A methanol synthesis catalyst steam temperature and pressure coordinated control method and system

Abstract

The present application relates to the technical field of chemical process control, and discloses a kind of methanol synthesis catalyst steam temperature-pressure synergic control method and system, including obtaining bed temperature, shell side pressure, steam flow and original condensate level data, calculate dynamic excitation index;According to the shell side pressure, calculate saturated condensation latent heat value and temperature-pressure nonlinear partial derivative;Combining phase change heat flux, calculate effective phase change heat transfer area proportionality coefficient;Calculate time-varying apparent heat capacity, and external standard temperature rising rate instruction is decomposed into shell side pressure, condensate level and steam flow instruction;Calculate the increment of regulating valve basic opening, utilize temperature-pressure nonlinear partial derivative to execute safety cut-off processing and output electric signal.The present application decouples multi-dimensional control instruction by online estimation of time-varying apparent heat capacity, combines with liquid level expansion compensation to restore effective heat transfer area, utilizes thermodynamic state constraint to limit excessive steam of valve, solves the problem of strong coupling of multi-dimensional physical quantity, avoids overpressure, improves control precision and guarantees equipment safety.

Description

Technical Field

[0001] This invention relates to the field of chemical process control technology, specifically to a method and system for coordinated temperature and pressure control of vapor heating in methanol synthesis catalysts. Background Technology

[0002] Methanol synthesis reactions are typically carried out in tubular reactors, and newly loaded catalysts require precise temperature reduction treatment before being put into operation. In industrial settings, steam is often introduced into the shell side to heat the catalyst bed. During the steam heating process, complex phase change heat transfer processes and thermodynamic evolution mechanisms occur inside the reactor, and existing conventional control schemes are difficult to meet the high-precision process requirements.

[0003] Existing control strategies often employ a single temperature control loop to directly regulate the steam inlet valve. This approach ignores the dynamic changes in the thermodynamic properties of the catalyst at different heating stages, and the system cannot obtain real-time information on the actual heat capacity of the catalyst bed. Furthermore, there is a strong coupling relationship between multiple physical quantities such as bed temperature, shell-side pressure, and steam flow rate. Single-dimensional regulation cannot adapt to complex operating conditions, making it difficult to accurately match the system's heating rate to the process-set control commands. This can easily lead to catalyst damage due to uneven local heating.

[0004] In the calculation of system energy balance, the condensation and heat release of steam in the shell side will cause boiling, and internal bubbles will cause significant physical expansion of the condensate. Existing measurement and control systems usually directly use the liquid level data transmitted from field instruments, failing to identify and deduct the expansion error caused by boiling on the condenser side. The liquid level data containing false components cannot accurately reflect the true height of the heat exchange tubes actually submerged in liquid water, causing the control system to be unable to accurately restore the effective physical surface area actually involved in heat release, resulting in the final calculated energy balance parameters deviating from the actual operating conditions.

[0005] The thermodynamic state changes of steam exhibit nonlinear characteristics. Existing control algorithms for regulating valves lack constraint mechanisms for the system's thermodynamic limits when outputting action commands. When faced with large control deviations, the system is prone to outputting excessive opening commands to the end actuators, causing an excessive influx of steam into the reactor shell side. The lack of control logic for safe shut-off actions can easily lead to saturation oscillations in the steam inlet regulating valve, causing a rapid increase in shell side pressure and triggering a system overpressure hazard, thus affecting the operational safety of the entire heating process. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a method and system for coordinated temperature and pressure control of vapor heating in methanol synthesis catalysts. This method solves the problems of low control accuracy caused by strong coupling of multidimensional physical quantities in existing heating control, distortion in heat transfer area calculation caused by liquid level boiling expansion, and easy overpressure and oscillation caused by lack of thermodynamic boundary constraints.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The first aspect of this invention provides a method for coordinated temperature and pressure control of vapor rise in methanol synthesis catalyst, comprising the following steps:

[0009] Acquire bed temperature, shell pressure, steam flow rate and raw condensate level data, and calculate dynamic excitation index;

[0010] Calculate the saturated latent heat of condensation and the partial derivative of the temperature-pressure nonlinearity based on the shell-side pressure; obtain the phase change heat flux data of the previous control cycle, and calculate the effective phase change heat transfer area ratio coefficient based on the phase change heat flux data and the original condensate level data;

[0011] The time-varying apparent heat capacity is calculated by combining the bed temperature, the dynamic excitation index, the saturated latent heat of condensation, and the effective phase change heat transfer area ratio coefficient.

[0012] The target latent heat flux is obtained based on the external standard heating rate command and the time-varying apparent heat capacity. The target latent heat flux is decomposed into the target shell-side pressure command, the target condensate level command, and the steam inlet flow rate command.

[0013] The basic opening increment of the steam inlet pneumatic control valve is calculated based on the steam inlet flow command. The basic opening increment is then subjected to a safety cutoff process using the temperature and pressure nonlinear partial derivative. An electrical signal is output to the steam inlet pneumatic control valve. An electrical signal is also output to the shell-side back pressure pneumatic control valve based on the target shell-side pressure command. Finally, an electrical signal is output to the condensate discharge pneumatic control valve based on the target condensate level command.

[0014] Furthermore, the acquisition of bed temperature, shell-side pressure, steam flow rate, and initial condensate level data, and the calculation of the dynamic excitation index, includes:

[0015] The bed temperature is obtained by acquiring measured values ​​from thermocouples and calculating the average value; the shell pressure is obtained from an absolute pressure transmitter; the steam flow rate is obtained from a flow meter; and the raw condensate level data is obtained from a differential pressure level transmitter.

[0016] The bed temperature and the steam flow rate are subjected to low-pass filtering to obtain the effective values ​​of the bed temperature and the steam flow rate, respectively.

[0017] Calculate the absolute difference between the effective value of the bed temperature at the current discrete sampling time and the effective value of the bed temperature at the previous discrete sampling time to obtain the change in bed temperature;

[0018] Calculate the absolute difference between the effective value of the steam inlet flow rate at the current discrete sampling time and the effective value of the steam inlet flow rate at the previous discrete sampling time to obtain the change in steam inlet flow rate;

[0019] The dynamic excitation index is obtained by normalizing and weighting the changes in bed temperature and the changes in steam flow rate.

[0020] Further, the saturated latent heat of condensation and the thermo-baric nonlinear partial derivatives are calculated based on the shell-side pressure, including:

[0021] Extract the saturated absolute temperature, saturated water vapor specific volume, saturated liquid water specific volume, saturated water vapor specific enthalpy, and saturated liquid water specific enthalpy corresponding to the shell-side pressure;

[0022] The saturated latent heat of condensation is obtained by subtracting the saturated water vapor specific enthalpy and the saturated liquid water specific enthalpy.

[0023] The saturated absolute temperature is multiplied by the difference between the saturated water vapor specific volume and the saturated liquid water specific volume, and the result of the multiplication is divided by the saturated latent heat of condensation to obtain the nonlinear partial derivative of temperature and pressure.

[0024] Further, the step of acquiring the phase change heat flux data of the previous control cycle, and calculating the effective phase change heat transfer area ratio coefficient based on the phase change heat flux data and the original condensate level data, includes:

[0025] The phase change heat flux data is obtained by multiplying the effective value of the inlet steam flow rate of the previous control cycle with the value of the saturated latent heat of condensation.

[0026] Calculate the liquid level expansion based on the phase change heat flux data;

[0027] The original condensate level data at the current discrete sampling time is subjected to low-pass filtering to obtain the original effective value of the condensate level;

[0028] The effective static liquid level is obtained by subtracting the liquid level expansion from the original effective value of the condensate level.

[0029] Substituting the effective static liquid level into the tube-shell geometric mapping function, the ratio of the effective surface area of ​​the unsubmerged tube section to the total surface area of ​​the tube-shell is calculated, thus obtaining the effective phase change heat transfer area ratio coefficient.

[0030] Furthermore, by combining the bed temperature, the dynamic excitation index, the saturated latent heat of condensation, and the effective phase change heat transfer area ratio coefficient, the time-varying apparent heat capacity is calculated, including:

[0031] The dynamic forgetting factor is determined based on the dynamic incentive index.

[0032] The effective input heat power is obtained by multiplying the effective value of the inlet steam flow rate, the saturated latent heat of condensation, and the effective phase change heat transfer area ratio coefficient.

[0033] The temperature difference is calculated by comparing the effective value of the bed temperature at the current discrete sampling time with the effective value of the bed temperature at the previous discrete sampling time.

[0034] Using the effective input thermal power as the excitation input vector and the temperature difference as the observation output vector, the preliminary apparent heat capacity estimate is calculated by using the recursive least squares method in combination with the dynamic forgetting factor.

