A method and system for optimizing temperature and pressure collaborative control of an electric control cabinet of a vulcanizer

Abstract

The present application belongs to the technical field of industrial production process control, and particularly relates to a kind of vulcanizing machine electric control cabinet temperature and pressure synergic control optimization method and system, its method includes: real-time acquisition frequency converter operating current, the environmental temperature in electric control cabinet, mold hydraulic pressure and mould original temperature;Based on current thermal effect and thermal inertia principle, the heat accumulation index reflecting the local heat saturation degree of PCB is constructed;Based on the principle of contact mechanics, the interface heat conduction efficiency coefficient reflecting the heat conduction performance of the contact interface between the mold and the heating plate is constructed;The error gain vector containing the reference drift term and the coupling interference term is estimated in real time by using recursive least square algorithm, the temperature compensation amount is calculated and the real temperature is reconstructed, and the heating actuator is adjusted.The present application dynamically decouples and compensates the nonlinear drift and contact thermal resistance through the physical mechanism model, eliminates the environmental disturbance and load disturbance under complex working conditions, and improves the temperature control precision of vulcanization process.

Description

Technical Field

[0001] This invention relates to the field of industrial production process control technology. More specifically, this invention relates to a method and system for optimizing temperature and pressure coordinated control of a vulcanizing machine's electrical control cabinet. Background Technology

[0002] In the rubber vulcanization process, precise control of temperature and pressure is crucial in determining the tensile strength, hardness, and abrasion resistance of the finished product. Traditional vulcanizing machine control systems typically rely on closed-loop regulation based on PID algorithms. However, in actual industrial settings, two types of physical interference severely impact the accuracy of temperature acquisition, causing traditional control methods to fail: The first type is thermal accumulation interference within the electrical control cabinet. As the control core, the electrical control cabinet integrates high-power frequency converters and solid-state relays. During prolonged operation, the Joule heat generated by these components causes the ambient temperature inside the cabinet to rise. Existing analog signal acquisition modules are typically located inside the cabinet, and the high-precision reference voltage source within this module is extremely sensitive to temperature. When the ambient temperature changes, the reference voltage source experiences nonlinear drift, causing errors in the analog-to-digital conversion stage of the sensor feedback signal. This error is often mistakenly interpreted as a change in mold temperature, leading the controller to make incorrect adjustments.

[0003] The second type is nonlinear time-varying interference from contact thermal resistance. Heat is transferred between the heating plate and the mold of the vulcanizing machine through mechanical contact. According to the principles of contact mechanics, the thermal resistance at the contact interface is not constant but is nonlinearly affected by the hydraulic pressure during mold closing. When the hydraulic pressure fluctuates or during the initial stage of mold closing, the thermal resistance increases because the physical interface between the mold and the heating plate fails to achieve completely tight mechanical contact. At this time, the temperature collected by sensors installed at specific locations on the mold or heating plate will show a significant lag. Current technology lacks a mathematical description of this coupling relationship between pressure and thermal resistance, making it impossible to distinguish whether the problem stems from insufficient heat source power or excessive contact thermal resistance, thus leading to control overshoot.

[0004] In summary, the existing technology lacks a comprehensive model of the thermal environment inside the electrical control cabinet and the contact state with external mechanical components, resulting in physical distortion of the collected temperature data, which in turn leads to a decrease in product yield. Summary of the Invention

[0005] To address the technical problems in existing vulcanizing machine control systems, such as sampling drift caused by heat accumulation interference inside the electrical control cabinet and temperature control lag caused by nonlinear changes in mold contact thermal resistance with mold closing hydraulic pressure, this invention provides a method and system for optimizing temperature and pressure coordinated control of the vulcanizing machine electrical control cabinet.

[0006] In a first aspect, the present invention provides a method for optimizing temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet, comprising: acquiring multi-source physical state parameters of the vulcanizing machine system in real time through an industrial communication interface and a sensor network, wherein the multi-source physical state parameters include inverter operating current, ambient temperature inside the electrical control cabinet, mold closing hydraulic pressure, and original mold temperature; constructing a heat accumulation index based on inverter operating current and thermal memory decay factor using weighted logic reflecting thermal inertia, and evaluating the degree of thermal interference generated by heat sources inside the electrical control cabinet on the analog quantity acquisition module through the heat accumulation index; constructing a temperature and pressure coupled thermal conductivity model based on the physical characteristics of the mold closing hydraulic pressure and the contact interface, determining the interface thermal conductivity coefficient under the current state through the temperature and pressure coupled thermal conductivity model to characterize the nonlinear characteristics of the contact thermal resistance between the mold and the heating plate as a function of pressure; using the ambient temperature inside the electrical control cabinet, the heat accumulation index, and the interface thermal conductivity coefficient, combined with a recursive least squares algorithm to estimate the error gain vector in real time, calculating the temperature compensation amount, and using the temperature compensation amount to correct the original mold temperature to obtain the true temperature, and adjusting the heating actuator according to the deviation between the true temperature and the process set value.

