A control system for an energy-saving cable extrusion production process

Abstract

The present application relates to cable production and automation control technical field, concretely is a kind of control system of energy-saving cable extrusion production process, comprising: data acquisition module, obtains the real-time working condition parameter of extrusion production line;Rheological thermal coupling analysis module, solve the shear heat contribution rate under current working condition;Thermal-mechanical response decoupling module, determine the thermal-mechanical response lag time difference between mechanical shear heat and cylinder heat conduction;Energy efficiency optimization calculation module, configured to generate dynamic thermal balance control strategy for non-steady state condition according to the thermal-mechanical response lag time difference and the preset unit output specific energy consumption target;Adaptive execution module, configured to output the coordinated control instruction of heating and cooling system and screw drive system based on the dynamic thermal balance control strategy, to realize the minimization of system energy consumption;The present application solves the energy confrontation phenomenon of common heating and cooling alternate operation in traditional control, greatly reduces the energy consumption of transition process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cable production and automation control, in particular to a control system for energy-saving cable extrusion production process. BACKGROUND

[0002] In the current cable extrusion production field, as the core processing equipment, the energy efficiency of the extruder is closely related to the resistance energy consumption of the barrel heating system and the mechanical work conversion of the screw driving system. During the extrusion process, the high molecular material will generate significant viscous dissipation heat under the action of screw shearing. This internal heat generation fluctuates dynamically with the changes of material flow characteristics, screw speed and process temperature.

[0003] To achieve temperature control in the extrusion process, the existing scheme generally uses an independent control architecture based on a conventional PID algorithm, that is, the barrel temperature ring and the screw speed ring are decoupled. Although this scheme has certain temperature control ability in the steady state running scene, it fails to establish a coupled quantitative model of mechanical shear heat and external compensation heat, and ignores the time phase difference between the rapidly changing mechanical energy input and the slowly responding medium heat conduction, resulting in energy confrontation phenomenon of alternating operation of electric heating and forced cooling in non-steady state conditions such as start-up speed-up and rule change speed-down. In addition, the existing strategy lacks effective adaptive compensation mechanism for environmental temperature difference interference and material batch fluctuation, often causing excessive heat supply, melt temperature overshoot and decline of product outer diameter size stability. Therefore, how to realize precise decoupling of thermal machine response in the extrusion process and improve system energy efficiency through deep optimization of energy structure while ensuring product quality constraints has become a technical problem to be solved. SUMMARY

[0004] To solve the above technical problems, the present application provides a control system for energy-saving cable extrusion production process. Specifically, the technical scheme of the present application comprises:

[0005] A data acquisition module configured to obtain real-time working condition parameters of the extrusion production line and call preset material flow characteristic data, the real-time working condition parameters including screw speed, barrel temperature in each zone, melt temperature, main motor power, extrusion flow and environmental temperature;

[0006] A rheological heat coupling analysis module configured to calculate the shear heat contribution rate under the current working condition based on the screw speed, the material flow characteristic data and the main motor power;

[0007] A thermal machine response decoupling module configured to determine the thermal machine response lag time difference between mechanical shear heat and barrel heat conduction according to the shear heat contribution rate and a preset system thermal inertia model;

[0008] An energy efficiency optimization calculation module is configured to generate a dynamic thermal balance control strategy for a non-steady state working condition according to the thermal machine response lag time difference and a preset unit output specific energy consumption target;

[0009] An adaptive execution module is configured to output a coordinated control instruction for the heating and cooling system and the screw driving system based on the dynamic thermal balance control strategy, so as to minimize the system energy consumption.

[0010] Preferably, based on the screw rotation speed, the material rheological property data and the main motor power, a shear heat contribution rate under the current working condition is calculated, including:

[0011] The screw rotation speed and the material rheological property data are called;

[0012] A viscous dissipation model based on the non-Newtonian fluid property is constructed to calculate the internal heat power converted by mechanical friction;

[0013] The ratio of the internal heat power to the total enthalpy change power required in the melting process is calculated to generate a shear heat contribution rate representing the proportion of mechanical energy converted into heat energy.

[0014] Preferably, according to the shear heat contribution rate and a preset system thermal inertia model, a thermal machine response lag time difference between mechanical shear heat and barrel heat conduction is determined, including:

[0015] The time sequence fluctuation frequency feature of the shear heat contribution rate is extracted;

[0016] A preset system thermal inertia model is called to obtain the heat conduction time constant of the barrel heating and cooling system;

[0017] By comparing the fluctuation frequency feature with the heat conduction time constant, the thermal machine response lag time difference between the melt temperature change caused by screw rotation speed adjustment and the barrel wall temperature response is calculated.