[0035] Numerical clamping processing is performed on the preliminary apparent heat capacity estimate based on the predetermined lower and upper limits of apparent heat capacity, and the time-varying apparent heat capacity is output.

[0036] Further, the dynamic forgetting factor is determined based on the dynamic stimulus index, including:

[0037] By combining a preset basic forgetting factor and a preset forgetting gain coefficient, a nonlinear exponential decay function is used to map the dynamic excitation exponent to the dynamic forgetting factor.

[0038] Further, the step of deriving the target latent heat flux based on the external standard heating rate command and the time-varying apparent heat capacity, and decomposing the target latent heat flux into a target shell-side pressure command, a target condensate level command, and an inlet steam flow rate command, includes:

[0039] The target latent heat flux is obtained by multiplying the external standard heating rate command with the time-varying apparent heat capacity.

[0040] The product of the target latent heat flux, the saturated condensing latent heat value, and the effective phase change heat transfer area ratio coefficient is divided to obtain the steam inlet flow command.

[0041] The target shell-side pressure command is generated by performing integral calculations using the aforementioned nonlinear partial derivatives of temperature and pressure.

[0042] The target condensate level command is generated by multiplying the pre-stored effective total height parameter of the heat exchange tubes with the liquid level safety margin ratio.

[0043] Further, the basic opening increment of the steam inlet pneumatic regulating valve is calculated based on the steam inlet flow command, including:

[0044] The difference between the steam inlet flow command and the effective value of the steam inlet flow is calculated to obtain the steam inlet flow deviation;

[0045] The proportional-integral-differential algorithm is used to calculate the steam inlet flow deviation, thereby obtaining the basic opening increment of the steam inlet pneumatic regulating valve.

[0046] Furthermore, by applying a safety cutoff to the basic opening increment using the aforementioned temperature-pressure nonlinear partial derivative, an electrical signal is output to the steam inlet pneumatic regulating valve, including:

[0047] The dynamic maximum opening increment threshold is calculated by multiplying the temperature-pressure nonlinear partial derivative with the partial derivative gain conversion coefficient.

[0048] The basic opening increment of the steam inlet pneumatic regulating valve is compared with the dynamic maximum opening increment threshold.

[0049] When the basic opening increment of the steam inlet pneumatic regulating valve exceeds the dynamic maximum opening increment threshold, the dynamic maximum opening increment threshold is taken as the final opening increment.

[0050] The final valve opening command is obtained by superimposing the final opening increment with the actual opening command of the previous control cycle.

[0051] The final valve opening command is converted into an electrical signal and output to the steam inlet pneumatic regulating valve.

[0052] A second aspect of this invention provides a temperature and pressure coordinated control system for vapor heating of a methanol synthesis catalyst, applied to the temperature and pressure coordinated control method for vapor heating of a methanol synthesis catalyst described in the first aspect of this invention, comprising:

[0053] The feature extraction module is used to acquire bed temperature, shell pressure, steam flow rate and raw condensate level data, and calculate the dynamic excitation index;

[0054] The state calculation module is used to calculate the saturated latent heat of condensation and the thermo-baric nonlinear partial derivatives based on the shell-side pressure.

[0055] The area observation module is used to acquire phase change heat flux data from the previous control cycle and calculate the effective phase change heat transfer area ratio coefficient based on the phase change heat flux data and the original condensate level data.

[0056] The heat capacity estimation module is used to calculate the time-varying apparent heat capacity by combining the bed temperature, the dynamic excitation index, the saturated latent heat of condensation, and the effective phase change heat transfer area ratio coefficient.

[0057] The decoupled calculation module is used to obtain the target latent heat flux based on the external standard heating rate command and the time-varying apparent heat capacity, and decompose the target latent heat flux into the target shell-side pressure command, the target condensate level command and the steam inlet flow command.

[0058] The constraint drive module is used to calculate the basic opening increment of the steam inlet pneumatic regulating valve according to the steam inlet flow command, perform safety truncation processing on the basic opening increment using the temperature and pressure nonlinear partial derivative, output an electrical signal to the steam inlet pneumatic regulating valve, output an electrical signal to the shell-side back pressure pneumatic regulating valve according to the target shell-side pressure command, and output an electrical signal to the condensate discharge pneumatic regulating valve according to the target condensate level command.

[0059] This invention provides a method and system for coordinated temperature and pressure control of vapor heating in methanol synthesis catalysts, which has the following beneficial effects:

[0060] This invention calculates the time-varying apparent heat capacity by combining bed temperature, dynamic excitation index, saturated latent heat of condensation, and effective phase change heat transfer area ratio coefficient. Based on the external standard heating rate command and the time-varying apparent heat capacity, the target latent heat flux is obtained. The target latent heat flux is decomposed into the target shell-side pressure command, the target condensate level command, and the steam inlet flow command. The temperature and pressure nonlinear partial derivatives are used to perform a safety cut-off process on the basic opening increment of the steam inlet pneumatic regulating valve to complete temperature and pressure coordinated control. This can adapt to the dynamic changes in the thermodynamic properties of the catalyst during the heating process, solve the problem of strong coupling of multidimensional physical quantities in traditional single-loop control, improve the control accuracy of the system heating rate, and prevent the catalyst from being damaged due to uneven heating.

[0061] This invention calculates the liquid level expansion by acquiring the phase change heat flux data of the previous control cycle, subtracts the expansion component caused by steam condensation and boiling from the filtered original condensate level, obtains the effective static liquid level, and calculates the effective phase change heat transfer area ratio coefficient. This eliminates the liquid level measurement error caused by the boiling phenomenon on the condensation side, accurately restores the actual physical surface area of ​​the heat exchange tubes that participate in heat release, and provides reliable basic parameters for the energy balance calculation of the control system.

[0062] This invention utilizes the steam state equation to calculate and extract the nonlinear partial derivatives of temperature and pressure, converts them into the dynamic maximum opening increment threshold of the steam inlet valve, performs safety cut-off processing on the basic opening increment, and directly converts the current thermodynamic limit of the system into the action constraint of the actuator. This limits excessive steam intake at the end of the control loop, avoids saturation oscillation of the regulating valve and the danger of system overpressure, and ensures the safe operation of equipment in the heating process. Attached Figure Description

[0063] Figure 1 This is a structural block diagram of a temperature and pressure coordinated control system for vapor heating of methanol synthesis catalyst according to the present invention;

[0064] Figure 2 This is an overall flowchart of a method for coordinated temperature and pressure control of vapor heating in methanol synthesis catalyst according to the present invention;

[0065] Figure 3This is a flowchart illustrating the steps of acquiring real-time on-site data and calculating the dynamic excitation index in this invention.

[0066] Figure 4 This is a flowchart of the steps in this invention to convert thermodynamic parameters and calculate the nonlinear partial derivatives of temperature and pressure;

[0067] Figure 5 This is a flowchart of the steps in the present invention to eliminate liquid level measurement deviation and calculate the effective phase change heat transfer area ratio coefficient;

[0068] Figure 6 This invention provides a flowchart for the step of preventing parameter identification algorithm divergence and calculating the time-varying apparent heat capacity.

[0069] Figure 7 This is a flowchart illustrating the steps of deriving the core energy requirements and converting them into multi-dimensional physical control commands in this invention.

[0070] Figure 8 This is a flowchart of the steps in this invention to calculate the basic opening increment and execute the safety truncation output command;

[0071] Figure 9 This is a comparison chart of the temperature tracking effect of the methanol synthesis catalyst of the present invention.

[0072] Figure 10 This diagram illustrates the control effect of the constraint drive module of the present invention on the opening degree of the regulating valve by safely cutting off the valve opening. Detailed Implementation

[0073] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0074] See Figure 1 This invention provides a temperature and pressure coordinated control system for vapor heating of methanol synthesis catalyst, including a field instrument layer and an industrial control layer.

[0075] The field instrumentation layer is located within the methanol synthesis reactor and its auxiliary pipelines, including multi-point thermocouples, absolute pressure transmitters, flow meters, temperature transmitters, differential pressure level transmitters, and pneumatic control valves. Multi-point thermocouples are installed inside the catalyst bed in the reactor tubes. The absolute pressure transmitter is located at the top of the reactor shell side. Flow meters and temperature transmitters are located on the steam inlet line. The differential pressure level transmitter is located on the reactor shell side wall. Pneumatic control valves include a steam inlet pneumatic control valve, a shell-side back pressure pneumatic control valve, and a condensate discharge pneumatic control valve.

[0076] The industrial control layer comprises a distributed control system or an advanced process control workstation. It includes an industrial master controller and computer-readable storage media. The field instrumentation layer communicates with the industrial master controller via analog input channels. The industrial master controller communicates with pneumatic control valves in the field instrumentation layer via analog output channels.

