Oxidation kettle temperature self-adaptive control system and control method

Abstract

The embodiment of the invention provides an oxidation kettle temperature self-adaptive control system and a control method. The control system comprises a temperature detection module; the self-adaptive control algorithm module is used for dynamically adjusting the output of the heating or cooling device through data provided by the temperature detection module based on a self-adaptive control algorithm of a snow ablation algorithm; the feedback control module compares the output of the temperature detection module with a set temperature, the feedback control module adjusts control parameters and ensures that the temperature reaches a set value, the feedback control module adopts a double-closed-loop PID control system, and the double-closed-loop control structure comprises a self-adaptive PID controller of an outer loop and a rapid PID controller of an inner loop which are combined; and the man-machine interaction module allows an operator to set a target temperature and a control parameter, and displays a temperature change curve in real time. Through dynamic adjustment of PID controller parameters combined with real-time monitoring, intelligent analysis and an intelligent optimization algorithm and design of a double-closed-loop feedback system, quick response and stable control of temperature control are realized.

Description

Technical Field

[0001] This specification relates to the technical field of automatic control of chemical equipment, and specifically relates to an oxidation kettle temperature adaptive control system and a control method. Background Art

[0002] The oxidation kettle is one of the common equipment in modern chemical production, mainly used in industries such as petrochemical, rubber, pesticide, fuel, medicine, etc., and mainly completes the reactions of various chemical processes. Due to the wide variety of chemical reactions, large differences in operating conditions, and different states of material aggregation, extremely high requirements are imposed on the temperature control of the oxidation kettle. At present, the temperature control of most oxidation kettles mainly relies on traditional PID control algorithms. However, these methods have problems such as slow response speed and low control accuracy when dealing with complex and dynamic reaction environments, which to a certain extent affect the reaction efficiency and product quality. Summary of the Invention

[0003] In view of this, the embodiments of this specification provide an oxidation kettle temperature adaptive control system and a control method, which can dynamically adjust control parameters according to the real-time data of the temperature in the oxidation kettle to achieve a fast response for temperature control.

[0004] The embodiments of this specification provide the following technical solutions: An oxidation kettle temperature adaptive control system includes:

[0005] Temperature detection module: By installing a high-precision temperature sensor in the oxidation kettle, it is used to detect the change of the temperature in the kettle in real time to ensure the accuracy of the data;

[0006] Adaptive control algorithm module: An adaptive control algorithm based on the snow ablation algorithm, which dynamically adjusts the output of the heating or cooling device through the data provided by the temperature detection module, and automatically adjusts the control parameters according to the real-time temperature change and the set temperature difference to achieve a fast response;

[0007] Feedback control module: Compares the output of the temperature detection module with the set temperature, and adjusts the control parameters through the feedback control module to ensure that the temperature quickly reaches the set value. The feedback control module adopts a double-closed-loop PID control system. The double-closed-loop control structure combines an outer-loop adaptive PID controller and an inner-loop fast PID controller to improve the stability and response speed of the system;

[0008] Human-machine interaction module: Provides a user interface, allows operators to set the target temperature and control parameters, and displays the temperature change curve in real time, facilitating operators to adjust and monitor the parameters.

[0009] Preferably, the high-precision temperature sensor is a thermocouple sensor or a thermal resistance sensor.

[0010] Preferably, the human-machine interaction module includes VF monitoring configuration.

[0011] A method for self-adaptive control of the temperature of an oxidation kettle, applied to the control system described in any one of the above, includes:

[0012] Step 1: Initialize the proportional coefficient, integral coefficient, and differential coefficient of the PID according to the preset parameter range;

[0013] Step 2: Before or during the chemical reaction, collect the temperature data inside the oxidation kettle in real time at a preset time interval through the temperature sensor installed inside the oxidation kettle;

[0014] Step 3: Based on the obtained temperature data, calculate the difference between the temperature and the set value, and divide the temperature region into several temperature difference adjustment intervals according to the distribution of the temperature difference values;

[0015] Step 4: Analyze the outliers in the above temperature difference adjustment intervals, identify the abnormal intervals deviating from the normal cooling rate, and evaluate the impact of the PID parameters on the system using the interval outliers;

