] Step S1: Real-time monitoring of the device production process parameters and transmission to the control center; the device production process parameters include the flow, temperature and pressure data of the coal gas and combustion air collected by the coal 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 device production process parameters based on the compensation algorithm constructed by the ideal gas state equation to obtain the corrected device production process parameters;

[0083] Step S3: The control center extracts the corrected furnace temperature data from the corrected device production process parameters, calculates the control signal according to the deviation of the corrected furnace temperature data and the pre-set furnace temperature target value using PID operation, and adjusts the coal gas actuator opening degree according to the control signal to obtain the corrected coal gas flow value;

[0084] Step S4: According to the corrected coal gas flow value and the pre-set combustion ratio, the required combustion air flow is calculated, and the control center adjusts the combustion air actuator according to the obtained combustion air flow to stabilize the heat supply in the furnace;

[0085] Step S5: When the equipment furnace temperature is stable, the temperature data of 5 points of the tube body is collected by the online temperature measurement 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 the average value of points 3, 4 and 5 as the second average value. The first average value and the second average value are compared with the process required temperature, and the left and right temperature adjustment zones are adjusted according to the comparison result.

[0086] Embodiment 2

[0087] Please refer to Figure 3 , the specific steps of step S2 in the embodiment include:

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

[0089] S2.2: According to the ideal gas state equation , a compensation algorithm is constructed , wherein 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, Q represents the flow rate under the actual measurement state, represents the compensated flow rate, represents the pressure under the standard state, represents the temperature under the standard state, represents the compensated pressure, represents the pressure under the actual measurement, represents the reference temperature, represents the compensated temperature, represents the temperature under the actual measurement, represents the temperature correction value obtained according to the experimental data;

[0090] It should be noted that according to the ideal gas state equation , the density can be obtained , and the flow rate Q is inversely proportional to the density , that is , when the pressure and temperature change, the density will also change, so the compensated flow rate is related to the flow rate Q, the pressure P and the temperature T under the actual measurement state, that is , wherein N represents the molar mass, represents the direct proportional symbol, represents that the flow rate Q is directly proportional to the reciprocal of the density .

[0091] At the same time, it is assumed that there is a functional relationship between the pressure measurement value and the temperature, and when the temperature deviates from the reference temperature, the pressure measurement value will deviate. Therefore, 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 The temperature compensation of the pressure measurement eliminates or reduces the influence of temperature on pressure measurement, improving the accuracy of pressure measurement. Therefore, accurate pressure measurement is crucial for flow compensation and stable operation of the entire equipment control center, which helps to more accurately control gas supply and furnace temperature.

[0092] Finally, according to the principle of temperature measurement and the analysis of influencing factors in practical application, the temperature compensation formula is obtained. For example, the ambient temperature may have a heat conduction effect on the temperature sensor, causing a deviation in the measured value. Through experiments and analysis, the amount of deviation is determined , and the compensation formula is obtained By compensating the furnace temperature measurement value, the accuracy of temperature measurement is improved. Therefore, accurate furnace temperature data is the key to equipment control, which helps to achieve more accurate temperature control, improve product quality, and reduce product defects and energy waste caused by temperature errors.

[0093] For flow compensation, for example, in a large chemical production device, it is necessary to accurately control the flow of reaction gas to ensure the stable progress of chemical reactions and the consistency of product quality. The gas flow is measured by an orifice flowmeter. However, in actual production, the pressure and temperature of the gas will fluctuate greatly, affecting the accuracy of flow measurement. In this application, the measured value of the uncompensated flow is known , the pressure under standard conditions kPa, unit kPa, pressure , the temperature , unit K, Kelvin temperature, temperature under standard conditions , then according to the flow compensation formula of the present application , since the traditional method considers the flow to be , and the actual flow is calculated as , through the flow compensation formula of the present application, the influence of pressure and temperature on gas flow can be accurately considered, and a more realistic flow value can be provided, which is crucial for scenarios in chemical production that require high flow accuracy. It can effectively avoid problems such as reaction out of control and product quality fluctuations caused by inaccurate flow, which cannot be achieved by traditional uncompensated flow measurement technology.