[0007] By adopting the above technical solution, this invention introduces multi-source sensing features such as inverter operating current, ambient temperature inside the electrical control cabinet, and mold clamping hydraulic pressure to construct a thermal accumulation index and a temperature-pressure coupled thermal conductivity model. It then combines this with a recursive least squares algorithm to calculate the temperature compensation in real time to correct the original mold temperature. This solution expands the traditional single temperature feedback into a multi-dimensional physical state feedforward and feedback joint control. It utilizes the thermal accumulation index to accurately eliminate measurement noise caused by the temperature drift of the reference voltage source in the analog quantity acquisition module. Simultaneously, it effectively decouples the false low-temperature feedback caused by insufficient mechanical contact between the mold and the heating plate through the interface thermal conductivity coefficient. This solves the control failure problems caused by thermal accumulation interference inside the electrical control cabinet and nonlinear time-varying interference from contact thermal resistance, eliminates physical distortion of the original temperature data during the acquisition stage, and improves the dynamic tracking accuracy of the vulcanization temperature under complex working conditions.

[0008] Preferably, in the step of acquiring multi-source physical state parameters, the inverter operating current is acquired by a Hall current sensor installed at the three-phase output terminal of the inverter; the ambient temperature inside the electrical control cabinet is acquired by a temperature sensor arranged near the PCB board of the analog quantity acquisition module; the mold closing hydraulic pressure is acquired by a pressure transmitter on the oil circuit of the main hydraulic cylinder of the vulcanizing machine; and the original mold temperature is the original digital quantity obtained by a thermal resistor embedded inside the mold.

[0009] By adopting the above technical solution, this invention provides a complete and accurate data foundation for the system to accurately construct a multi-dimensional real-time model of the ambient temperature state and external mechanical contact state inside the electrical control cabinet by using dedicated sensor devices to collect multi-source physical state parameters at key nodes. This avoids the control instability caused by traditional temperature control that is based solely on a single temperature feedback.

[0010] Preferably, the heat accumulation index satisfies the following relationship:

[0011] in, Indicates the current time The heat accumulation index; Indicates the thermal memory decay factor; This represents the heat accumulation index at the previous moment; Indicates the current time The inverter's operating current; This indicates the rated current of the frequency converter.

[0012] By employing the above technical solution, this invention utilizes an exponentially weighted moving average algorithm and weighted logic reflecting thermal inertia to construct a thermal accumulation index with attenuation characteristics. This accurately assesses the local thermal saturation level of the PCB board inside the analog signal acquisition module and precisely characterizes the thermal response hysteresis characteristics of electronic components under long-term operating conditions. This design considers the instantaneous heat generation caused by the inverter's operating current while also introducing a thermal memory attenuation factor to restore the hysteresis effect of the heat dissipation system. Through this technical means, this invention avoids drastic signal fluctuations caused by compensating solely with the instantaneous inverter operating current, ensuring the smoothness of the temperature compensation process.

[0013] Preferably, the interfacial thermal conductivity coefficient satisfies the following relationship:

[0014] in, Indicates the current time The interfacial thermal conductivity coefficient; Indicates the lowest thermal conductivity; Indicates the limiting thermal conductivity; Indicates the critical pressure constant; Indicates hydraulic clamping; This represents an exponential function with the natural constant e as its base.

[0015] By employing the above technical solution, this invention constructs a temperature-pressure coupled thermal conductivity model and maps mechanical pressure values ​​to an interface thermal conductivity coefficient. This coefficient quantitatively characterizes the physical law that the contact thermal resistance between the mold and the heating plate decreases exponentially with increasing mold closing hydraulic pressure. This allows the control system to automatically identify false low-temperature states caused by insufficient mechanical contact between the mold and the heating plate in the early stages of low-pressure mold closing, thus preventing the control system from misinterpreting this phenomenon as insufficient heat source power and making overheating adjustments. Through this interface thermal conductivity coefficient, this invention successfully decouples the influence of mold closing pressure fluctuations on the initial mold temperature acquisition, improving the accuracy of identifying the process state in the early stages of vulcanization.

[0016] Preferably, in the step of calculating the temperature compensation amount, the temperature compensation amount is linearly superimposed from the reference drift component and the coupling interference component; the reference drift component has a logarithmic growth relationship with the ratio of the ambient temperature inside the electrical control cabinet to the standard reference temperature, which is used to characterize the nonlinear drift characteristics of the semiconductor device reference voltage source as the ambient temperature inside the electrical control cabinet increases; the coupling interference component is proportional to the heat accumulation index and inversely proportional to the interface thermal conductivity coefficient, which is used to characterize the coupling phenomenon where the measurement error is physically amplified when the external thermal conductivity is low and the internal heat accumulation is high.

[0017] Preferably, the temperature compensation amount satisfies the following relationship:

[0018] in, Indicates the current time The calculated temperature compensation amount; Indicates the standard reference temperature constant; This represents the first gain coefficient in the error gain vector; This represents the second gain coefficient in the error gain vector; Indicates the current time The ambient temperature inside the electrical control cabinet; Indicates the current time The heat accumulation index; Indicates the current time The interfacial thermal conductivity coefficient; It is the natural logarithm function.