[0018] Preferably, according to the thermal machine response lag time difference and a preset unit output specific energy consumption target, a dynamic thermal balance control strategy for a non-steady state working condition is generated, including:

[0019] The thermal machine response lag time difference is called;

[0020] During the non-steady state stage of the production line in the speed-up or speed-down state, the melt temperature overshoot at the future time is predicted based on a model predictive control algorithm;

[0021] A target function is constructed with the minimization of the unit output specific energy consumption as the core and the melt temperature deviation as a soft constraint penalty term, and an optimal heating power compensation value within the thermal machine response lag time difference is reversely solved to generate a dynamic thermal balance control strategy.

[0022] Preferably, the generation process of the dynamic thermal balance control strategy further comprises process capability index constraint logic:

[0023] Real-time monitoring of the statistical distribution state of the product key geometry;

[0024] Calculate the current process capability index;

[0025] Determine the relationship between the process capability index and the preset quality threshold:

[0026] If the process capability index is lower than the quality threshold, generate a size stability priority signal, modify the optimal heating power compensation value, and generate a size priority control strategy that guarantees product size stability as a priority;

[0027] If the process capability index is higher than or equal to the quality threshold, generate an energy efficiency priority signal and maintain the generation of a dynamic thermal balance control strategy targeting optimal energy efficiency.

[0028] Preferably, the system further comprises an environmental disturbance compensation module configured to:

[0029] Real-time acquisition of the ambient temperature;

[0030] Calculate the correlation between the ambient temperature change and the barrel heat dissipation rate, and generate an environmental thermal influence coefficient;

[0031] Input the environmental thermal influence coefficient as a feedforward variable into the energy efficiency optimization calculation module to modify the dynamic thermal balance control strategy to offset external heat exchange disturbances.

[0032] Preferably, the rheological thermal coupling analysis module further comprises a material property self-learning unit configured to:

[0033] Record the actual pressure, flow rate, and temperature correspondence data during the production process;

[0034] Use the correspondence data to correct the pre-stored material rheological property data online;

[0035] Update the rheological model parameters used to calculate the shear heat contribution rate to adapt to the physical property fluctuations of different batches of materials.

[0036] Preferably, the adaptive execution module outputs a cooperative control instruction, specifically including:

[0037] Decompose the total thermal energy demand into mechanical shear heat component and resistance heating component;

[0038] Under the premise of ensuring that the total thermal energy demand meets the melting conditions, adjust the screw rotation speed to increase the proportion of the mechanical shear heat component;

[0039] The set value of the resistance heating component is reduced synchronously, and a cooling or heating suppression command is sent in advance based on the time difference of the thermodynamic response to prevent temperature overshoot.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. This invention achieves precise coupling of thermomechanical response and optimizes the energy supply structure. The system breaks the traditional separation of temperature and velocity loops in control. By establishing a rheological-thermal coupling analysis mechanism, the unmeasurable mechanical shear heat generation is transformed into an explicit control variable. This enables the system to accurately identify the contribution of the endogenous heat generated by the screw rotation to the total thermal energy. Thus, while ensuring the quality of the melt, it maximizes the use of mechanical energy to replace the high-energy-consuming resistance heating, solving the problem of power waste caused by unreasonable energy structure.

[0042] 2. This invention eliminates energy consumption conflicts in unsteady-state operating conditions and improves dynamic control accuracy. By introducing a thermo-mechanical response decoupling module, the system can accurately capture the time misalignment between rapidly changing mechanical energy input and slow-responding medium heat conduction. In unsteady-state phases such as start-up acceleration or deceleration during speed change, the system uses predictive control algorithms to adjust the heating power in advance, cleverly utilizing the upcoming shear heat filling heat demand. This solves the energy conflict phenomenon of alternating heating and cooling operation commonly seen in traditional control, and significantly reduces energy consumption during the transition process.