[0094] For pressure compensation, for example, in oil and gas pipeline transportation, it is necessary to monitor the pressure in the pipeline in real time to ensure safe transportation. The pressure sensor is installed on the pipeline, but its measurement value will be affected by changes in ambient temperature. Assuming that the actual measured pressure value is known kPa, temperature , reference temperature , then according to the pressure compensation formula in the present application Since the traditional measurement can directly use 800 kPa as the pipeline pressure, and the actual pressure is found to be 873.72 kPa after pressure compensation, the pressure compensation formula of the application can effectively eliminate the influence of environmental temperature on pressure measurement, provide more accurate data for pipeline pressure monitoring, and has important significance for ensuring the safe and stable operation of the oil and gas pipeline. Compared with the traditional pressure measurement technology without considering the temperature influence, it can more accurately reflect the real pressure condition in the pipeline, avoid the safety hazards and economic losses caused by pressure misjudgment.

[0095] For temperature compensation, for example, in the semiconductor chip manufacturing process, accurate control of the furnace temperature directly affects the performance and yield of the chip. Thermocouples are used to measure the furnace temperature, but the measurement of the thermocouples is disturbed by factors such as installation position and furnace airflow, resulting in a deviation in the measured temperature. Assuming that the temperature correction value is determined through experiments and data analysis , according to the temperature compensation formula in the application , since the traditional measurement considers that the furnace temperature is 723 K, and the actual temperature is determined to be 728 K after compensation, the temperature compensation formula of the application can effectively correct the deviation in the thermocouple measurement process by introducing the temperature correction value, and provide more accurate furnace temperature data for semiconductor chip manufacturing. In the chip manufacturing industry with almost strict temperature accuracy requirements, the accuracy of temperature control is greatly improved, and the chip yield rate caused by temperature error is reduced. It is difficult for the traditional simple temperature measurement technology to achieve this.

[0096] S2.3: According to the constructed compensation algorithm, the obtained device production process parameters are compensated and calculated to obtain the compensated device production process parameters, and the compensated device production process parameters are output as the corrected device production process parameters, including the corrected flow, the corrected pressure, and the corrected temperature.

[0097] Embodiment 3

[0098] Please refer to Figure 4 , the specific steps of step S3 in the embodiment include:

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

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

[0101] S3.3: using time series analysis algorithm to the furnace temperature deviation value trend prediction, deviation trend prediction result is obtained;

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

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

[0104] S3.32: load pre-built autoregressive integrated moving average model, wherein the autoregressive integrated moving average model is prior art in the art, not the inventive scheme of the present application, and will not be described here;

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

[0106] S3.34: input the latest furnace temperature deviation value data into the trained autoregressive integrated moving average model, and the trained autoregressive integrated moving average model outputs the trend prediction result of the furnace temperature deviation value according to the input of the latest furnace temperature deviation value data;

[0107] S3.4: according to and deviation trend prediction result, using fusion multi-parameter improved PID control algorithm to calculate control signal ; the improved PID control algorithm logic is:

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

[0109] Calculate the product of the integral coefficient and the cumulative result of all deviations from the initial time to the current time multiplied by the sampling period, to obtain the second part parameter;

[0110] Calculate the product of the differential coefficient and the result of the current time deviation minus the last time deviation divided by the sampling period, to obtain the third part parameter;

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

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

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

[0114] The sum of the first partial parameter, the second partial parameter, the third partial parameter, the fourth partial parameter and the fifth partial parameter is calculated, and then the sixth partial parameter is subtracted, and the control signal at the k moment is obtained by multiplying the corresponding adaptive weighting factor of each partial parameter;

[0115] Further, the specific formula of the improved PID control algorithm fusing multiple parameters is: The control signal is calculated , wherein, represents an adaptive weighting factor, represents a proportional coefficient, represents an integral coefficient, represents a differential coefficient, represents a furnace temperature deviation value at the last sampling moment, represents a thermal inertia compensation coefficient, and H represents a thermal inertia parameter, represents an ambient temperature compensation coefficient, and E represents an ambient temperature influence parameter, represents a noise compensation coefficient, represents a system noise estimation value, and M represents a sampling period, represents a furnace temperature deviation value at the i sampling moment;

[0116] Further, in the present application, the Ziegler-Nichols method is adopted to adjust , and First, the critical gain and the critical period of the system are obtained through experiments, then the initial values of , , and are calculated according to the formula , and finally the fine adjustment is made according to the actual system operation.