[0019] By adopting the above technical solution, this invention clarifies the specific mathematical relationships between each variable and parameter, and introduces a standard reference temperature constant to eliminate the dimensional influence in logarithmic calculations, thus ensuring the rigor of the mathematical expression. Simultaneously, by utilizing a recursive least squares algorithm, the first and second gain coefficients can be iteratively updated online based on the residual between the process setpoint and the original mold temperature. This solution ensures that the system can still adaptively calibrate the weights of each component in the temperature compensation amount when facing equipment aging and environmental temperature fluctuations within the control cabinet, thereby maintaining a high-precision temperature reconstruction capability during the operation of the vulcanizing machine.

[0020] Preferably, the iterative process of the recursive least squares algorithm further includes: initializing the covariance matrix, wherein the diagonal elements of the covariance matrix are set to preset large values ​​to maintain high sensitivity to parameter changes in the initial stage; and introducing a forgetting factor to weight the historical data to ensure that the time-varying characteristics of the system can be tracked and the interference of old data can be suppressed.

[0021] Preferably, before calculating the actual temperature, a safety truncation process is performed on the temperature compensation amount: a maximum positive compensation threshold and a maximum negative compensation threshold are set; if the calculated temperature compensation amount exceeds the range of the maximum positive compensation threshold or the maximum negative compensation threshold, the temperature compensation amount is forcibly limited to the corresponding threshold boundary to prevent control instability caused by sensor failure or calculation divergence.

[0022] Preferably, the heating adjustment actuator specifically includes: calculating the difference between the actual temperature and the process set value, and using the difference as a control deviation; using a PID control algorithm to calculate the control deviation and output a duty cycle signal; and controlling the on / off state of a solid-state relay connected in the heating circuit through the duty cycle signal to adjust the heating power.

[0023] This invention provides a temperature and pressure coordinated control optimization system for a vulcanizing machine electrical control cabinet, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the aforementioned temperature and pressure coordinated control optimization method for a vulcanizing machine electrical control cabinet is implemented.

[0024] By adopting the above technical solution, a computer program is generated from the above-mentioned method for optimizing temperature and pressure coordination control of a vulcanizing machine electrical control cabinet, and stored in a memory for loading and execution by a processor. This allows for the creation of terminal equipment based on the memory and processor, making it convenient to use.

[0025] The technical solution of the present invention has the following beneficial technical effects: This invention introduces a multi-source physical state collaborative sensing mechanism to quantitatively assess the environmental thermal response hysteresis effect generated by heat sources inside the electrical control cabinet, as well as the evolution of the interfacial contact thermal resistance between the mold and the heating plate as a function of the mold closing hydraulic pressure. By dynamically constructing a temperature-pressure coupled thermal conductivity model and a heat accumulation index, and combining a recursive least squares algorithm to compensate for nonlinear reference drift and coupling interference in real time, this invention eliminates, from a physical logic perspective, the physical distortion deviation caused by insufficient heat accumulation and mechanical contact inside the electrical control cabinet on the accuracy of the original mold temperature sampling.

[0026] Furthermore, this invention not only decouples the nonlinear physical relationship between contact thermal resistance and mold-closing hydraulic pressure, but also achieves accurate identification and correction of false low-temperature feedback during the low-pressure mold-closing stage through dynamic temperature restoration technology with adaptive weight updates and safety truncation processing. This frees the back-end PID controller from the nonlinear drift sensitivity of the analog acquisition module and the static feedback limitations of a single sensor, enhancing the control stability and dynamic tracking accuracy of the vulcanizing machine temperature control system under complex non-stationary load conditions such as equipment aging and large fluctuations in ambient temperature within the control cabinet, thereby effectively eliminating heating overshoot. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating an optimization method for temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet according to the present invention; Figure 2 This is a schematic diagram of the spatial characterization of the correlation between thermal accumulation and sampling deviation in the electrical control cabinet provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the measured distribution of hydraulic pressure and contact heat conduction performance of the vulcanizing machine according to an embodiment of the present invention; Figure 4 This is a comparative schematic diagram of the improvement in control accuracy under complex variable load conditions provided by the embodiments of the present invention. Detailed Implementation

[0028] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0029] This invention discloses an optimization method for temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet, referring to... Figure 1 This includes steps S1-S4: S1: Real-time acquisition of multi-source physical state parameters of the vulcanizing machine system through industrial communication interface and sensor network. Multi-source physical state parameters include inverter operating current, ambient temperature in the electrical control cabinet, mold closing hydraulic pressure and mold original temperature.

[0030] In an optional embodiment, given that during long-term operation of the vulcanizing machine, heat accumulation inside the electrical control cabinet can cause reference drift in the analog quantity acquisition module, and that the contact thermal resistance between the mold and the heating plate changes nonlinearly with pressure, in order to break through the limitations of traditional temperature control that is only based on a single temperature feedback, the core purpose of this step is to obtain the real-time physical state of the vulcanizing machine through a multi-dimensional sensing network, thereby establishing an accurate data foundation for subsequent dynamic compensation and error decoupling.