[0077] The computer-readable storage medium stores program instructions. When the processor of the industrial main controller executes the program instructions, it instantiates multiple functional modules. These functional modules include a feature extraction module, a state calculation module, an area observation module, a heat capacity estimation module, a decoupling calculation module, and a constraint driving module.

[0078] The feature extraction module is communicatively connected to both the field instrumentation layer and the state calculation module. It synchronously acquires bed temperature, shell pressure, steam flow rate, and raw condensate level data for the current control cycle via analog input channels. This data is then processed using a first-order low-pass filter to extract changes in bed temperature and steam flow rate, and the dynamic excitation index is calculated. The dynamic excitation index characterizes the current operating condition of the system.

[0079] The state calculation module is connected to the feature extraction module. The state calculation module receives shell-side pressure data, calls the industrial steam state equation to calculate the saturated latent heat of condensation corresponding to the shell-side pressure, and calculates the thermo-baric nonlinear partial derivatives according to the Clausius-Clapeyron equation.

[0080] The area observation module is connected to the feature extraction module. The area observation module is used to acquire the phase change heat flux data of the previous control cycle, establish a boiling expansion compensation model based on the phase change heat flux data to calculate the liquid level expansion, subtract the liquid level expansion from the original condensate level to obtain the effective static liquid level, and substitute the effective static liquid level into the tube geometric mapping function to calculate the effective phase change heat transfer area ratio coefficient.

[0081] The heat capacity estimation module is connected to the feature extraction module, the state calculation module, and the area observation module. The heat capacity estimation module receives the dynamic excitation index, the saturated latent heat of condensation, and the effective phase change heat transfer area ratio coefficient. Based on the dynamic excitation index, it adjusts the internal dynamic forgetting factor, calculates the time-varying apparent heat capacity of the reactor catalyst bed using the recursive least squares algorithm, and performs numerical clamping processing on the time-varying apparent heat capacity according to preset physical boundary parameters.

[0082] The decoupled calculation module is connected to the heat capacity estimation module. The decoupled calculation module is used to obtain the external standard heating rate command issued by the process system, multiply the external standard heating rate command with the time-varying apparent heat capacity to calculate the target latent heat flux, and decompose the target latent heat flux into the target shell-side pressure command, the target condensate level command, and the steam inlet flow rate command.

[0083] The constraint drive module is connected to the decoupled calculation module, the state solution module, and the field instrument layer, respectively. The constraint drive module receives the target shell-side pressure command, the target condensate level command, the inlet steam flow command, and the temperature-pressure nonlinear partial derivatives. It then calculates the basic opening increment of the pneumatic control valve using a proportional-integral-differential algorithm. A dynamic maximum opening increment threshold is constructed using the temperature-pressure nonlinear partial derivatives to verify the basic opening increment of the inlet steam pneumatic control valve. If the basic opening increment exceeds this dynamic maximum opening increment threshold, a safety cutoff is performed, and the final valve opening command is converted into an electrical signal and output to the corresponding pneumatic control valve.

[0084] See Figure 2 This invention provides a method for coordinated temperature and pressure control of methanol synthesis catalyst vapor heating, comprising the following steps:

[0085] S100 uses a feature extraction module to simultaneously acquire bed temperature, shell pressure, steam flow rate and raw condensate level data, and calculates the dynamic excitation index after filtering.

[0086] S200: The state calculation module receives the shell-side pressure data obtained in step S100 and calculates the saturated latent heat of condensation and the temperature-pressure nonlinear partial derivative based on the shell-side pressure data.

[0087] S300: The phase change heat flux data of the previous control cycle is obtained by using the area observation module. The liquid level expansion is calculated based on the phase change heat flux data. The liquid level expansion is subtracted from the original condensate liquid level data obtained in step S100 to obtain the effective static liquid level. The effective phase change heat transfer area ratio coefficient is also calculated.

[0088] S400: The heat capacity estimation module receives the dynamic excitation index calculated in step S100, the saturated condensation latent heat value calculated in step S200, and the effective phase change heat transfer area ratio coefficient calculated in step S300. The dynamic forgetting factor is adjusted according to the dynamic excitation index, and the time-varying apparent heat capacity after numerical clamping is calculated and output.

[0089] S500: The external standard heating rate command is obtained by using the decoupled calculation module. The external standard heating rate command is multiplied with the time-varying apparent heat capacity output in step S400 to calculate the target latent heat flux. The target latent heat flux is decomposed into the target shell pressure command, the target condensate level command, and the steam flow command.

[0090] S600: The constraint drive module receives the target shell-side pressure command, target condensate level command, and steam inlet flow command obtained from step S500. It calculates the basic opening increment of the corresponding pneumatic control valve, constructs a dynamic maximum opening increment threshold using the temperature and pressure nonlinear partial derivatives calculated in step S200, verifies the basic opening increment of the steam inlet pneumatic control valve, performs safety cut-off processing, and outputs an electrical signal to the corresponding pneumatic control valve.

[0091] The working principle of each part will be explained in detail below with specific steps and formulas.

[0092] See Figure 3 The method provided by this invention mainly acquires real-time data from the industrial site and performs signal purification through a feature extraction module in step S100. Specifically, it includes the following steps:

[0093] S101 utilizes a feature extraction module to synchronously acquire multidimensional state variables from the reactor and its auxiliary pipelines via an analog input channel. At the current discrete sampling moment, the feature extraction module reads thermocouple measurements from multiple locations within the reactor tubes, performs an arithmetic average of these measurements, and calculates the bed temperature at the current discrete sampling moment. This multi-point averaging method transforms the non-uniformity of temperature distribution within the tube space into representative state data in a single dimension, supporting the subsequent overall assessment of time-varying apparent heat capacity.

[0094] The feature extraction module synchronously reads the shell-side pressure output from the absolute pressure transmitter, the inlet steam flow rate output from the flow meter, and the raw condensate level output from the differential pressure level transmitter. The analog-to-digital conversion and electrical isolation processing performed by the analog input channel when reading field instrument signals can be implemented by those skilled in the art using the hardware circuitry and firmware of conventional distributed control system input modules; this is well-known technology in the field and will not be elaborated upon here.

[0095] S102 utilizes the feature extraction module to perform first-order low-pass filtering on the synchronously acquired multi-dimensional state variables to eliminate high-frequency measurement noise caused by fluid pulsation and electromagnetic interference in the industrial environment. The feature extraction module establishes corresponding data buffers in its internal storage medium for bed temperature, shell-side pressure, steam flow rate, and initial condensate level, storing historical filtered valid data for each state dimension. The feature extraction module calls upon the historical filtered valid data for iterative calculations in the discrete-time domain according to a set discrete control cycle. The formula for the first-order low-pass filtering performed by the feature extraction module is:

[0096] ;

[0097] in, This represents the original measured observation value of the multidimensional state variable obtained at the current discrete sampling moment. This observation value specifically corresponds to any one of the aforementioned bed temperature, shell pressure, steam flow rate, or original condensate level. This represents the effective value of the state variable obtained after filtering the corresponding variable at the current discrete sampling time. This represents the effective value of the state variable output at the previous discrete sampling time. Indicates the current discrete sampling time; Indicates the previous discrete sampling time; This represents the filter coefficients.

[0098] Filter coefficients The value range is set to a real number greater than 0 and less than 1. The feature extraction module pre-calculates and determines the filter coefficients based on the duration of the discrete control cycle and the physical response time constant of the corresponding measuring instrument. The specific values ​​are determined. For example, for variables like temperature that have significant measurement inertia, a larger filter coefficient is configured to ensure real-time data tracking; for variables like pressure and flow that are prone to pulsation, a smaller filter coefficient is configured to enhance the smoothing effect. The effective values ​​of the state variables in each dimension obtained after filtering will serve as the basic data source for subsequent thermodynamic state calculations and feature extraction.

[0099] The method provided by the present invention further includes the following step of calculating the system dynamic excitation index in step S100:

[0100] S103, the feature extraction module extracts change feature data from the effective values ​​of the state variables after first-order low-pass filtering. At the current discrete sampling moment, the feature extraction module retrieves the calculated effective value of the bed temperature and the effective value of the bed temperature at the previous discrete sampling moment, and calculates the absolute difference between the two to determine the bed temperature change for the current control cycle. The bed temperature change is used to characterize the dynamic fluctuation of the thermal energy accumulation state inside the reactor.

[0101] Simultaneously, the feature extraction module retrieves the effective value of the inlet steam flow rate at the current discrete sampling moment and the effective value of the inlet steam flow rate at the previous discrete sampling moment, and calculates the absolute difference to obtain the change in inlet steam flow rate. The change in inlet steam flow rate is used to characterize the disturbance of energy input from the external heat source. Acquiring the change characteristic data at both the system input and output ends allows for a quantitative assessment of whether the current reactor operation is in a transient or steady-state process. The quantitative assessment results provide effective excitation data criteria for subsequent adaptive parameter identification.