[0117] The thermal inertia compensation coefficient and the thermal inertia parameter H are set by the experimental modeling method. In the laboratory environment or actual production, a series of temperature change experiments are carried out on the equipment, the response curves of the furnace temperature under different inputs such as coal gas flow changes are recorded, the thermal inertia characteristics of the equipment are obtained by analyzing these curves, the thermal inertia model is established by using the system identification method such as the least square method, and thus the thermal inertia parameter H is determined. The thermal inertia compensation coefficient can be adjusted through experiments, and the control effect of the system after adding the thermal inertia compensation term is observed to find the value that makes the system respond fastest and most stably.

[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 , considering the influence of ambient temperature on furnace temperature, the disturbance of ambient temperature change on control effect can be eliminated through ambient temperature compensation term, so that the system can maintain stable control performance at different ambient temperatures, finally, in order to reduce the influence of sensor measurement noise on control signal, noise compensation term , which can effectively suppress the influence of sensor measurement noise on control signal, reduce the control error caused by noise, and further improve the control precision.

[0122] For example, in an industrial device, the temperature in the furnace needs to be controlled to ensure the annealing quality of metal materials. The traditional PID controller often has poor control effect when dealing with complex working conditions, such as furnace thermal inertia, ambient temperature change and sensor noise, which will cause large furnace temperature fluctuation and affect product quality. However, the application uses to control, which can better adapt to these complex situations;

[0123] Suppose the traditional PID parameters , , , the thermal inertia compensation coefficient , the thermal inertia parameter H=20, the ambient temperature compensation coefficient , the noise compensation coefficient , the sampling period M=1s, the adaptive weighting parameter is set to 1.2 in the device startup stage and 1 in the stable running stage, the furnace temperature target value , the initial furnace temperature , the initial deviation , the ambient temperature influence parameter , the system noise estimated by Kalman filter , then in the control process simulation, since it is the initial moment, so , and , , substitute the formula in the application to calculate the control signal This control signal will be converted into the opening regulation instruction of the gas actuator to increase the gas flow, so that the furnace temperature rises rapidly. After running for a period of time, such as k=10, assuming that after 10 sampling periods, the furnace temperature , the deviation , at the same time, assuming , is the cumulative value calculated before, , at this time, the adaptive weighting parameter , substitute the formula to calculate the control signal At this time, the value of the control signal is reduced, and the opening of the gas actuator is reduced accordingly, so that the furnace temperature rising speed slows down and tends to 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 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;

[0133] The instruction format received by the actuator 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 opening range of the actuator is 0-100%, and the calculated opening is 50%. If it is represented by 16-bit unsigned integer in Modbus protocol, the corresponding numerical value is 65535 x 0.5 = 32767.5, rounded up to 32768;

[0136] (2) For 16-bit unsigned integer, it is divided into two 8-bit bytes, i.e. high 8 bits and low 8 bits. Taking 32768 as an example, its hexadecimal representation is 0x8000, so the high 8-bit byte is 0x80 and the low 8-bit byte is 0x00. In this way, a byte sequence [0x80, 0x00] containing two bytes is obtained, which is the byte sequence that the actuator can receive to represent 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 instruction to change the flow of gas. During the actuator action, the actual opening information of the actuator is obtained in real time through monitoring equipment to verify the adjustment effect.

[0140] S3.55: After the actuator action, monitor the change of the furnace temperature in real time and feed back the furnace temperature information to the control center. The control center adjusts the control signal again according to the difference between the feedback furnace temperature and the target value.