[0043] 3. This invention constructs a quality constraint protection wall to balance energy efficiency and product precision. The system introduces constraint logic based on process capability index, which monitors the statistical distribution of product dimensions in real time while pursuing optimal energy efficiency. This self-checking mechanism can dynamically switch control priorities according to production stability: aggressive energy saving when the process is stable, and automatic degradation to a high-precision constant temperature mode to prioritize product qualification rate when there are fluctuations. This ensures that the energy-saving strategy does not sacrifice product dimension stability, greatly enhancing the robustness of the system in actual industrial environments.

[0044] 4. This invention possesses full environmental adaptability, ensuring stable long-term operation; the system integrates environmental disturbance compensation and material property self-learning functions, which can automatically offset the impact of seasonal temperature differences or diurnal fluctuations on barrel heat dissipation, and correct rheological calculation deviations caused by fluctuations in the physical properties of different batches of raw materials online; this closed-loop evolution capability solves the control failure problem caused by preset data distortion, ensures the continuous accuracy of shear heat calculation, and enables the system to maintain a highly efficient and stable operating state under different production environments and raw material conditions. Attached Figure Description

[0045] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0046] Figure 1 This is a structural diagram of the system of the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0048] Example 1:

[0049] Please see Figure 1 A control system for an energy-saving cable extrusion production process includes:

[0050] The data acquisition module is configured to acquire real-time operating parameters of the extrusion production line and call preset material rheological property data. The real-time operating parameters include: screw speed, temperature of each zone of the barrel, melt temperature, main motor power, extrusion flow rate and ambient temperature.

[0051] The rheological-thermal coupling analysis module is configured to calculate the shear heat contribution rate under the current working condition based on the screw speed, the material rheological property data, and the main motor power.

[0052] The thermomechanical response decoupling module is configured to determine the thermomechanical response lag time difference between mechanical shear heat and barrel heat conduction based on the shear heat contribution rate and the preset system thermal inertia model.

[0053] The energy efficiency optimization calculation module is configured to generate a dynamic thermal balance control strategy for unsteady-state conditions based on the heat engine response lag time difference and a preset unit output energy consumption target.

[0054] The adaptive execution module is configured to output coordinated control commands to the heating and cooling system and the screw drive system based on the dynamic thermal balance control strategy, so as to minimize the system energy consumption.

[0055] This embodiment details the hardware architecture and data flow logic of the control system. The system relies on an industrial PC or PLC as the core computing carrier and constructs a high-frequency communication link through Profinet or EtherCAT bus. The data acquisition module obtains raw data from the field sensor group through a high-frequency sampling interface, for example, with a period of 100ms. Among them, the screw speed comes from the pulse feedback of the rotary encoder, the temperature of each zone of the barrel and the melt temperature come from the thermocouple array arranged in the key temperature zone, the main motor power comes from the communication message of the frequency converter, the extrusion flow rate comes from the real-time reading of the meter weight controller or metering pump, and the ambient temperature is collected by an externally deployed temperature sensor.

[0056] On this basis, the system calls the material rheological property data of the batch of cable materials from the association database, mainly including the mapping curve of shear rate and viscosity; the rheological heat coupling analysis module introduces the above physical quantities into the rheological model, aiming to quantify the unmeasurable mechanical heat generation; the thermal-mechanical response decoupling module identifies the time misalignment between the fast-changing mechanical energy input and the slow-response medium heat conduction; the energy efficiency optimization calculation module no longer simply pursues the constant temperature, but searches for the lowest energy consumption point under the premise of meeting the process window; the adaptive execution module converts the strategy into specific voltage or frequency instructions and distributes them to the heating ring, fan and motor driver;

[0057] The embodiment constructs a control architecture based on the rheological heat coupling mechanism. In the cable extrusion scene, the system breaks the fragmented state of the temperature ring and the speed ring in the traditional PID control; by quantifying the shear heat in real time and introducing thermal-mechanical response decoupling, the system can accurately identify the contribution of the internal heat generated by screw rotation to the total heat energy demand, thereby maximizing the use of mechanical energy to replace expensive electric heating energy and optimizing the energy structure under the premise of ensuring the quality of the melt.

[0058] Embodiment 2:

[0059] Based on the screw rotation speed, the material rheological property data and the main motor power, the shear heat contribution rate under the current working condition is calculated, including:

[0060] The screw rotation speed and the material rheological property data are called;

[0061] A viscous dissipation model based on the non-Newtonian fluid characteristics is constructed to calculate the internal heat power converted by mechanical friction;

[0062] The ratio of the internal heat power to the total enthalpy power required in the melting process is calculated to generate the shear heat contribution rate representing the proportion of mechanical energy converted into heat energy.