[0102] S104, the feature extraction module performs normalized and weighted processing on the calculated change feature data to calculate the current dynamic stimulus index. The calculation expression for the normalized and weighted processing performed by the feature extraction module is as follows:

[0103] ;

[0104] in, This represents the dynamic excitation index calculated at the current discrete sampling moment; This represents the effective value of the bed temperature at the current discrete sampling moment; This represents the effective value of the bed temperature at the previous discrete sampling time. This represents the effective value of the inlet steam flow rate at the current discrete sampling moment; This represents the effective value of the inlet steam flow rate at the previous discrete sampling time. Indicates the current discrete sampling time; Indicates the previous discrete sampling time; This represents the normalized weighting coefficient for bed temperature; This represents the normalized weighting coefficient for the steam inlet flow rate.

[0105] Because of the physical difference in magnitude between bed temperature and steam flow rate, the feature extraction module determines normalization weighting coefficients based on the physical range of the corresponding instrument sensors. Specifically, the normalization weighting coefficient for bed temperature is set to the reciprocal of the difference in the maximum measurement range of the bed temperature sensor. The normalization weighting coefficient for steam flow rate is set to the reciprocal of the difference in the maximum measurement range of the steam flow rate sensor. Both normalization weighting coefficients are limited to a range between 0 and 1. Introducing these weighting coefficients ensures that the changes in both dimensions are mapped to the same order of magnitude for weighted calculation.

[0106] The calculated dynamic excitation index is a dimensionless, non-negative real number. When the reactor system is in a stable, isothermal plateau period, data excitation is scarce, and the calculated dynamic excitation index approaches zero. When the reactor system responds to process control commands by increasing the temperature or is disturbed by external steam network pressure fluctuations, the dynamic excitation index increases with the increase of data difference. The feature extraction module outputs the calculated dynamic excitation index to the heat capacity estimation module to avoid covariance matrix divergence in the heat capacity estimation algorithm during the steady-state region where effective data excitation is lacking.

[0107] See Figure 4 In step S200, the method provided by this invention mainly converts the shell-side pressure into thermodynamic parameters of the physical phase transition process through a state calculation module. Specifically, it includes the following steps:

[0108] S201: The state solution module receives the effective shell-side pressure value output by the feature extraction module at the current discrete sampling moment and calls the built-in industrial steam state equation of state to calculate the thermodynamic specific enthalpy. After receiving the pressure data, it is input as an independent variable into the internal calculation subroutine for reconstructing the thermodynamic properties. For the specific functional expression of the industrial steam state equation of state and the basic formula for Gibbs free energy, those skilled in the art can use the publicly available calculation framework of the internationally recognized IAPWS-IF97 standard. Its internal polynomial fitting calculation rules are well-known in the field and will not be elaborated upon here.

[0109] Based on the aforementioned state equation, the system can map the two-phase thermodynamic parameters under the current physical pressure environment in real time, and then simultaneously calculate the enthalpy of saturated liquid water and the enthalpy of saturated water vapor corresponding to the current pressure. By establishing this mapping relationship from apparent pressure to thermodynamic enthalpy, the energy state boundary in the actual phase change process can be accurately obtained, thereby avoiding the data lag phenomenon caused by traditional control schemes relying solely on surface temperature deviations.

[0110] S202, using the state calculation module based on the specific enthalpy data obtained above, the current saturated latent heat of condensation is further calculated. Specifically, by subtracting the specific enthalpy of saturated water vapor from that of saturated liquid water, the phase change heat release capacity under the current physical conditions can be obtained. The corresponding latent heat calculation formula is:

[0111] ;

[0112] in, This represents the saturated latent heat of condensation calculated at the current discrete sampling moment; This represents the saturated water vapor specific enthalpy calculated based on the effective value of the shell-side pressure at the current discrete sampling time. This represents the enthalpy of saturated liquid water calculated based on the effective value of the shell-side pressure at the current discrete sampling moment. This indicates the current discrete sampling time.

[0113] The calculated saturated latent heat of condensation is used to characterize the total latent heat released by a unit mass of water vapor during condensation phase change at the current shell-side ambient pressure. This value is subsequently stored in the shared data area of ​​the industrial main controller and output to the area observation module and heat capacity estimation module, serving as the basic physical constant for assessing the actual input heat of the reactor and estimating the apparent heat capacity of the bed.

[0114] The method provided by the present invention further includes the following step of calculating the nonlinear partial derivatives of temperature and pressure in step S200:

[0115] S203 utilizes the state calculation module to obtain the saturated latent heat of condensation, and further acquires the saturated absolute temperature and two specific volume data corresponding to the current effective shell-side pressure. Specifically, by calling the built-in inverse function of the industrial steam state equation, the saturated steam specific volume and saturated liquid water specific volume under the current physical pressure environment are extracted. Obtaining these parameters is beneficial for a complete description of the geometric and energy characteristics of the phase transition boundary, providing fundamental data for subsequent quantification of the nonlinear sensitivity of temperature-pressure coupling.

[0116] For the specific formulas for calculating the specific volume and saturation temperature under a specific pressure in the industrial steam state equation, those skilled in the art can refer to the standard thermodynamic constant table or the polynomial empirical fitting function. The table lookup and interpolation calculation of the physical constants are well-known techniques in this field and will not be elaborated here.

[0117] S204, using the state-based solution module, calculates the current temperature-pressure nonlinear partial derivatives based on the acquired thermodynamic parameters and the Clausius-Clapeyron equation. In the shell-side space of a closed reactor with coexisting vapor and liquid phases, the nonlinear gradient of the saturation temperature with pressure fluctuations directly determines the sensitivity of heat transfer in the catalyst bed. The corresponding formula for calculating the temperature-pressure nonlinear partial derivatives is:

[0118] ;

[0119] in, This represents the nonlinear partial derivative of temperature and pressure calculated at the current discrete sampling moment; This represents the absolute water vapor saturation temperature mapped from the effective value of the shell-side pressure at the current discrete sampling moment; This represents the saturated water vapor specific volume at the current discrete sampling time; This represents the specific volume of saturated liquid water at the current discrete sampling moment; This represents the saturated latent heat of condensation calculated at the current discrete sampling moment; This indicates the current discrete sampling time.

[0120] The calculated nonlinear partial derivatives of temperature and pressure reflect the physical offset of the saturated condensation temperature caused by unit pressure fluctuations under the current pressure conditions. As the methanol synthesis reactor gradually moves towards the high-pressure region during the heating process, the value of this partial derivative exhibits a nonlinear decay characteristic. The state solution module outputs the calculated nonlinear partial derivatives of temperature and pressure to the constraint drive module as a dynamic physical reference for setting the maximum action step threshold of the bottom-level pneumatic control valve. This replaces the fixed gain limitation in traditional control schemes, thereby suppressing the risk of bed temperature overshoot caused by temperature and pressure coupling distortion in the high-pressure region.

[0121] See Figure 5The method provided by this invention, in step S300, mainly eliminates the apparent liquid level measurement deviation caused by the boiling of the fluid inside the shell side through the area observation module. Specifically, it includes the following steps:

[0122] S301 utilizes the area observation module to acquire phase change heat flux data from the previous control cycle through the shared data area of ​​the industrial main controller. The area observation module retrieves the effective value of the inlet steam flow recorded at the previous discrete sampling moment and simultaneously reads the saturated latent heat of condensation value calculated and output by the state solution module at the previous discrete sampling moment. The area observation module multiplies the effective value of the inlet steam flow with the saturated latent heat of condensation value to obtain the phase change heat flux data injected into the reactor shell side in the previous control cycle.

[0123] This phase change heat flux data objectively characterizes the transient heating power acting on the bottom condensate of the shell side within the previous time window. During the heating process of the methanol synthesis reactor, when the input heat flux reaches a certain level, nucleation boiling occurs in the bottom condensate, generating a large number of rising bubbles. These bubbles, mixed in the liquid phase, cause a decrease in the average fluid density, resulting in the original condensate level output by the differential pressure level transmitter appearing as a physical illusion higher than the actual liquid level. Therefore, feedforward compensation calculations must be performed using historical heat flux.