[0016] Step 5: The inner-loop PID controller receives the temperature feedback signal, calculates the error between the current temperature and the inner-loop set value, and outputs a control signal according to the error. The inner-loop PID controller is responsible for quickly responding to the change of the temperature inside the kettle, and adjusts the opening of the hot water or cold water valve by outputting an electric signal to achieve a quick adjustment of the temperature inside the kettle;

[0017] Step 6: Use the multi-strategy snow ablation optimization algorithm as an optimization tool, use ITAE as the objective function of the algorithm, and construct a new self-adaptive PID controller. Among them, using ITAE can well reflect the response speed and stability performance of the system, and its expression is The obtained self-adaptive PID controller dynamically adjusts the set value of the inner loop according to the overall temperature feedback of the system to optimize the response of the inner-loop controller. The outer-loop controller has self-adaptive ability and can automatically adjust the control parameters according to the error analysis;

[0018] Step 7: Repeat Steps 2 to 6, and continuously monitor and adjust the system temperature to ensure that the temperature inside the kettle is stable within the target range, and according to the PID parameter self-adaptive strategy in Step 6, adjust the control strategy in real time according to the changes in the oxidation kettle process to ensure the quick response and stability of the system;

[0019] Step 8: Record the system operation data and analyze the temperature control effect; according to the data analysis results, further optimize the controller parameter settings to improve the temperature control accuracy and response speed of the system;

[0020] Step 9: Design a human-machine interface through VF monitoring configuration, and the operator can set the target temperature and monitor the real-time temperature change through the user interface.

[0021] Preferably, in Step 2, the temperature data inside the kettle is collected in real time by a temperature sensor, and the actual data of the temperature inside the kettle is recorded as T a , and the data is transmitted to the inner-loop PID controller; in Steps 3 and 4, the target temperature T t and the actual temperature T a are compared, and the difference ΔT between them is recorded. This data is input into the inner-loop PID controller as a value to achieve a fast response.

[0022] Preferably, in Step 5, the inner-loop PID controller realizes the fast response and fine adjustment of the temperature inside the oxidation kettle to ensure that the temperature can quickly reach and maintain the set target value, and changes the magnitude of the output signal current to accurately control the valve opening of hot water or cold water to achieve a fast temperature response.

[0023] Preferably, in Step 6, the outer-loop adaptive PID controller receives the overall temperature data from multiple temperature sensors. The multiple sensors are distributed at different positions of the oxidation kettle to obtain comprehensive temperature information, and the collected temperature data is filtered and denoised to improve the accuracy and reliability of the data.

[0024] Preferably, in Step 7, the change of the temperature inside the oxidation kettle is detected in real time by a temperature detection device, and the obtained data is fed back to the PID controller. By continuously adjusting the control parameters, the temperature control strategy inside the oxidation kettle is optimized to improve the control accuracy and response speed of the system.

[0025] Preferably, in Step 5, the range of the output electrical signal is 4 - 20 mA.

[0026] Preferably, in Step 1, the operator inputs a reasonable target temperature range in advance according to the requirements as a reference basis.

[0027] Compared with the prior art, the beneficial effects that can be achieved by at least one of the above technical solutions adopted in the embodiments of this specification at least include:

[0028] The response speed and accuracy of the oxidation kettle temperature control are improved through the adaptive PID controller. The temperature adaptive control realizes the efficient control of complex environments, adapts to various operating conditions, and the dual-loop PID control system improves the response speed of the system and enhances the stability of the system. Brief Description of the Drawings

[0029] To more clearly illustrate the technical solutions of the embodiments of the present application, the accompanying drawings required for the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0030] Figure 1 is the control strategy diagram of the oxidation kettle temperature adaptive control system;

[0031] Figure 2 is the schematic diagram of the double closed-loop PID control system. Specific embodiments

[0032] The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0033] The following uses specific specific examples to illustrate the implementation manners of the present application. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in this specification. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. The present application can also be implemented or applied through other different specific implementation manners. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts belong to the scope of protection of the present application.