[0063] The embodiment materializes the quantitative calculation process of mechanical shear heat, aiming to convert the implicit mechanical friction heat into an explicit control variable; the system calls the screw rotation speed and the material rheological property data including the consistency coefficient and the power-law index ; a viscous dissipation model based on the non-Newtonian fluid characteristics is constructed to calculate the internal heat power converted by mechanical friction , and the calculation formula is as follows:

[0064]

[0065] wherein, : derived from calculation, the physical meaning is the effective shear viscosity under the current shear rate, the unit is Pa·s, and the specific calculation is based on the power-law equation:

[0066]

[0067] wherein, is the consistency factor of the material, is the non-Newtonian index, both are called from the pre-set rheological property database;

[0068] : derived from the calculated value based on screw geometry size and rotational speed, the physical meaning is the equivalent shear rate, the unit is 1 / s; the calculation formula is ;

[0069] wherein, is the diameter of the screw homogenization section, is the screw channel depth of the homogenization section, is the screw rotational speed, the unit is r / s when calculating;

[0070] : derived from the pre-set equipment parameters, the physical meaning is the effective volume of the screw homogenization section, the unit is ;

[0071] : derived from the correction value based on the comparison of the main motor power and the theoretical shaft power, the physical meaning is the conversion efficiency coefficient of mechanical energy into heat energy, dimensionless; the system calculates the ratio of the internal heat power to the total enthalpy power required by the melting process, generates the shear heat contribution rate , the formula is as follows:

[0072]

[0073] wherein, : the mass flow in the denominator, derived from the extrusion mass flow acquisition, the unit is kg / s;

[0074] : derived from the material thermal physical property parameters, the physical meaning is the specific heat capacity, the unit is J / (kg·°C), this place adopts Joule unit to ensure that the power unit of the molecular term is watt, to keep the same dimension;

[0075] : derived from the feeding port sensor acquisition, the physical meaning is the initial temperature of the material, the unit is °C; this calculation process outputs the proportion of the heat contribution of mechanical energy to the melting of the material in real time;

[0076] The embodiment realizes accurate measurement of passive heat generation in continuous extrusion production scene by constructing a refined viscous dissipation model; this technical means enables the control system to clearly distinguish between active electric heating demand and passive mechanical heat surplus, thereby providing a quantitative basis for replacing high-energy electric resistance heating by increasing mechanical shear share without reducing production, and effectively solving the waste caused by excessive cooling due to neglecting shear heat in traditional control.

[0077] Embodiment 3:

[0078] According to the shear heat contribution rate and the preset system thermal inertia model, the thermal-mechanical response lag time difference between the mechanical shear heat and the cylinder heat conduction is determined, including:

[0079] Extracting the time sequence fluctuation frequency characteristics of the shear heat contribution rate;

[0080] Calling the preset system thermal inertia model to obtain the heat conduction time constant of the cylinder heating and cooling system;

[0081] By comparing the fluctuation frequency characteristics and the heat conduction time constant, the thermal-mechanical response lag time difference between the melt temperature change caused by screw speed adjustment and the cylinder wall temperature response is calculated.

[0082] The embodiment further refines the specific algorithm of thermal-mechanical response decoupling, aiming to solve the problem of different synchronization of mechanical action and thermal response in time domain; the system performs fast Fourier transform FFT on the shear heat contribution rate data sequence in the recent time window, extracts the main fluctuation frequency caused by speed adjustment or load fluctuation The specific operator of extracting the main fluctuation frequency is: Wherein is the frequency spectrum amplitude array of the shear heat contribution rate sequence after FFT; the preset system thermal inertia model is called, which includes the cylinder heat conduction time constant measured by step response experiment ; on this basis, the thermal-mechanical response lag time difference is calculated by comparing the fluctuation frequency and the heat conduction characteristics, and the calculation logic is as follows:

[0083]

[0084] Wherein, is an empirical correction coefficient mapped phase lag angle, unit: rad, through this division operator, the frequency domain information is converted to time domain offset, ensuring that the dimensions on both sides of the equation are unified to seconds;

[0085] : derived from pre-set thermodynamic model parameters, physically representing the time constant for heat conduction from the heating element to the inner wall of the barrel and the melt, in s;

[0086] : derived from frequency domain analysis of real-time data, physically representing the dominant frequency of the fluctuation of shear heat input, in Hz;