[0124] S302, using the area observation module to establish a boiling expansion compensation model based on the calculated phase change heat flux data, to solve for the liquid level expansion at the current moment. The area observation module, combining shell-side hydrodynamic characteristics, converts the phase change heat flux into the equivalent liquid level height occupied by the bubble volume. The formula for the boiling expansion compensation model executed by the area observation module is as follows:

[0125] ;

[0126] in, This represents the amount of liquid level expansion calculated at the current discrete sampling moment; This represents the phase change heat flux data calculated at the previous discrete sampling time. This represents the saturated latent heat of condensation calculated at the previous discrete sampling time. This represents the saturated water vapor specific volume at the previous discrete sampling time. This represents the effective cross-sectional area of ​​the reactor shell side after deducting the heat exchange tube bundle; it is a fixed geometric constant. This represents the empirical coefficient of boiling expansion; Indicates the current discrete sampling time; This indicates the previous discrete sampling time.

[0127] The boiling expansion empirical coefficient is used to characterize the combined effect of the residence time and escape rate of bubbles in the liquid phase. The preset range for the boiling expansion empirical coefficient in the area observation module is between 0.01 and 0.15. The specific value of this empirical coefficient is preset by the field engineer based on the structural dimensions of the shell side of different reactors and calibration data from previous hydrostatic tests. The calculated liquid level expansion reflects the spurious increase in liquid level caused purely by the entrainment effect of boiling bubbles, and it serves as the baseline data for error deduction in the subsequent calculation of the true heat transfer boundary.

[0128] The method provided by the present invention further includes the following step in step S300: calculating the effective phase change heat transfer area ratio coefficient:

[0129] S303 utilizes the area observation module to correct measurement deviations based on the previously calculated liquid level expansion, thus obtaining the true physical liquid level height. It retrieves the original effective value of the condensate level output by the feature extraction module at the current discrete sampling moment and directly subtracts the liquid level expansion output by the boiling expansion compensation model from it. The effective static liquid level is obtained after the subtraction operation. This value eliminates dynamic interference caused by boiling bubbles in the shell side, accurately representing the physical boundary height of the bottom of the reactor shell side actually submerged by liquid water. Accurately obtaining the liquid level submersion height is a fundamental prerequisite for assessing the currently available heat exchange space on the reactor shell side.

[0130] S304, by substituting the obtained effective static liquid level into the internally configured tube-shell geometric mapping function, the effective phase change heat transfer area ratio coefficient is calculated. In a shell-and-tube methanol synthesis reactor, the tube-shell region submerged in condensate within the shell side transforms into liquid-phase sensible heat transfer, losing the physical conditions for the release of latent heat of water vapor condensation. Only the tube surfaces exposed in the vapor space can provide effective phase change heat transfer. The essence of geometric mapping is to calculate the dynamic ratio of the effective surface area of ​​the tube sections not submerged in liquid to the total surface area of ​​the tubes. The calculation formula for performing this geometric mapping is:

[0131] ;

[0132] in, This represents the effective phase change heat transfer area ratio coefficient calculated at the current discrete sampling moment; This represents the effective static liquid level calculated at the current discrete sampling moment; This indicates the effective total height of the heat exchange tubes inside the reactor, which is pre-written into the controller's storage area as a fixed hardware dimension parameter; This indicates the current discrete sampling time.

[0133] The calculated effective phase change heat transfer area proportionality coefficient is a dimensionless real number ranging from 0 to 1. As the condensate level inside the shell rises, this proportionality coefficient decreases accordingly, indicating that the actual usable condensation heat release capacity of the system is limited by physical space. The calculated results are then synchronously transmitted to the heat capacity estimation module as the basis for subsequent calculations of the effective input heat power. Introducing this coefficient ensures that the identification process of apparent heat capacity will not result in overestimation calculation errors due to the dynamic decay of the heat transfer area.

[0134] See Figure 6 The method provided by this invention, in step S400, mainly prevents the parameter identification algorithm from diverging under steady-state conditions through a heat capacity estimation module, thereby improving the stability of the identification process. Specifically, it includes the following steps:

[0135] S401 utilizes the heat capacity estimation module to receive the dynamic excitation index output by the feature extraction module at the current discrete sampling moment. In the online parameter identification stage of industrial process control, when the methanol synthesis reactor system is under stable operating conditions such as steady-state heat preservation, the system operating data often lacks sufficient fluctuation excitation. If a conventional and fixed small forgetting factor is used at this time, the covariance matrix inside the recursive least squares method will continuously expand due to the inability to acquire sufficient information, ultimately leading to the serious problem of covariance matrix divergence.

[0136] To avoid non-physical oscillations in the identification results due to minor high-frequency noise interference caused by covariance matrix divergence, the system pre-sets a basic forgetting factor and a forgetting gain coefficient in the controller's configuration area. The basic forgetting factor is set to a constant between 0.95 and 0.99, its physical meaning being to determine the lower limit boundary of forgetting under strong excitation conditions. The forgetting gain coefficient is set to a real number between 1 and 5, used to adjust the sensitivity of the identification algorithm to excitation index fluctuations; its specific value is pre-calibrated based on the noise statistical characteristics of historical operating data.

[0137] S402 utilizes the heat capacity estimation module to calculate the dynamic forgetting factor for the current control cycle in real time based on the received dynamic excitation index. Upon receiving the data, the internal calculation program introduces a nonlinear exponential decay function to map the dimensionless dynamic excitation index into a dynamic adjustment parameter between the basic forgetting factor and the value 1. The formula for this mapping calculation is:

[0138] ;

[0139] in, This represents the dynamic forgetting factor calculated at the current discrete sampling time. This represents the pre-defined basic forgetting factor; This represents the preset forgetting gain coefficient; This represents the dynamic excitation index received at the current discrete sampling moment; This indicates the current discrete sampling time.

[0140] Using the aforementioned nonlinear adjustment mechanism, when the reactor system responds to process heating commands or experiences strong data excitation due to external steam network disturbances, the calculated dynamic forgetting factor rapidly converges to the basic forgetting factor. This adaptive contraction adjustment accelerates the discarding of historically outdated data lacking reference value, improving the apparent heat capacity assessment algorithm's dynamic tracking speed of sudden changes in operating conditions. Conversely, when the system enters a steady state where data fluctuations approach zero, the calculated value of the dynamic forgetting factor automatically approaches 1. This state essentially freezes the decay and forgetting process of historical data, thereby suppressing the unbounded expansion of the covariance matrix and ensuring the absolute numerical stability of the heat capacity identification results under constant operating conditions.

[0141] The method provided by the present invention further includes the following step in step S400: calculating and outputting the time-varying apparent heat capacity through a heat capacity estimation module:

[0142] S403 utilizes the heat capacity estimation module to establish mathematical relationships for parameter identification based on the reactor's energy input and temperature response data, and performs parameter recursive updates in conjunction with a dynamic forgetting factor. It retrieves the effective value of the inlet steam flow rate at the current discrete sampling moment from the feature extraction module, and simultaneously acquires the saturated latent heat of condensation output from the state calculation module and the effective phase change heat transfer area ratio coefficient output from the area observation module. These three physical parameters are then continuously multiplied to obtain the effective input heat power actually acting on the catalyst bed within the current control cycle. Simultaneously, the difference between the effective bed temperature at the current discrete sampling moment and the previous discrete sampling moment is extracted and used as the observed output term of the system state response.

[0143] The calculated effective input heat power is used as the excitation input vector, and the temperature difference is used as the observed output vector, both substituted into the internal recursive least squares algorithm engine. This engine synchronously calls the historical covariance matrix retained from the previous control cycle, as well as the dynamic forgetting factor calculated in the preceding steps. For the specific solution formula for the Kalman gain vector and the iterative update rules for the covariance matrix in the recursive least squares method, those skilled in the art can refer to the standard multivariate recursive equation system in the field of system identification. The underlying matrix algebra operations are well-known techniques in this field and will not be elaborated here. After parameter iteration by the algorithm engine, the preliminary estimated value of the apparent heat capacity for the current control cycle is calculated.

[0144] S404 performs numerical clamping based on physical property extrema on the calculated preliminary apparent heat capacity estimate to output the final time-varying apparent heat capacity. During complex fluid disturbances or extreme condition transitions in industrial settings, purely mathematically driven recursive algorithms may output transient spikes that deviate from the actual physical meaning. To ensure the safe and stable operation of subsequent decoupled control commands, the system must forcibly restrict the identification results to a trust domain with clear physical meaning. The conditional expression for performing this numerical clamping process is:

[0145] ;

[0146] in, This represents the time-varying apparent heat capacity output after numerical clamping at the current discrete sampling time. This represents the preliminary apparent heat capacity estimate calculated by the recursive least squares algorithm engine at the current discrete sampling time. This indicates the preset upper limit threshold for apparent heat capacity; This represents the preset lower threshold value of apparent heat capacity; Indicates the current discrete sampling time; This represents a logical conditional operator, which means that when the mathematical interval relationship following it is satisfied, the corresponding branch's numerical assignment operation is executed.