[0031] Specifically, the system performs real-time data acquisition on the vulcanizing machine, using sensors distributed at key nodes to measure the electrical, environmental, and mechanical conditions of the equipment from multiple dimensions. Through these measurements, the key physical state parameters acquired by the system mainly include: Inverter operating current The unit is A. This parameter is collected by Hall current sensors installed at the three-phase output terminals of the frequency converter and the effective value of the three-phase current is used to reflect the heating power of the main heat source in the electrical control cabinet. It is the core basis for calculating the heat accumulation index.

[0032] Ambient temperature inside the electrical control cabinet The unit is °C. This parameter is acquired by a DS18B20 digital temperature sensor installed near the PCB of the PLC analog signal acquisition module. It is used to directly monitor the operating environment of the analog-to-digital converter chip and can effectively characterize the degree of deviation of the reference voltage source as the ambient temperature changes.

[0033] Mold closing hydraulic The unit is MPa. It is collected by a pressure transmitter installed on the main hydraulic cylinder oil circuit and outputting a 4-20mA signal. This parameter determines the tightness of the physical interface contact between the mold and the heating plate and is a key variable for determining the interface heat transfer efficiency coefficient.

[0034] Original temperature of mold The unit is ℃. The data was collected by a PT100 platinum resistance thermometer embedded inside the mold. This data is the raw digital quantity that has not been corrected by this algorithm and may contain physical drift errors.

[0035] Thus, by constructing a multi-dimensional physical sensing network, this invention can digitally model the thermal environment inside the electrical control cabinet and the external mechanical contact state in real time, providing complete data support for distinguishing between real temperature changes and sensor measurement interference, and avoiding the control instability problem caused by traditional temperature control relying solely on single temperature feedback.

[0036] S2: Based on the inverter's operating current and thermal memory attenuation factor, a thermal accumulation index is constructed using weighted logic that reflects thermal inertia. The thermal accumulation index is used to evaluate the degree of thermal interference caused by heat sources inside the control cabinet to the analog quantity acquisition module.

[0037] In an optional embodiment, given that heat accumulation inside the electrical control cabinet is a complex dynamic process with thermal inertia, the core objective of this step is to accurately assess the degree of local thermal saturation of the PCB board inside the cabinet. To overcome the limitations of drastic signal fluctuations caused by compensation using only instantaneous current, this embodiment employs an exponentially weighted moving average algorithm to construct the thermal accumulation index. This enables accurate characterization of the thermal response hysteresis characteristics of electronic components.

[0038] Specifically, the heat accumulation index satisfies the following relationship:

[0039] in, Indicates the current time The thermal accumulation index is a dimensionless parameter with a value ranging from 0 to 1. The larger the value of the index, the more severe the thermal accumulation phenomenon inside the electrical control cabinet. The thermal memory decay factor, a dimensionless constant, typically ranges from 0.85 to 0.98. This parameter characterizes the thermal hysteresis characteristics of the cooling system within the electrical control cabinet. Its value is determined by the cooling capacity of the cabinet's fan; the slower the cooling, the larger the value, indicating a stronger memory effect. This range of 0.85 to 0.98 is the optimal engineering application range derived from the inherent rules of the exponentially weighted moving average algorithm in this field, combined with the general industrial operating parameters of vulcanizing machine electrical control cabinets. This range simultaneously satisfies the smoothness and real-time requirements of the thermal accumulation index. Those skilled in the art can determine the appropriate range for specific equipment within the aforementioned range, based on the cooling capacity of the electrical control cabinet, using conventional step response testing and empirical tuning methods. value; The heat accumulation index represents the heat accumulation index of the previous moment. By introducing the heat accumulation index of the previous moment as the benchmark for the current calculation, the system can incorporate the historical thermal state into the current iteration process, thereby reflecting the thermal inertia and time continuity in the heat accumulation process. Indicates the current time The inverter's operating current, measured in amperes, reflects the current moment... The heating power of the main heat-generating components inside the electrical control cabinet; This indicates the rated current of the frequency converter, and its unit is amperes. This value can be obtained from the equipment nameplate. The term represents the square term. According to the physical law that heat generation is proportional to the square of the current in Joule's law, this square term is used to characterize the proportion of the instantaneous heat generated by the inverter's operating current in the maximum heat generation capacity at the current moment. Normalization can keep the dimensions of the instantaneous heat generation intensity consistent with the heat accumulation index.

[0040] Understandably, the construction of the aforementioned thermal accumulation index relationship is based on combining the electrical heating mechanism with the inertial characteristics of thermodynamic systems. First, according to Joule's law, the instantaneous heat generation power inside the electrical control cabinet, especially high-power frequency converters and other electrical components, is proportional to the square of their operating current. Therefore, the model uses the square of the ratio of the frequency converter's operating current to its rated current to quantitatively characterize the instantaneous internal heat source intensity after normalization. Second, considering that heat generation and dissipation within the electrical control cabinet are typical physical processes exhibiting significant first-order hysteresis and other thermal inertial characteristics, a large instantaneous current will not directly cause sudden and drastic temperature fluctuations. Based on this, this invention introduces an exponentially weighted moving average algorithm, using a thermal memory decay factor to simulate the thermal response hysteresis effect caused by the heat transfer process of the cooling system, thereby transforming discrete instantaneous current sampling data into a dynamic dimensionless state variable that can smoothly and continuously reflect the local thermal saturation degree of the circuit board.