[0087] : derived from empirical correction coefficients, physically representing the phase correction factor for compensating the non-linear heat diffusion effect, dimensionless; the system outputs this lag time difference as the time reference for subsequent predictive control;

[0088] This embodiment utilizes the combination of frequency domain analysis and thermal inertia model to accurately capture the time misalignment between mechanical energy input and temperature field response in the dynamic variable speed extrusion scene; this technical means not only considers the static heat conduction delay, but also combines the dynamic shear frequency characteristics, so as to accurately predict the exact time of melt temperature rise caused by shear heat, eliminate the risk of temperature overshoot caused by control lag, and greatly improve the control accuracy of non-steady state process.

[0089] Embodiment 4:

[0090] The thermal engine response lag time difference and the pre-set unit output specific energy consumption target generate a dynamic thermal balance control strategy for non-steady state conditions, including:

[0091] Call the thermal engine response lag time difference;

[0092] In the non-steady state stage of the production line in the speed-up or speed-down stage, based on the model predictive control algorithm, predict the melt temperature overshoot at the future time;

[0093] Build a target function with minimizing unit output specific energy consumption as the core, and combine the melt temperature deviation as a soft constraint penalty term, inversely solve the optimal heating power compensation value within the thermal engine response lag time difference, and generate a dynamic thermal balance control strategy.

[0094] This embodiment details the strategy generation process based on model predictive control (MPC) for non-steady state stages such as start-up speed-up and rule change speed-down; the process prediction model built in the model predictive control algorithm is a linear state space model after discretization: , where the state vector is the melt temperature , the control variable is the heating power compensation value, the disturbance term is the shear heat power ; the matrix and the disturbance transfer matrix are derived from the system thermal inertia time constant and shear heat conduction gain is obtained by bilinear transformation, wherein for characterizing the weight of mechanical shear heat on the melt temperature state; the system calls the thermal mechanical response lag time difference calculated in the previous step ; in response to the production line entering the non-steady state stage, the system simulates the change trajectory of the melt temperature based on the process model within the prediction time domain starting from the current time, predicts the potential temperature overshoot; on this basis, a target function is constructed with the core of minimizing the energy consumption per unit output, combined with the melt temperature deviation as a soft constraint penalty term , the formula is as follows:

[0095]

[0096] wherein, : the source is a preset algorithm control parameter, the physical meaning is the step number of the model prediction time domain, and the time span corresponds to the thermal mechanical response lag time difference, which is dimensionless;

[0097] : the source is model prediction calculation, the physical meaning is the energy consumption per unit output at the kth prediction time, and the unit is kWh / kg;

[0098] : the source is process setting, the physical meaning is the ideal energy consumption target value, and the unit is kWh / kg;

[0099] : the source is an adaptive adjustment algorithm, the physical meaning is the weight coefficient of the energy consumption optimization term and the temperature stabilization term, which is dimensionless; wherein the term is a soft constraint penalty factor, which ensures that the energy consumption optimization is carried out within the allowable temperature control accuracy of the process;

[0100] : the source is model prediction calculation, the physical meaning is the melt temperature at the kth prediction time, and the unit is °C;

[0101] : the source is process setting, the physical meaning is the set target value of the melt temperature, and the unit is °C; the system reversely solves the target function to generate a set of optimal heating power compensation value sequences containing the time dimension, the reverse solution adopts a quadratic programming algorithm, under the premise of meeting the upper and lower limit constraints of the heater power, calculates the control sequence that minimizes the target function ; that is, the dynamic thermal equilibrium control strategy;

[0102] ​​The embodiment introduces a forward-looking model predictive control algorithm. In a non-steady state working condition scene, the calculated lag time difference is used as a prediction window. This strategy enables the system to reduce heating power or start micro-cooling in advance when the temperature has not actually changed but the trend has been determined. The mechanical shear heat that will soon arrive is used to fill the heat demand, thereby completely eliminating the common phenomenon of alternating heating and cooling in traditional PID control, and significantly reducing the energy consumption of the transition process.

[0103] Embodiment 5:

[0104] The generation process of the dynamic thermal balance control strategy also includes process capability index constraint logic:

[0105] Real-time monitoring of the statistical distribution state of the key geometric dimensions of the product; calculation of the current process capability index;

[0106] Determine the relationship between the process capability index and the preset quality threshold: if the process capability index is lower than the quality threshold, generate a size stability priority signal, modify the optimal heating power compensation value, and generate a size priority control strategy that prioritizes ensuring the size stability of the product;

[0107] If the process capability index is higher than or equal to the quality threshold, generate an energy efficiency priority signal and maintain the generation of a dynamic thermal balance control strategy that targets optimal energy efficiency.