[0147] Regarding the specific method for determining the trust domain boundary, the lower threshold of apparent heat capacity is pre-calculated based on the physical parameters of the reactor's metal shell weight and the dry total heat capacity of the unloaded catalyst inside. The upper threshold of apparent heat capacity is calculated based on the total full-load heat capacity of the system when the reactor shell-side space is completely filled with saturated condensate. These basic structural material parameters and fluid specific heat capacity data are directly derived from the original engineering design drawings and factory calibration documents of the chemical equipment. After the above clamping constraint, the time-varying apparent heat capacity can accurately and safely reflect the true thermal inertia state of the current reactor bed. This data is then transmitted in real time to the decoupled calculation module to support the subsequent construction process of the target latent heat flux.

[0148] See Figure 7 The method provided by this invention, in step S500, mainly derives the core energy requirements of the system based on the energy supply and demand balance logic through a decoupled calculation module. Specifically, it includes the following steps:

[0149] S501 utilizes a decoupled calculation module to receive external standard temperature rise rate commands from a host computer via an industrial communication network. These commands are pre-configured by process operators based on the activation requirements of the methanol synthesis catalyst, specifying the allowable reasonable temperature rise gradient for the reactor at different production stages. The specific protocol and verification process for the decoupled calculation module to parse network data packets via the communication interface can be implemented using standard Modbus or OPC UA industrial communication protocols by those skilled in the art. The underlying data link transmission and parsing mechanisms are well-known technologies in the field and will not be elaborated upon here.

[0150] While receiving external standard heating rate commands, the decoupled calculation module synchronously retrieves the time-varying apparent heat capacity output by the heat capacity estimation module at the current discrete sampling moment. Through the above operations, the system obtains the process requirement data that drives the reactor state to change and the physical state data characterizing the current thermal inertial resistance of the system. Obtaining these two pieces of data is a prerequisite for breaking away from the traditional control strategy that relies solely on temperature deviation for hysteresis adjustment, enabling the subsequent control command generation logic to shift to forward derivation based on physical mechanisms.

[0151] S502, the decoupled calculation module multiplies the acquired external standard heating rate command with the current time-varying apparent heat capacity to deduce the energy reference value required to sustain the heating process. This energy reference value is the target latent heat flux. The specific mathematical expression for performing the forward calculation of the target latent heat flux is:

[0152] ;

[0153] in, This represents the target latent heat flux calculated at the current discrete sampling time. This represents the time-varying apparent heat capacity output after numerical clamping at the current discrete sampling time. This indicates the external standard heating rate command received at the current discrete sampling moment; This indicates the current discrete sampling time.

[0154] The calculated target latent heat flux clearly characterizes the total phase change heating power that must be provided on the reactor shell side to overcome the current dynamic thermal inertia of the bed and achieve the predetermined temperature rise target. This calculation process directly transforms the temperature change requirements at the process operation level into an energy input indicator at the underlying thermodynamic level. The obtained target latent heat flux is then used as a unified energy driving source, residing in the internal register of the decoupled calculation module, to support the subsequent multidimensional physical decomposition of temperature and pressure boundaries and material flow rates.

[0155] The method provided by this invention, in step S500, transforms the one-dimensional target energy demand into a three-dimensional physical control command that the underlying actuator can directly respond to through a decoupled calculation module. Specifically, it includes the following steps:

[0156] S503 utilizes the decoupled calculation module to transform the target latent heat flux derived in the previous step into physical dimensions to generate the basic steam flow command. It retrieves the saturated latent heat of condensation output from the state calculation module and the effective phase change heat transfer area ratio coefficient output from the area observation module. Combining these data, a division operation is used to reduce the abstract heat power demand to specific material mass attributes.

[0157] The calculation expression for decomposing the steam flow command is as follows:

[0158] ;

[0159] in, This represents the steam flow command calculated at the current discrete sampling moment; This represents the target latent heat flux calculated at the current discrete sampling time. This represents the saturated latent heat of condensation at the current discrete sampling moment; This represents the effective phase change heat transfer area ratio coefficient at the current discrete sampling moment; This indicates the current discrete sampling time. The calculated inlet steam flow command directly represents the mass flow rate of water vapor that the system must supply to the reactor shell side after considering space flooding losses and the current physical pressure environment.

[0160] S504 further derives the target shell-side pressure command and target condensate level command for maintaining system thermodynamic equilibrium. To ensure the saturation temperature of the reactor shell-side space tracks the process-specified temperature rise curve without deviation, the system extracts the external standard heating rate command at the current discrete sampling moment and performs discrete-time domain integral derivation using the temperature-pressure nonlinear partial derivatives output by the state solution module. The derivation formula for the target shell-side pressure command is:

[0161] ;

[0162] in, This represents the target shell-side pressure command calculated at the current discrete sampling moment; This indicates the target shell-side pressure command output at the previous discrete sampling time. This indicates the external standard heating rate command received at the current discrete sampling moment; This indicates the preset discrete control cycle duration, which is set to a fixed real number between 0.1 seconds and 2 seconds. This represents the nonlinear partial derivative of temperature and pressure at the current discrete sampling moment; Indicates the current discrete sampling time; This indicates the previous discrete sampling time.

[0163] To address the spatial geometric constraints at the bottom of the reactor, the system synchronously generates a target condensate level command based on a fixed structural boundary. The pre-stored effective total height parameter of the heat exchange tubes is extracted and multiplied by a set safety margin ratio for the condensate level to calculate the maximum physical limit that the condensate can reach. This physical limit is directly output as the target condensate level command to the bottom-level control loop. The safety margin ratio is set to a range of 0.8 to 0.9 to ensure that 10% to 20% of the top of the shell-side space is always reserved for pure vapor-phase heat exchange tubes. Through this physical dimensionality reduction decomposition, the single energy demand is completely reconstructed into three independent control objectives in three orthogonal dimensions: flow rate, pressure, and condensate level.

[0164] See Figure 8 In step S600, the method provided by this invention mainly converts multi-dimensional physical control commands into actual action quantities of the underlying pneumatic regulating valve through a constraint drive module. Specifically, it includes the following steps:

[0165] S601 utilizes the constraint-driven module to calculate the real-time operational deviations of each control dimension. It retrieves the steam flow command, target shell-side pressure command, and target condensate level command output by the decoupled calculation module at the current discrete sampling moment. Simultaneously, it receives the effective values ​​of the steam flow and shell-side pressure extracted by the feature extraction module, as well as the effective static liquid level calculated and output by the area observation module. Through one-to-one subtraction calculations, it calculates the difference between the corresponding target command and the actual feedback effective value, thereby obtaining the current control deviations of the three physical dimensions: flow, pressure, and liquid level.

[0166] Obtaining precise control deviations is fundamental to driving feedback regulation in the underlying closed-loop circuit. The above calculation quantitatively compares the ideal physical state derived from the forward derivation of energy supply and demand in the preceding steps with the actual operating state of the reactor, objectively reflecting the compensation margin lacking in the system to achieve the target latent heat flux transfer.

[0167] S602 inputs the acquired control deviations of each dimension into the controller's built-in basic closed-loop regulation loop to calculate the corresponding basic opening increment. Combining the incremental control strategy widely used in industrial settings, a proportional-integral-derivative (PID) algorithm is used to iteratively calculate the control deviation. Taking the steam inlet regulating valve, which controls the core energy input, as an example, the specific mathematical expression for calculating the basic opening increment is:

[0168] ;

[0169] in, This represents the increment of the basic opening of the steam inlet regulating valve calculated at the current discrete sampling moment; , , These represent the deviations in the inlet steam flow rate at the current, previous, and previous discrete sampling times, respectively. These deviations are obtained by subtracting the effective value of the inlet steam flow rate from the inlet steam flow rate command. , , These represent the proportional coefficient, integral coefficient, and differential coefficient preset in the closed-loop circuit for steam inlet flow, respectively. This indicates the current discrete sampling time.

[0170] For the specific tuning rules and parameter optimization methods of each gain coefficient in the above algorithm, those skilled in the art can use the standard Ziegler-Nichols rule or the empirical trial-and-error method based on historical step response curves. The underlying proportional, integral, and differential logic are well-known techniques in the field and will not be elaborated upon here. The calculated basic opening increment characterizes the theoretical action amplitude required by the underlying control valve to eliminate the current deviation under normal conditions without considering the temperature-pressure coupling limitations in the high-pressure zone. This preliminary solution data is then sent to an internal verification program to accept subsequent dynamic physical extremum constraints based on thermodynamic partial derivatives.