[0041] Thus, by constructing a thermal accumulation index, this invention can accurately characterize the thermal response hysteresis characteristics of electronic components under long-term operation. This thermal accumulation index not only considers the current heat generation situation, but also restores the hysteresis effect of the heat dissipation system through the attenuation factor, ensuring the smoothness and physical authenticity of the compensation amount, and avoiding the drastic fluctuations in temperature acquisition data caused by only using instantaneous current for compensation.

[0042] S3: Based on the physical characteristics of the mold clamping hydraulic pressure and the contact interface, a temperature-pressure coupled thermal conductivity efficiency model is constructed. The interface thermal conductivity efficiency coefficient under the current state is determined by the temperature-pressure coupled thermal conductivity efficiency model to characterize the nonlinear characteristics of the contact thermal resistance between the mold and the heating plate as a function of pressure.

[0043] In an optional embodiment, given that heat is transferred between the heating plate of the vulcanizing machine and the mold through mechanical contact, and that the thermal resistance at the contact interface is not constant but is affected nonlinearly by the hydraulic pressure during mold closing, the core objective of this step is to map the mechanical pressure value into a thermal parameter and define it as the interface thermal conductivity coefficient. This coefficient quantitatively characterizes the physical law that the contact thermal resistance decreases exponentially with increasing pressure, ultimately achieving effective decoupling of the impact of pressure fluctuations on the initial temperature acquisition of the mold.

[0044] Specifically, the interfacial heat transfer efficiency coefficient satisfies the following relationship:

[0045] in, Indicates the current time The interfacial thermal conductivity coefficient is a dimensionless parameter, and its value is set between the minimum thermal conductivity and the limiting thermal conductivity. This coefficient is used to characterize the nonlinear characteristic of thermal conductivity increasing exponentially with increasing pressure. This represents the minimum thermal conductivity, which is the thermal conductivity of the mold when it is in contact solely by its own weight and the hydraulic pressure during mold closing is close to zero. This value is obtained experimentally. This represents the limiting thermal conductivity, which is the thermal conductivity of the mold and the heating plate under fully compressed conditions. This value is obtained experimentally. This represents the critical pressure constant, and its unit is MPa. This indicates the clamping hydraulic pressure, measured in MPa. This parameter determines the tightness of the contact between the mold and the heating plate. This represents an exponential function with the natural constant e as its base.

[0046] Understandably, the above formula for the interfacial heat transfer efficiency coefficient is based on its deep integration of mechanical micro-contact mechanics and interfacial heat transfer theory. In the initial stage of mold closing in a vulcanizing machine, the presence of numerous microscopic protrusions on the initial physical contact surface between the mold and the heating plate results in a true contact area far smaller than the nominal geometric area, leading to extremely high thermal resistance at the contact interface. As the closing hydraulic pressure gradually increases, the microscopic protrusions on the contact surface undergo elastoplastic deformation and are gradually flattened, causing the true contact area to increase nonlinearly. This area eventually reaches physical saturation at the critical yield state. Therefore, the microscopic thermal resistance of the contact interface exhibits an exponential decay trend with increasing pressure. Correspondingly, this model, by introducing the critical pressure constant and the limiting thermal conductivity, constructs a mapping evolution model of the inverse exponential saturation growth characteristic of interfacial heat transfer efficiency with hydraulic pressure changes, thereby achieving precise decoupling of the influence of unsteady pressure fluctuations on interfacial heat transfer efficiency.

[0047] Thus, by constructing a temperature-pressure coupled thermal conductivity efficiency model and introducing an interfacial thermal conductivity efficiency coefficient, this invention enables the control system to automatically identify false low-temperature states caused by insufficient contact during the low-pressure mold closing stage, thereby avoiding overheating problems caused by pressure fluctuations.

[0048] It should be noted that the method for obtaining the critical pressure constant includes: under constant heat input conditions, controlling the mold clamping hydraulic pressure to increase stepwise according to a preset gradient, recording the temperature response curve of the mold under each pressure gradient in real time, and extracting sample values ​​of equivalent thermal conduction delay or relative thermal conduction efficiency corresponding to different pressures; subsequently, using the least squares fitting algorithm, substituting the above multiple sets of sample values ​​into the interface heat conduction efficiency coefficient formula for nonlinear regression calculation, with the goal of minimizing the sum of squared residuals between the measured efficiency and the model calculated efficiency, and solving in reverse to obtain the optimal critical pressure constant; physically speaking, this constant characterizes the critical pressure characteristic of the interface contact thermal resistance entering the rapid saturation stage as the pressure increases. Its value is affected by the roughness of the mold contact surface and the hardness of the material. The recommended calibration value range under typical working conditions is usually 5.0MPa to 12.0MPa, thereby ensuring that the model can accurately decouple the nonlinear interference of pressure fluctuations on the original temperature acquisition of the mold.