[0034] It should be noted that the following describes various aspects of the embodiments within the scope of the appended claims. It should be obvious that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is illustrative only. Based on the present application, those skilled in the art should understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspects described herein can be used to implement the device and / or practice the method. In addition, this device and / or this method can be implemented using other structures and / or functions in addition to one or more of the aspects described herein.

[0035] It also needs to be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present application in a schematic manner. The diagrams only show the components related to the present application, rather than being drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and ratio of each component in its actual implementation can be an arbitrary change, and the component layout type may also be more complex.

[0036] In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0037] The following describes the technical solutions provided by the embodiments of the present application in conjunction with the accompanying drawings.

[0038] As Figure 1 - Figure 2 shown, a temperature adaptive control system for an oxidation kettle includes:

[0039] Temperature detection module: By installing a high-precision temperature sensor in the oxidation kettle, it is used to detect the temperature change in the kettle in real time to ensure the accuracy of the data;

[0040] Adaptive control algorithm module: An adaptive control algorithm based on the snow melting algorithm, which dynamically adjusts the output of the heating or cooling device (adjusts the opening of the valve for regulating the cold water flow or hot water flow) through the data provided by the temperature detection module, and automatically adjusts the control parameters according to the real-time temperature change and the set temperature difference to achieve a fast response;

[0041] Feedback control module: Compares the output of the temperature detection module with the set temperature, and adjusts the control parameters through the feedback control module (the control parameters should include heating, cooling flow rates, and control time, etc.) to ensure that the temperature quickly reaches the set value. The feedback control module adopts a double closed-loop PID control system. The double closed-loop control structure combines an outer-loop adaptive PID controller and an inner-loop fast PID controller to improve the stability and response speed of the system;

[0042] Human-machine interaction module: Provides a user interface, allowing operators to set the target temperature and control parameters, and displays the temperature change curve in real time, facilitating operators to adjust and monitor the parameters.

[0043] A high-precision temperature sensor is used to monitor the temperature change in the oxidation kettle in real time, with a low error range. Through a multi-point distributed layout, different areas of the reaction kettle (such as the top, middle, and bottom) are covered to solve the local error problem of traditional single-point temperature measurement. The adaptive control algorithm module is based on an improved adaptive snow melting algorithm. According to the real-time temperature deviation and the deviation change rate, the PID parameters are dynamically optimized to solve the limitation of fixed traditional PID parameters. The outer-loop adaptive PID controller of the double closed-loop PID control system dynamically adjusts the parameters based on the snow melting algorithm to handle the macroscopic temperature trend, and the inner-loop fast PID controller uses high-frequency sampling to quickly respond to small temperature fluctuations.

[0044] In some embodiments, the high-precision temperature sensor is a thermocouple sensor or a thermal resistance sensor, and a suitable temperature sensor is selected according to the specific requirements of the system, such as a thermocouple, a thermistor, or an infrared temperature sensor.

[0045] In some embodiments, the human-machine interaction module includes VF monitoring configuration. Visualization of full-process parameters: The key parameter curves such as temperature, pressure, and liquid level are displayed in real time through a graphical interface, supporting multi-dimensional data overlay analysis for quick positioning of abnormal fluctuations. Dynamically adaptive interface: The monitoring interface is automatically switched according to the operation stage, with key parameters highlighted to reduce information overload.

[0046] Please refer to Figure 1 - Figure 2 , based on the same inventive concept, an embodiment of this specification provides a method for adaptively controlling the temperature of an oxidation kettle, which is applied to the control system described in any one of the above, and includes:

[0047] Step 1. While the user inputs a reasonable target temperature range according to their own needs in advance, calibrate the temperature sensor and other key sensors to ensure the accuracy of the measurement data, and initialize the proportional coefficient, integral coefficient, and derivative coefficient of the PID according to the preset parameter range.