[0171] The method provided by the present invention further includes the following step in step S600: performing a safety cutoff through the constraint driving module and outputting a final control command:

[0172] S603 utilizes the constraint-driven module to retrieve the nonlinear thermo-pressure partial derivatives calculated by the state-solving module to construct adaptive action boundaries that change with process conditions. During the methanol synthesis reactor's transition to the high-pressure zone, the sensitivity of the saturated condensation temperature to pressure fluctuations exhibits a nonlinear decay. If the fixed adjustment step size calculated from the basic closed-loop circuit is still used at this point, it can easily lead to over-response in the underlying control system and cause significant pressure oscillations. Therefore, the system must map the purely physical thermodynamic partial derivatives to the action constraints of the actuators. The specific mathematical expression for calculating this constraint boundary is:

[0173] ;

[0174] in, This represents the dynamic maximum opening increment threshold calculated at the current discrete sampling time. This represents the nonlinear partial derivative of temperature and pressure output by the state solution module at the current discrete sampling moment; This represents the preset partial derivative gain conversion coefficient; This indicates the current discrete sampling time.

[0175] The calculated dynamic maximum opening increment threshold directly defines the maximum permissible actuation range of the pneumatic control valve within a single control cycle under the current physical pressure environment. The partial derivative gain conversion coefficient is used to match the conversion ratio between the physical partial derivative dimensions and the valve's mechanical opening dimensions; its value is set as a fixed constant between 0.1 and 1.5. The specific value of this coefficient is pre-calculated by engineers based on the inherent flow characteristic curve and nominal flow capacity parameters of the control valve in the field and configured in the controller.

[0176] S604 compares the previously calculated basic opening increment with the dynamic maximum opening increment threshold, performs a safety cutoff based on physical property extreme value constraints, and finally outputs the valve control command. This cutoff mechanism prevents the control system from outputting extreme adjustment amounts that disrupt the reactor's thermodynamic balance when faced with sudden changes in process setpoints or strong external pipeline interference. The conditional expression for performing the safety cutoff is:

[0177] ;

[0178] in, This represents the final opening increment after safe truncation at the current discrete sampling time; This represents the basic aperture increment calculated at the current discrete sampling moment; This represents a logical conditional decision operator, specifically meaning that when the mathematical interval relationship following it is satisfied, the corresponding branch's numerical assignment operation is executed. This logic ensures that regardless of the calculation result of the basic control loop, the actual action increment is clamped within the safety boundary.

[0179] After the safety cutoff is completed, the internal logic adds the final opening increment to the actual opening command of the previous control cycle to obtain the final valve opening command for the current cycle. The calculation formula is as follows:

[0180] ;

[0181] in, This represents the final valve opening command calculated at the current discrete sampling moment; This indicates the final valve opening command output and applied to the actuator at the previous discrete sampling time.

[0182] The calculated final valve opening command is converted into a control signal recognizable by the underlying hardware and sent to the reactor shell-side inlet pneumatic regulating valve in the field. For the signal conversion and control transmission from the controller command to the field actuator, those skilled in the art can use standard 4-20mA analog electrical signal output or fieldbus-based digital message communication. The underlying hardware interface driver and the working principle of the electro-pneumatic conversion mechanism are well-known technologies in the field and will not be elaborated here. Through the aforementioned physical gain verification and output truncation mechanism, the system effectively cuts off the path of nonlinear coupling distortion that damages bed temperature stability from the execution terminal.

[0183] Furthermore, for the shell-side pressure deviation and condensate level deviation obtained in step S601, the constraint drive module simultaneously uses its internally configured proportional-integral-differential algorithm to calculate the final opening commands of the shell-side back pressure pneumatic control valve and the condensate discharge pneumatic control valve, respectively, and converts them into corresponding electrical signals for output to the two pneumatic control valves. Thus, the system closes the control loop from three dimensions: steam energy injection, shell-side back pressure exhaust, and bottom condensate discharge, achieving multi-dimensional physical coordinated control of flow rate, pressure, and level.

[0184] Specific application examples are as follows:

[0185] A methanol plant with an annual production capacity of 600,000 tons uses a shell-and-tube methanol synthesis reactor (water-cooled). During the initial temperature-raising and activation stage of the catalyst (such as Cu / Zn / Al system) during start-up, it is necessary to introduce medium-pressure steam through the shell side for heating.

[0186] External standard heating rate command (i.e., 0.00416℃ / s), sudden temperature increases are strictly prohibited to prevent catalyst sintering. The effective total height of the heat exchange tubes inside the reactor. The effective cross-sectional area of ​​the reactor shell side after deducting the heat exchange tube bundle Discrete control cycle duration Filter coefficients .

[0187] Assume the current reactor shell pressure is 1.55 MPa, corresponding to a saturation temperature of approximately 200 °C.

[0188] After low-pass filtering, the effective value of the inlet steam flow rate is read. Shell-side pressure 1.55 MPa.

[0189] Calculate the saturated latent heat of condensation using the industrial steam state equation. .

[0190] Obtain the two phase tolerance values, and calculate the thermo-baric nonlinear partial derivatives based on the Clausius-Clapeyron equation. (This means that under this pressure, for every 1 MPa fluctuation in pressure, the saturation temperature fluctuates by approximately 38.5°C).

[0191] The differential pressure level gauge measured the initial liquid level to be 1.8m. The liquid level expansion was calculated using phase change heat flux. .

[0192] Subtracting false liquid levels yields the effective static liquid level. .

[0193] Calculation of tube-shell geometry mapping: effective phase change heat transfer area ratio coefficient (That is, 85% of the pipe section is exposed to the steam zone and participates in phase change heating).

[0194] The recursive least squares method combined with a dynamic forgetting factor (to avoid steady-state divergence) identifies the time-varying apparent heat capacity of the current bed layer. .

[0195] The latent heat flux is derived forward as follows: .

[0196] Dimensional reduction decomposition of steam flow: (An incremental demand of approximately 435.6 kg / h).

[0197] The basic PID calculation yields the basic opening increment of the steam inlet regulating valve. .

[0198] Constructing dynamic boundaries using nonlinear partial derivatives of temperature and pressure: partial derivative gain conversion coefficient .

[0199] The maximum opening increment threshold is: .

[0200] because This triggers a safety cutoff, resulting in the final actual output. .

[0201] In high-pressure areas, even a small pressure surge can lead to a dramatic temperature response. The system... The valve step size is forcibly limited to prevent temperature overshoot caused by thermodynamic imbalance.

[0202] To verify the effectiveness of this invention, a comparative experiment was conducted with a traditional cascade PID control strategy under the aforementioned process conditions. In this embodiment, the external standard heating rate command was set to 15℃ / h, the controlled object was a shell-and-tube methanol synthesis reactor, and the comparison object was a traditional cascade PID control strategy.

[0203] See Figure 9 , Figure 9The figure illustrates the control results of two control strategies on the bed temperature during a 2-hour heating cycle. The solid black line represents the external standard heating rate command, with a constant slope of 15℃ / h, increasing the temperature from 150℃ to 180℃ at the set rate. The gray dashed line represents the actual temperature under traditional PID control. This curve lies below the solid black line representing the external standard heating rate command in the 0-1.1h interval and above it in the 1.2-2h interval. This phenomenon occurs because the reactor has a large heat capacity. Traditional PID control relies on temperature deviation for feedback regulation. Due to the time-dependent integral action in the early heating stage, the input heat cannot compensate for the bed's thermal inertia in time, resulting in a temperature lag of approximately 2.5℃. In the later heating stage, the reactor shell pressure increases, and the sensitivity of the saturated condensation temperature to pressure exhibits nonlinear characteristics due to temperature-pressure coupling. The fixed PID parameters lead to an excessively large adjustment, resulting in a temperature overshoot of approximately 3.5℃.

[0204] Figure 9 The black dashed line represents the actual temperature controlled by the present invention. This curve largely coincides with the black solid line, showing no significant lag or overshoot. The reason for the overlap of the two curves is that the present invention uses a heat capacity estimation module to calculate the time-varying apparent heat capacity, multiplying it by the heating rate command to obtain the target latent heat flux. This forward derivation mechanism calculates the required steam flow rate before temperature deviation occurs, pre-matching the heat required by the system, thus enabling the actual temperature to stably match the target command curve.

[0205] See Figure 10 , Figure 10 This diagram illustrates the changes in the opening of the pneumatic control valve during the heating process. The gray dashed line represents the valve action under traditional PID control. The curve shows the opening increasing to approximately 30% in the initial stage of operation, followed by low-frequency oscillations in the later stages. This is because, in response to the temperature lag in the early stages of heating, the integral accumulation of the PID controller increases the valve opening to improve steam flow; conversely, in response to temperature overshoot in the later stages, the feedback mechanism reduces the valve opening. Traditional control methods do not introduce limiting parameters for physical boundaries, resulting in the valve opening fluctuating repeatedly during regulation.