[0049] S4: Using the ambient temperature, heat accumulation index and interface heat transfer efficiency coefficient inside the electrical control cabinet, combined with the recursive least squares algorithm, the error gain vector is estimated in real time through iteration to calculate the temperature compensation amount. The original temperature of the mold is corrected using the temperature compensation amount to obtain the true temperature. The controller adjusts the heating actuator according to the deviation between the true temperature and the process setting value.

[0050] In an optional embodiment, given that static model parameters are difficult to adapt to equipment aging and fluctuations in ambient temperature within the electrical control cabinet, the core objective of this step is to estimate the error gain vector online using a recursive least squares algorithm, and then synthesize and calculate the temperature compensation amount based on this error gain vector. By calculating the residuals and updating the gain vector in real time, the system can adaptively calibrate the weights of the reference drift component and the coupled interference component in the temperature compensation amount, thereby maintaining a high-precision temperature reconstruction capability.

[0051] Furthermore, in the process of estimating the error gain vector online using the recursive least squares algorithm, the system first performs an initialization operation. Specifically, the system initializes the covariance matrix and sets the diagonal elements of the covariance matrix to preset large values. This setting ensures that the system remains highly sensitive to subtle changes in parameters during the initial iteration phase, thereby achieving rapid convergence of the first and second gain coefficients. In addition, to effectively address the non-stationary characteristics caused by equipment aging and environmental fluctuations, this invention introduces a forgetting factor during the iteration process. By using the forgetting factor to perform weighted attenuation processing on historical data, the system can prioritize the current measurement state, thereby tracking the time-varying characteristics of the system in real time and suppressing the interference of outdated data on the current compensation accuracy.

[0052] Specifically, the temperature compensation amount satisfies the following relationship:

[0053] in, Indicates the current time The calculated temperature compensation amount is in °C. This represents the standard reference temperature constant, which is used to eliminate the dimensions within the logarithmic function, ensuring the rigor of the mathematical expression. The first gain coefficient in the error gain vector is represented by ℃. This first gain coefficient is updated online by the recursive least squares algorithm based on the residual between the target process temperature and the original mold temperature. This represents the second gain coefficient in the error gain vector, with the unit being °C. This second gain coefficient is also updated online by the recursive least squares algorithm based on the residual between the target process temperature and the original mold temperature. Indicates the current time The ambient temperature inside the electrical control cabinet; Indicates the current time The heat accumulation index; Indicates the current time The interfacial thermal conductivity coefficient; It is the natural logarithm function.

[0054] Understandably, the above temperature compensation formula is constructed considering that the temperature sampling error is caused by the combined effect of temperature drift within the electrical control cabinet and external thermal conduction resistance. This model employs a linear superposition architecture with multi-physics decoupling. The first term of the formula is based on semiconductor physics principles. The carrier mobility and forward voltage drop of the bandgap reference voltage source inside the analog acquisition module typically exhibit nonlinear temperature drift characteristics in logarithmic or approximately logarithmic form as the ambient temperature changes. Therefore, a logarithmic function is used to fit the ratio of the ambient temperature to the standard reference temperature. The second term of the formula is based on the physical mechanism of measurement error amplification. When the heat accumulation inside the electrical control cabinet (the numerator) is higher, the intensity of the reference interference source increases accordingly. Conversely, if the thermal conduction efficiency of the external mold interface (the denominator) is lower, it will lead to obstruction of real heat transfer and severe measurement lag, resulting in a nonlinear amplification effect from internal electrical interference. Therefore, this model uses a ratio of division to characterize this error amplification phenomenon caused by temperature-pressure coupling and combines it with an error gain vector to achieve adaptive calibration.

[0055] After calculating the temperature compensation amount, the original temperature of the mold is corrected using the temperature compensation amount, and the restored true temperature satisfies the following relationship:

[0056] in, This represents the true temperature restored after dynamic compensation, and its unit is °C. This indicates the original temperature of the mold directly obtained through the sensor network, and its unit is ℃; Indicates the current time The calculated temperature compensation amount is expressed in °C.

[0057] Furthermore, the online iterative update process of the first and second gain coefficients is as follows: The system pre-identifies the isothermal steady-state stage of the vulcanization process. During this stage, the output power of the heating actuator and the heat dissipation power reach a dynamic balance. At this time, the transient residuals generated by the PID dynamic adjustment are eliminated, and the static deviation between the original mold temperature after low-pass filtering and the process setpoint is used as the observation input of the recursive least squares algorithm. Simultaneously, a physical mechanism residual constraint is introduced, that is, a prediction deviation model is constructed using the current ambient temperature of the electrical control cabinet and the heat accumulation index. The recursive least squares algorithm achieves adaptive correction of the first and second gain coefficients by minimizing the residual between the prediction error of the physical model and the compensation amount of the gain vector synthesis. This ensures that the system only compensates for the nonlinear drift generated by the sensor chain, while retaining the real physical temperature difference caused by load disturbances, thus avoiding the compensation paradox in closed-loop control.