[0048] Step 2. Before or during the chemical reaction, collect the temperature data inside the oxidation kettle in real time at a preset time interval through the temperature sensor installed inside the oxidation kettle, collect the temperature data inside the kettle in real time through the temperature sensor, and record the actual data of the temperature inside the kettle as T a , and transmit the data to the inner-loop PID controller;

[0049] Preferably, determine the optimal installation position of the sensor to ensure that it can accurately reflect the temperature change of the system;

[0050] Preferably, set a suitable data acquisition frequency according to the dynamic characteristics of the system to ensure that the temperature change can be captured in a timely manner;

[0051] Preferably, set a temperature alarm threshold to avoid safety accidents, so that the system can send an alarm signal in time when the temperature exceeds the safe range;

[0052] Preferably, filter the collected temperature data to remove noise and outliers and improve the accuracy of the data;

[0053] Preferably, dynamically adjust the boundary values between intervals according to historical data or preset rules to adapt to the changes in external environmental conditions at different time periods; for the data points falling within a specific interval, apply statistical methods (such as Z-Score test) or other advanced pattern recognition techniques to determine whether there is a significant deviation from the normal distribution; once any data beyond the expected range is found, immediately record it as an abnormal event and send an alarm notification to relevant personnel through a preset channel to take measures.

[0054] Step 3: Based on the obtained temperature data above, calculate the difference between the temperature and the set value, and divide the temperature region into several temperature difference adjustment intervals according to the distribution of the temperature difference values;

[0055] Step 4: Analyze the outliers in the above temperature difference adjustment intervals, identify the abnormal intervals deviating from the normal cooling rate, and evaluate the impact of the PID parameters on the system using the interval outliers;

[0056] In Steps 3 and 4, compare the target temperature T t and the actual temperature T a , and record the difference ΔT between the two. This data is input as a value into the inner-loop PID controller to achieve fast response;

[0057] Find the initial temperature T0 corresponding to the starting point t0 and the final temperature T n

[0058] corresponding to the ending point t n from the preprocessed dataset. Use the formula to calculate the average cooling rate R_base over the entire selected time period. Here, R represents the average cooling rate; T0 is the temperature value at the start time; T n is the temperature value at the end time; t0 and t n are the time points corresponding to these two temperature readings respectively.

[0059] Step 5: The inner-loop PID controller receives the temperature feedback signal, calculates the error between the current temperature and the inner-loop set value, and controls the output signal according to the error. The inner-loop PID controller is responsible for quickly responding to the temperature change in the kettle and adjusts the opening of the hot water or cold water valve by outputting an electrical signal to achieve a rapid adjustment of the temperature in the kettle;

[0060] In Step 5, the inner-loop PID controller achieves a fast response and fine adjustment of the temperature in the oxidation kettle to ensure that the temperature can quickly reach and maintain the set target value, and changes the magnitude of the output signal current to precisely control the opening of the hot water or cold water valve to achieve a fast temperature response.

[0061] Step 6: Use the multi-strategy snow ablation optimization algorithm as an optimization tool, use ITAE as the objective function of the algorithm, construct a new adaptive PID controller, design the PID controller with ITAE as the fitness function. Among them, using ITAE can well reflect the response speed and stability performance of the system, and its expression is The smaller the ITAE value, the faster the response speed and better the stability of the reaction system can be indicated; the obtained adaptive PID controller dynamically adjusts the set value of the inner loop according to the overall temperature feedback of the system to optimize the response of the inner loop controller, and the outer loop controller has the adaptive ability to automatically adjust the control parameters according to the error analysis;

[0062] In step 6, the outer loop adaptive PID controller receives the overall temperature data from multiple temperature sensors, and the multiple sensors are distributed at different positions of the oxidation kettle to obtain comprehensive temperature information, and perform filtering and denoising processing on the collected temperature data to improve the accuracy and reliability of the data.

[0063] It should be noted that the design of the inner loop PID controller:

[0064] 1. The error e(t) is defined as e(t) = T in -T act , where T act represents the actual temperature, and T in represents the inner loop PID temperature set value.

[0065] 2. The output of the PID controller is where k p represents the proportional gain, k i represents the integral gain, and k d represents the derivative gain.

[0066] Furthermore, in order to prevent the control output from being too large or too small, the output limit value is set to ensure that the control signal is within the range allowed by the device.

[0067] 3. Convert the comprehensive control output into a 4-20 mA electrical signal to control the power output of the heater or cooling system.