[0206] The solid black line represents the valve action of this invention. Initially, the opening is increased to approximately 26%, and then only a small adjustment is maintained in subsequent control cycles, resulting in minimal overall fluctuation. This is because the constraint drive module of this invention utilizes the nonlinear partial derivatives of temperature and pressure calculated by the state solution module to construct a dynamic maximum opening increment threshold. As the temperature rises towards the high-pressure zone, this maximum opening increment threshold tightens as the partial derivative decreases. When the basic opening increment calculated by the basic closed-loop circuit exceeds this threshold, the constraint drive module performs a safety cutoff, limiting the maximum step size of a single valve action. This mechanism limits the limit value of the opening increment, preventing oscillations in the actuator.

[0207] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for coordinated temperature and pressure control of vapor heating in methanol synthesis catalysts, characterized in that, Includes the following steps: Acquire bed temperature, shell pressure, steam flow rate and raw condensate level data, and calculate dynamic excitation index; Calculate the saturated latent heat of condensation and the nonlinear partial derivative of temperature and pressure based on the shell-side pressure. Obtain the phase change heat flux data of the previous control cycle, and calculate the effective phase change heat transfer area ratio coefficient based on the phase change heat flux data and the original condensate level data. The time-varying apparent heat capacity is calculated by combining the bed temperature, the dynamic excitation index, the saturated latent heat of condensation, and the effective phase change heat transfer area ratio coefficient. The target latent heat flux is obtained based on the external standard heating rate command and the time-varying apparent heat capacity. The target latent heat flux is decomposed into the target shell-side pressure command, the target condensate level command, and the steam inlet flow rate command. The basic opening increment of the steam inlet pneumatic control valve is calculated based on the steam inlet flow command. The basic opening increment is then subjected to a safety cutoff process using the temperature and pressure nonlinear partial derivative. An electrical signal is output to the steam inlet pneumatic control valve. An electrical signal is also output to the shell-side back pressure pneumatic control valve based on the target shell-side pressure command. Finally, an electrical signal is output to the condensate discharge pneumatic control valve based on the target condensate level command.

2. The method for coordinated temperature and pressure control of methanol synthesis catalyst vapor heating according to claim 1, characterized in that, The acquisition of bed temperature, shell pressure, steam flow rate, and initial condensate level data, and the calculation of the dynamic excitation index, include: The bed temperature is obtained by acquiring measured values ​​from thermocouples and calculating the average value; the shell pressure is obtained from an absolute pressure transmitter; the steam flow rate is obtained from a flow meter; and the raw condensate level data is obtained from a differential pressure level transmitter. The bed temperature and the steam flow rate are subjected to low-pass filtering to obtain the effective values ​​of the bed temperature and the steam flow rate, respectively. Calculate the absolute difference between the effective value of the bed temperature at the current discrete sampling time and the effective value of the bed temperature at the previous discrete sampling time to obtain the change in bed temperature; Calculate the absolute difference between the effective value of the steam inlet flow rate at the current discrete sampling time and the effective value of the steam inlet flow rate at the previous discrete sampling time to obtain the change in steam inlet flow rate; The dynamic excitation index is obtained by normalizing and weighting the changes in bed temperature and the changes in steam flow rate.

3. The method for coordinated temperature and pressure control of methanol synthesis catalyst vapor heating according to claim 1, characterized in that, The calculation of the saturated latent heat of condensation and the thermobaric nonlinear partial derivative based on the shell-side pressure includes: Extract the saturated absolute temperature, saturated water vapor specific volume, saturated liquid water specific volume, saturated water vapor specific enthalpy, and saturated liquid water specific enthalpy corresponding to the shell-side pressure; The saturated latent heat of condensation is obtained by subtracting the saturated water vapor specific enthalpy and the saturated liquid water specific enthalpy. The saturated absolute temperature is multiplied by the difference between the saturated water vapor specific volume and the saturated liquid water specific volume, and the result of the multiplication is divided by the saturated latent heat of condensation to obtain the nonlinear partial derivative of temperature and pressure.

4. The method for coordinated temperature and pressure control of methanol synthesis catalyst vapor heating according to claim 2, characterized in that, The step of acquiring phase change heat flux data from the previous control cycle and calculating the effective phase change heat transfer area ratio coefficient based on the phase change heat flux data and the original condensate level data includes: The phase change heat flux data is obtained by multiplying the effective value of the inlet steam flow rate of the previous control cycle with the value of the saturated latent heat of condensation. Calculate the liquid level expansion based on the phase change heat flux data; The original condensate level data at the current discrete sampling time is subjected to low-pass filtering to obtain the original effective value of the condensate level; The effective static liquid level is obtained by subtracting the liquid level expansion from the original effective value of the condensate level. Substituting the effective static liquid level into the tube-shell geometric mapping function, the ratio of the effective surface area of ​​the unsubmerged tube section to the total surface area of ​​the tube-shell is calculated, thus obtaining the effective phase change heat transfer area ratio coefficient.

5. The method for coordinated temperature and pressure control of methanol synthesis catalyst vapor heating according to claim 4, characterized in that, The time-varying apparent heat capacity is calculated by combining the bed temperature, the dynamic excitation index, the saturated latent heat of condensation, and the effective phase change heat transfer area ratio coefficient, including: determining the dynamic forgetting factor based on the dynamic excitation index; The effective input heat power is obtained by multiplying the effective value of the inlet steam flow rate, the saturated latent heat of condensation, and the effective phase change heat transfer area ratio coefficient. The temperature difference is calculated by comparing the effective value of the bed temperature at the current discrete sampling time with the effective value of the bed temperature at the previous discrete sampling time. Using the effective input thermal power as the excitation input vector and the temperature difference as the observation output vector, the preliminary apparent heat capacity estimate is calculated by using the recursive least squares method in combination with the dynamic forgetting factor. Numerical clamping processing is performed on the preliminary apparent heat capacity estimate based on the predetermined lower and upper limits of apparent heat capacity, and the time-varying apparent heat capacity is output.

6. The method for coordinated temperature and pressure control of methanol synthesis catalyst vapor heating according to claim 5, characterized in that, The dynamic forgetting factor is determined based on the dynamic stimulus index, including: Based on the preset basic forgetting factor and the preset forgetting gain coefficient, the dynamic excitation index is mapped to the dynamic forgetting factor using a nonlinear exponential decay function.

7. The method for coordinated temperature and pressure control of methanol synthesis catalyst vapor heating according to claim 5, characterized in that, The step of deriving the target latent heat flux based on the external standard heating rate command and the time-varying apparent heat capacity, and decomposing the target latent heat flux into a target shell-side pressure command, a target condensate level command, and an inlet steam flow rate command, includes: The target latent heat flux is obtained by multiplying the external standard heating rate command with the time-varying apparent heat capacity. The product of the target latent heat flux, the saturated condensing latent heat value, and the effective phase change heat transfer area ratio coefficient is divided to obtain the steam inlet flow command. The target shell-side pressure command is generated by performing integral calculations using the aforementioned nonlinear partial derivatives of temperature and pressure. The target condensate level command is generated by multiplying the pre-stored effective total height parameter of the heat exchange tubes with the liquid level safety margin ratio.

8. The method for coordinated temperature and pressure control of methanol synthesis catalyst vapor heating according to claim 7, characterized in that, The basic opening increment of the inlet pneumatic control valve is calculated based on the inlet steam flow command, including: The difference between the steam inlet flow command and the effective value of the steam inlet flow is calculated to obtain the steam inlet flow deviation; The proportional-integral-differential algorithm is used to calculate the steam inlet flow deviation, thereby obtaining the basic opening increment of the steam inlet pneumatic regulating valve.

9. The method for coordinated temperature and pressure control of methanol synthesis catalyst vapor heating according to claim 1, characterized in that, Using the aforementioned temperature-pressure nonlinear partial derivative to perform a safety cutoff process on the basic opening increment, an electrical signal is output to the steam inlet pneumatic regulating valve, including: The dynamic maximum opening increment threshold is calculated by multiplying the temperature-pressure nonlinear partial derivative with the partial derivative gain conversion coefficient. The basic opening increment of the steam inlet pneumatic regulating valve is compared with the dynamic maximum opening increment threshold. When the basic opening increment of the steam inlet pneumatic regulating valve exceeds the dynamic maximum opening increment threshold, the dynamic maximum opening increment threshold is taken as the final opening increment. The final valve opening command is obtained by superimposing the final opening increment with the actual opening command of the previous control cycle. The final valve opening command is converted into an electrical signal and output to the steam inlet pneumatic regulating valve.

10. A temperature and pressure coordinated control system for vapor heating of methanol synthesis catalyst, characterized in that, The system includes a functional module that performs a method for coordinated temperature and pressure control of vapor heating in methanol synthesis catalyst as described in any one of claims 1-9.

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