[0058] Furthermore, to ensure the stability of the control system, this invention performs a safety cutoff process before correcting the original mold temperature using the temperature compensation amount. Specifically, the system pre-sets a maximum positive compensation threshold and a maximum negative compensation threshold. Those skilled in the art can determine the maximum positive and maximum negative compensation thresholds based on the extreme temperature drift range of the temperature measurement system and the allowable temperature deviation of the vulcanization process, ensuring that the thresholds cover the compensation range under normal operating conditions while shielding abnormal compensation amounts caused by sensor malfunctions or algorithm divergence. In each calculation cycle, the system compares the real-time calculated temperature compensation amount with the aforementioned thresholds. If the calculated temperature compensation amount exceeds the safe range defined by the maximum positive and maximum negative compensation thresholds, the system will forcibly limit the temperature compensation amount to the corresponding threshold boundary. This technique effectively prevents abnormal compensation amounts caused by sudden sensor malfunctions, circuit breaks, or divergence in the recursive least squares algorithm, thereby avoiding instability in the control system.

[0059] After obtaining the true temperature, the controller further performs heating adjustment operations. Specifically, the system calculates the difference between the true temperature and the preset process setpoint in real time, and uses this difference as the control deviation. Subsequently, the controller uses a proportional-integral-derivative (PID) control algorithm to perform closed-loop calculations on the control deviation and outputs a corresponding duty cycle signal. This duty cycle signal is used to control the on / off state of the solid-state relay connected in the heating circuit to adjust the heating power. This process ensures that the true temperature of the mold can smoothly converge to the process setpoint.

[0060] Thus, through dynamic compensation using the recursive least squares algorithm and safety truncation processing, this invention can effectively eliminate measurement noise introduced by the electrical control cabinet environment and contact status in real time, thus restoring the true process temperature. Simultaneously, by employing a PID control algorithm to achieve closed-loop regulation, it ensures that the mold temperature can smoothly converge to the process setpoint, significantly improving the temperature control accuracy and stability of the vulcanization process.

[0061] Figure 2 This paper presents the characterization space of the correlation between thermal accumulation in the electrical control cabinet and sampling deviation. The figure shows a three-dimensional fitted surface constructed from numerous experimentally collected sample points, clearly revealing the complex nonlinear relationship between the inverter operating current percentage, the ambient temperature inside the electrical control cabinet, and the reference drift component. It can be observed from the figure that as the inverter operating current percentage increases and the ambient temperature inside the electrical control cabinet rises, the reference drift component exhibits a significant upward trend due to the temperature drift characteristics of the semiconductor device reference source. This provides a solid physical mechanism support for the temperature compensation model constructed in this invention and proves the feasibility of predicting measurement deviation by monitoring the ambient temperature and thermal accumulation index inside the cabinet.

[0062] Figure 3 This paper presents the measured distribution of the hydraulic pressure and contact heat transfer performance of a vulcanizing machine's mold closing system. The figure includes measured points of interfacial thermal properties, a theoretical heat transfer trend line, and the confidence interval of the physical heat transfer model. Experimental data shows that the interfacial heat transfer efficiency coefficient exhibits an exponential saturation increase with increasing mold closing hydraulic pressure. The critical pressure constant is specifically marked in the figure. When the mold closing hydraulic pressure is below this critical point, the interfacial heat transfer efficiency coefficient is low and fluctuates significantly, easily leading to a noticeable hysteresis in the temperature collected by the sensor. This invention, by constructing a temperature-pressure coupled heat transfer efficiency model, can accurately cover the nonlinear characteristics shown in the figure, thereby effectively identifying false low-temperature states during the low-pressure mold closing stage.

[0063] Figure 4 This paper demonstrates a comparison of the improved control accuracy of the dynamic compensation optimization scheme of this invention compared to the traditional fixed-gain control method under complex variable load conditions. The figure defines the high-quality vulcanization process window, which lies within a very small deviation range around 170℃. During the dramatic temperature fluctuations between 350s and 600s during vulcanization, the traditional fixed-gain control method, unable to recognize changes in ambient heat accumulation and contact thermal resistance, exhibits a sharp drop and overshoot in the actual temperature, significantly deviating from the process window. In stark contrast, the control curve using the dynamic compensation optimization scheme of this invention closely matches the process setpoint throughout the entire operation cycle, remaining stable within the high-quality vulcanization process window. Experimental results verify that this invention, through temperature and pressure coordinated control optimization, can effectively eliminate complex interferences and improve the stability and accuracy of temperature control.

[0064] This invention also discloses a temperature and pressure coordinated control optimization system for a vulcanizing machine electrical control cabinet, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, a temperature and pressure coordinated control optimization method for a vulcanizing machine electrical control cabinet according to the present invention is implemented.

[0065] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0066] While this specification has shown and described various embodiments of the invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in the practice of this invention.