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

[0142] During the operation of the equipment, start from the minimum value of the control signal, and increase by a fixed step each time Wait for the actuator to stabilize and record the opening value;

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

[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 parameter settings of the system;

[0146] S4.2: Obtain the mass of gas per unit time according to the product of the corrected gas flow value and the density of the gas ;

[0147] S4.3: Obtain the mass of required combustion air per unit time according to the product of the mass of gas per unit time and the preset air-fuel ratio ;

[0148] S4.4: Calculate the required combustion air flow rate by the ratio of and the density of the combustion air ; ;

[0149] S4.5: The control center converts the calculated combustion air flow rate 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 degree according to the received signal to change the combustion air flow rate;

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

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

[0152] (2) Establish the relationship between the combustion air flow rate value and the actuator opening degree according to the characteristics of the combustion air system and experimental data, and determine the mapping relationship between the flow rate value and the control signal in combination with the control signal range of the actuator.

[0153] Wherein, the relationship between the combustion air flow rate value and the actuator opening degree is established by a fitting model, and the fitting model adopts a linear model, which is a prior art content in the field and is not the inventive scheme of the present application, and will not be described here.

[0154] Wherein, the mapping relationship between the flow rate value and the control signal is obtained by combining the flow rate-opening degree relationship and the control signal-opening degree relationship through a linear interpolation method, wherein the linear interpolation method is a prior art content in the field and is not the inventive scheme of the present application, and will not be described here.

[0155] ​​(3) According to 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 for communication with the combustion air actuator, 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) Refer to S3.54 to convert the control signal into a byte sequence;

[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 of combustion air;

[0160] (8) Real-time monitoring of the actual flow of combustion air is realized through sensors installed on the combustion air pipeline, such as flow meters, and the monitoring data is fed back to the control center, which compares the actual flow with the target flow and makes further adjustments according to the deviation.

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

[0162] S4.7: Calculate the difference between and , and obtain the combustion air flow control signal according to the improved PID control algorithm of S3.4 ;

[0163] S4.8: The control center adjusts the opening of the combustion air actuator according to the combustion air flow control signal .

[0164] Example 4

[0165] Please refer to Figure 5 , the specific steps of step S5 in this embodiment include:

[0166] S5.1: When the equipment furnace temperature is stable, the online temperature thermal imager starts working, and the temperature data of 5 points on the pipe body is collected and transmitted to the control center through wireless network;

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

[0168] S5.3: Calculate the difference between the furnace temperature target value and ; ; and ;

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

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

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

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

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

[0174] Embodiment 5

[0175] Please refer to Figure 6 and Figure 7 , in Figure 6 , BZ101 and BZ102 represent control nodes, TN430 represents an online temperature measurement thermal imager, and in Figure 7 , A represents an air outlet, another embodiment provided by the present application: a continuous equipment temperature distribution optimization control system, comprising: programmable control, gas electric actuator, combustion air electric actuator, thermocouple and thermal resistance, online temperature measurement thermal imager, gas and combustion air flow meter, gas and combustion air pressure transmitter, data acquisition and analysis system, cooling fan;

[0176] The programmable control stabilizes the signal of the sensor through the analog quantity configuration isolator, and adjusts the flow of the gas and combustion air in the heating section and the holding section of the continuous equipment according to the difference between the set value and the actual temperature value through the PID control actuator, so as to obtain the best combustion ratio and fully burn the gas, obtain the highest combustion value, and reduce the production cost. The speed of the cooling fan in the rapid cooling section and the slow cooling section of the continuous equipment is adjusted according to the reaction of the PID adjustment according to the difference between the set value and the actual temperature value, so as to adjust the furnace temperature;

[0177] Gas electric actuator for controlling the flow of gas in the pipeline;

[0178] Combustion air electric actuator for controlling the flow of combustion air in the pipeline;

[0179] Wherein, the gas electric actuator and the combustion air electric actuator receive 4-20ma signals from the control center to open the opening of the actuator, so as to increase or decrease the flow of gas in the pipeline, and the opening signal is also fed back to the control center through the 4-20ma signal.

[0180] Thermocouple and thermal resistance are used to detect the furnace temperature, and the detection signal is connected to the control center through the transmitter, and the control center compares the set value after receiving the furnace temperature signal to make adjustment;

[0181] Wherein, the thermal resistance is used to detect the temperature of the gas in the pipeline, because as the furnace temperature rises, the inlet pipeline will also be affected to a certain extent, and the temperature has a great influence on the flow calculation, the change of temperature will cause the change of physical properties such as gas density and viscosity, thereby affecting the measurement accuracy of the flowmeter, in order to reduce the influence of temperature on the flowmeter, the thermal resistance is added behind the flowmeter to detect the temperature in real time online, and the measurement result is corrected through temperature compensation algorithm, so as to ensure the measurement accuracy of the flowmeter at different temperatures, because only the flow is accurate, the correct combustion ratio can be ensured, and there is no temperature compensation in the traditional equipment, which may cause inaccurate flow.