[0068] Furthermore, by adjusting the magnitude of the output current signal, the opening degree of the hot water or cold water valve is accurately controlled to achieve a rapid temperature response.

[0069] 4. The inner loop controller continuously monitors the temperature change to ensure that the temperature quickly reaches the set value and remains stable.

[0070] The design of the outer loop PID controller:

[0071] 1. Calculate the error between the overall temperature feedback and the outer loop set value as E(t), where E(t) = T out -T ave , T out represents the outer loop temperature set value, and T ave represents the average value of the overall temperature feedback in the kettle.

[0072] 2. The adaptive PID controller designed with the snow melting algorithm as an optimization tool and the ITAE as the objective function can achieve the adaptive adjustment of PID parameters, thus ensuring the rapid response of the system and the stability of the system.

[0073] 3. Calculate the new inner loop set value T in , and transmit it to the inner loop PID controller to achieve more precise temperature control.

[0074] 4. Continuously monitor the temperature response of the system, and further optimize the adaptive algorithm and control parameter settings according to the system response to improve the overall performance of the system.

[0075] Step 7: Repeat steps 2 to 6, continuously monitor and adjust the system temperature to ensure that the temperature in the kettle is stable within the target range, and according to the PID parameter adaptive strategy in step 6, adjust the control strategy in real time according to the changes in the oxidation kettle process to ensure the rapid response and stability of the system;

[0076] In step 7, the temperature change in the oxidation kettle is detected in real time through a temperature detection device, and the obtained data is fed back to the PID controller. By continuously adjusting the control parameters, the temperature control strategy in the oxidation kettle is optimized to improve the control accuracy and response speed of the system.

[0077] Step 8: Record the system operation data and analyze the temperature control effect; according to the data analysis results, further optimize the controller parameter settings to improve the temperature control accuracy and response speed of the system. And regularly monitor the key performance indicators of the system, such as response time, steady-state error, overshoot, and energy consumption efficiency.

[0078] Step 9: Design a human-machine interaction interface through VF monitoring configuration, and the operator can set the target temperature and monitor the temperature change in real time through the user interface.

[0079] The design of the human-machine interaction interface includes the following points:

[0080] (1) Provide a real-time monitoring interface for the system operation status, including temperature curve, control parameters, and key performance indicators.

[0081] (2) Design an intuitive parameter adjustment interface that allows users to manually adjust the PID control parameters and set values as needed.

[0082] (3) Integrate the fault detection and alarm function to promptly prompt the user of the abnormal situation of the system and provide fault handling suggestions.

[0083] (4) Provide the function of querying and analyzing historical data to support users for in-depth data analysis and performance evaluation

[0084] For the various embodiments in this specification, the similar parts can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the method embodiments described later, since they correspond to the systems, the descriptions are relatively simple. For the relevant parts, reference can be made to the corresponding parts of the system embodiments.

[0085] As described above, the above are only the specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed by the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An oxidation kettle temperature adaptive control system, characterized in that, Including: Temperature detection module: By installing a high-precision temperature sensor in the oxidation kettle, it is used to detect the change of the temperature in the kettle in real time to ensure the accuracy of the data; Adaptive control algorithm module: An adaptive control algorithm based on the snow ablation algorithm, which dynamically adjusts the output of the heating or cooling device through the data provided by the temperature detection module. According to the real-time temperature change and the difference between the set temperature, it automatically adjusts the control parameters to achieve a quick response; Feedback control module: Compares the output of the temperature detection module with the set temperature, and adjusts the control parameters through the feedback control module to ensure that the temperature quickly reaches the set value. The feedback control module adopts a double-loop PID control system. The double-loop control structure combines an adaptive PID controller in the outer loop and a fast PID controller in the inner loop to improve the stability and response speed of the system; Human-machine interaction module: Provides a user interface, allowing operators to set the target temperature and control parameters, and displays the temperature change curve in real time, facilitating operators to adjust and monitor the parameters.

2. The temperature adaptive control system of the oxidation kettle according to claim 1, characterized in that The high-precision temperature sensor is a thermocouple sensor or a thermal resistance sensor.

3. The oxidation kettle temperature adaptive control system according to claim 2, wherein The human-machine exchange module includes a VF monitoring configuration.