Claims

1. A method for optimizing temperature and pressure coordinated control of a vulcanizing machine's electrical control cabinet, characterized in that, include: The vulcanizing machine system acquires multi-source physical state parameters in real time through industrial communication interfaces and sensor networks. These multi-source physical state parameters include inverter operating current, ambient temperature inside the electrical control cabinet, mold closing hydraulic pressure, and mold original temperature. Based on the inverter operating current and thermal memory attenuation factor, a thermal accumulation index is constructed using weighted logic that reflects thermal inertia. The thermal accumulation index is used to evaluate the degree of thermal interference caused by the heat source inside the electrical control cabinet to the analog quantity acquisition module. Based on the physical characteristics of the mold clamping hydraulic pressure and the contact interface, a temperature-pressure coupled thermal conductivity efficiency model is constructed. The interface thermal conductivity efficiency coefficient under the current state is determined by the temperature-pressure coupled thermal conductivity efficiency model to characterize the nonlinear characteristics of the contact thermal resistance between the mold and the heating plate as a function of pressure. Using the ambient temperature, heat accumulation index and interface heat transfer efficiency coefficient inside the electrical control cabinet, and combining the recursive least squares algorithm to iteratively estimate the error gain vector in real time, the temperature compensation amount is calculated. The original temperature of the mold is then corrected using the temperature compensation amount to obtain the true temperature. The controller adjusts the heating actuator according to the deviation between the true temperature and the process setting value. In the step of calculating the temperature compensation amount, the temperature compensation amount is linearly superimposed from the reference drift component and the coupling interference component; the reference drift component has a logarithmic growth relationship with the ratio of the ambient temperature inside the electrical control cabinet to the standard reference temperature, which is used to characterize the nonlinear drift characteristics of the semiconductor device reference voltage source as the ambient temperature inside the electrical control cabinet increases; the coupling interference component is proportional to the heat accumulation index and inversely proportional to the interface thermal conductivity coefficient, which is used to characterize the coupling phenomenon in which the measurement error is physically amplified when the external thermal conductivity is low and the internal heat accumulation is high.

2. The method for optimizing temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet according to claim 1, characterized in that, In the step of acquiring multi-source physical state parameters, the inverter operating current is acquired by a Hall current sensor installed at the three-phase output terminal of the inverter; the ambient temperature inside the electrical control cabinet is acquired by a temperature sensor arranged near the PCB board of the analog quantity acquisition module; the mold closing hydraulic pressure is acquired by a pressure transmitter on the oil circuit of the main hydraulic cylinder of the vulcanizing machine; and the original mold temperature is the original digital quantity obtained by a thermal resistor embedded inside the mold.

3. The method for optimizing temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet according to claim 1, characterized in that, The heat accumulation index satisfies the following relationship: in, Indicates the current time The heat accumulation index; Indicates the thermal memory decay factor; This represents the heat accumulation index at the previous moment; Indicates the current time The inverter's operating current; This indicates the rated current of the frequency converter.

4. The method for optimizing temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet according to claim 1, characterized in that, The interface thermal conductivity coefficient satisfies the following relationship: in, Indicates the current time The interfacial thermal conductivity coefficient; Indicates the lowest thermal conductivity; Indicates the limiting thermal conductivity; Indicates the critical pressure constant; Indicates hydraulic clamping; This represents an exponential function with the natural constant e as its base.

5. The method for optimizing temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet according to claim 1, characterized in that, The temperature compensation amount satisfies the following relationship: in, Indicates the current time The calculated temperature compensation amount; Indicates the standard reference temperature constant; This represents the first gain coefficient in the error gain vector; This represents the second gain coefficient in the error gain vector; Indicates the current time The ambient temperature inside the electrical control cabinet; Indicates the current time The heat accumulation index; Indicates the current time The interfacial thermal conductivity coefficient; It is the natural logarithm function.

6. The method for optimizing temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet according to claim 1, characterized in that, The recursive least squares algorithm further includes, through iteration: initializing the covariance matrix, wherein the diagonal elements of the covariance matrix are set to preset large values ​​to maintain high sensitivity to parameter changes in the initial stage; and introducing a forgetting factor to weight historical data to ensure that the time-varying characteristics of the system can be tracked and the interference of old data can be suppressed.

7. The method for optimizing temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet according to claim 5, characterized in that, Before calculating the actual temperature, a safety truncation process is also included for the temperature compensation amount: a maximum positive compensation threshold and a maximum negative compensation threshold are set; if the calculated temperature compensation amount exceeds the range of the maximum positive compensation threshold or the maximum negative compensation threshold, the temperature compensation amount is forcibly limited to the corresponding threshold boundary to prevent control instability caused by sensor failure or calculation divergence.

8. The method for optimizing temperature and pressure coordinated control of a vulcanizing machine electrical control cabinet according to claim 1, characterized in that, The heating adjustment actuator specifically includes: calculating the difference between the actual temperature and the process set value, and using this difference as a control deviation; using a PID control algorithm to calculate the control deviation and output a duty cycle signal; and controlling the on / off state of a solid-state relay connected in the heating circuit through the duty cycle signal to adjust the heating power.

9. A temperature and pressure coordinated control optimization system for a vulcanizing machine electrical control cabinet, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement a temperature and pressure coordinated control optimization method for a vulcanizing machine electrical control cabinet according to any one of claims 1-8.

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