[0182] Online temperature measurement thermal imager is used to detect the temperature in the annealing of the pipe;

[0183] It should be noted that because the thermocouple is installed on the top of the furnace, there is still a certain difference between it and the actual annealing area temperature, in order to ensure the temperature requirement of the nodular cast iron pipe annealing process, the online temperature measurement thermal imager is used to detect the temperature of the pipe in the annealing process, which can collect the temperature of five parts of the pipe to ensure that the temperature requirement of the annealing is reached, if the furnace temperature reaches the temperature requirement, but the surface temperature of the pipe does not meet the standard, the precise adjustment can be made according to the surface temperature of the pipe, wherein, the process of annealing is mainly to eliminate internal stress and improve the structure, so as to improve the mechanical properties and processing performance of the pipe.

[0184] Gas and combustion air flowmeter for detecting the flow of gas in the pipeline;

[0185] It should be noted that the temperature regulation of the traditional device is to control the combustion ratio by the opening degree of the actuator. This can meet the production requirements when the gas flow is stable. However, in the actual production process, the coal gas is often transported from the blast furnace. Thus, the actual gas flow in the actual production process is often unstable due to the influence of the blast furnace. Therefore, the gas flow may be large or small at the same opening degree, and the combustion air is unchanged. Thus, too little air may cause incomplete combustion, and some components in the coal gas cannot fully play a role, resulting in a decrease in the total heat value. Too much air may also dilute the coal gas, also resulting in a decrease in the total heat value. Therefore, the application increases the flow meter to control the opening degree of the actuator according to the actual flow of the gas.

[0186] A coal gas and combustion air pressure transmitter is used to detect the pressure of the gas in the pipeline.

[0187] It should be noted that because the pressure change has a great influence on the flow calculation, the flow meter can maintain high measurement accuracy within a certain pressure range. However, when the fluid pressure exceeds or is lower than the design range, the reading of the flow meter may deviate, because the density and viscosity of the fluid change with the change of the pressure, thereby affecting the measurement result of the flow meter. In order to reduce the influence of the pressure on the flow meter, the application increases the pressure transmitter behind the flow meter to detect the pressure in real time online, and corrects the measurement result through the pressure compensation algorithm, to ensure the measurement accuracy of the flow meter under different pressures, because only the accurate flow can ensure the correct combustion ratio.

[0188] A data acquisition and analysis system is used to acquire the production process parameters of the device, including the furnace temperature, the pressures of the coal gas and the combustion air, the flow data, and to detect the furnace temperature and the pipe temperature in real time online.

[0189] The data acquisition and analysis system acquires data once an hour and saves it to the SQL database, and produces a daily report every 24 hours. At the same time, the furnace temperature and the pipe temperature are detected in real time online. When an abnormality occurs, an alarm information is immediately generated. When the annealed pipe is abnormal, the production data of the day can be called out for analysis.

[0190] A cooling fan is used to send cooling air into the device to adjust the atmosphere and temperature distribution in the device.

[0191] The embodiments of the application are described above in combination with the drawings, but the application is not limited to the above specific embodiments. The above specific embodiments are only illustrative, but not limiting. Those skilled in the art can make changes, modifications, replacements and variations to the above embodiments without departing from the purpose of the application and the protected scope, which are all within the protection of the application.

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 five points on the tube body are collected using an online temperature measurement 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 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. 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; 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.

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 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.

4. A method for optimizing temperature distribution control of a continuous equipment according to claim 3, 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.

5. A method for optimizing temperature distribution control of a continuous equipment according to claim 4, 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.

6. A method for optimizing temperature distribution control of a continuous equipment according to claim 5, 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.

7. A method for optimizing temperature distribution control of a continuous equipment according to claim 6, 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.

8. 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 7, 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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