4. A temperature self - adaptive control method for an oxidation kettle, characterized in that, Applied to the control system described in any one of claims 1-3 above, including: Step 1: Initialize the proportional coefficient, integral coefficient, and differential coefficient of the PID according to the preset parameter range; Step 2: Before or during the chemical reaction, collect the temperature data in the kettle in real time at a preset time interval through the temperature sensor installed inside the oxidation kettle; Step 3: Based on the obtained temperature data above, calculate the difference between the temperature and the set value, and divide the temperature region into several temperature difference adjustment intervals according to the distribution of the temperature difference values; Step 4: Analyze the outliers in the above temperature difference adjustment intervals, identify the abnormal intervals deviating from the normal cooling rate, and evaluate the impact of the PID parameters on the system using the interval outliers; Step 5: The inner-loop PID controller receives the temperature feedback signal, calculates the error between the current temperature and the inner-loop set value, and outputs a control signal according to the error. The inner-loop PID controller is responsible for quickly responding to the change of the temperature in the kettle, and adjusts the opening of the hot water or cold water valve by outputting an electrical signal to achieve a quick adjustment of the temperature in the kettle; Step 6: Use the multi-strategy snow melting optimization algorithm as an optimization tool, use ITAE as the objective function of the algorithm, and construct a new adaptive PID controller. Using ITAE can well reflect the response speed and stability performance of the system, and its expression is The obtained adaptive PID controller dynamically adjusts the set value of the inner loop according to the overall temperature feedback of the system to optimize the response of the inner loop controller. The outer loop controller has an adaptive ability and can automatically adjust the control parameters according to error analysis; Step 7: Repeat steps 2 to 6, and continuously monitor and adjust the system temperature to ensure that the temperature in the kettle is stable within the target range, and according to the PID parameter adaptive strategy in step 6, adjust the control strategy in real time according to the change of the oxidation kettle process to ensure the quick response and stability of the system; Step 8: Record the system operation data and analyze the temperature control effect; According to the data analysis results, further optimize the controller parameter settings to improve the temperature control accuracy and response speed of the system; Step 9: Design a human-machine exchange interface through the VF monitoring configuration, and operators can set the target temperature and monitor the temperature change in real time through the user interface.

5. The oxidation kettle temperature adaptive control method according to claim 4, characterized in that, In Step 2, the temperature data inside the kettle is collected in real time through a temperature sensor, and the actual data of the temperature inside the kettle is recorded as T a , and the data is transmitted to the inner-loop PID controller; in Steps 3 and 4, the target temperature T t and the actual temperature T a are compared, and the difference ΔT between the two is recorded. This data is input as a value into the inner-loop PID controller to achieve a fast response.

6. The oxidation kettle temperature adaptive control method according to claim 5, characterized in that In step 5, the inner loop PID controller is to achieve rapid response and fine adjustment of the temperature in the oxidation kettle, so as to ensure that the temperature can quickly reach and maintain the set target value, and change the magnitude of the output signal current to accurately control the valve opening of hot water or cold water, so as to achieve rapid temperature response.

7. The oxidation kettle temperature adaptive control method according to claim 6, characterized in that In step 6, the outer loop adaptive PID controller receives the overall temperature data from multiple temperature sensors, and the multiple sensors are distributed at different positions of the oxidation kettle to obtain comprehensive temperature information, and filters and denoises the collected temperature data to improve the accuracy and reliability of the data.

8. The oxidation kettle temperature adaptive control method according to claim 7, wherein In step 7, through the temperature detection device, the change of the temperature in the oxidation kettle is detected in real time, and the obtained data is fed back to the PID controller. By continuously adjusting the control parameters, the temperature control strategy in the oxidation kettle is optimized, and the control accuracy and response speed of the system are improved.

9. The method for adaptively controlling the temperature of the oxidation kettle according to any one of claims 4-8, characterized in that, In step 5, the output electrical signal range is 4 - 20 mA.

10. The oxidation kettle temperature adaptive control method according to any one of claims 4-8, characterized in that In step 1, the operator inputs a reasonable target temperature range in advance according to the requirements as a reference basis.

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