[0108] The embodiment adds quality constraint logic based on energy efficiency optimization as a firewall to ensure product pass rate; the system monitors the cable outer diameter data fed back by the online diameter gauge in real time and analyzes its distribution state; calculates the current process capability index , the formula is as follows:

[0109]

[0110] : sourced from product specifications, with a physical meaning of upper and lower tolerance limits of product size, in mm;

[0111] : sourced from real-time statistical analysis, with a physical meaning of the mean and standard deviation of the current sample;

[0112] System execution logic judgment: in response to below the preset quality threshold, such as 1.33, indicating that the process fluctuation is large, the system immediately generates a size stability priority signal, and the specific modification logic is: let , and set to more than times the current energy efficiency item nominal value, so that the gradient contribution of the energy efficiency item disappears when the optimization operator is looking for extreme values, and the algorithm degenerates to For the PID equivalent steady-state control of the hard target, the optimal heating power compensation value is modified, the size priority control strategy is generated to ensure the product size stability, and the high-precision constant temperature control is degraded; otherwise, in response to higher than or equal to the threshold value, the system generates an energy efficiency priority signal, and maintains the strategy of optimizing energy efficiency as the target;

[0113] In this embodiment, a statistical process control (SPC) index is introduced as a feedback constraint to build a dynamic trade-off mechanism between extreme energy efficiency and product quality assurance; this self-examination capability ensures that the energy-saving strategy will not sacrifice product pass rate, and when the process is stable, it is aggressive in energy saving, and when it is fluctuating, it is conservative in quality preservation, greatly enhancing the robustness and usability of the system in actual industrial production.

[0114] Embodiment 6:

[0115] The system also includes an environmental disturbance compensation module,

[0116] configured to: collect the ambient temperature in real time;

[0117] calculate the correlation between the ambient temperature change and the cylinder heat dissipation rate, and generate an environmental thermal influence coefficient;

[0118] input the environmental thermal influence coefficient as a feedforward variable into the energy efficiency optimization calculation module, and modify the dynamic thermal balance control strategy to offset external heat exchange disturbances.

[0119] This embodiment describes in detail the compensation mechanism for external environmental disturbances; the system collects the ambient temperature in real time through sensors installed around the equipment ; based on the modified model of Newton's cooling law, the correlation between the ambient temperature change and the cylinder heat dissipation rate is calculated, and an environmental thermal influence coefficient is generated, and the calculation logic is as follows:

[0120]

[0121] : derived from the thermal parameter library, with a physical meaning of natural convection heat transfer coefficient, and a unit of ;

[0122] : derived from the equipment geometric parameters, with a physical meaning of the effective heat dissipation surface area of the cylinder exposed to the environment, and a unit of ;

[0123] : derived from the cylinder wall temperature sensor, with a physical meaning of the cylinder shell temperature, and a unit of °C; the calculated As a feedforward variable directly input to the energy efficiency optimization calculation module, the heat dissipation power change caused by the environment is added or subtracted explicitly when calculating the heating demand, and the dynamic thermal balance control strategy is modified; The specific mathematical implementation of the modification is: in the control output of each cycle of MPC , the feedforward compensation term is directly accumulated , that is , the reverse power compensation is used to offset the heat dissipation loss of the barrel wall caused by the environmental temperature difference;

[0124] The embodiment uses a feedforward compensation mechanism to cope with environmental thermal disturbance. In the production scene across day and night or across seasons, the system can sensitively distinguish whether the barrel temperature fluctuation is caused by internal heat absorption or external environmental heat dissipation. This design effectively avoids excessive cooling shock due to slow heat dissipation in summer and insufficient heating due to fast heat dissipation in winter, significantly improving the adaptability and stability of the control model to environmental changes.

[0125] Embodiment 7:

[0126] The rheological thermal coupling analysis module further comprises a material property self-learning unit,

[0127] configured to record the corresponding relationship data of actual pressure, flow and temperature during the production process;

[0128] using the corresponding relationship data to correct the pre-stored material rheological property data online;

[0129] updating the rheological model parameters used to calculate the shear heat contribution rate to adapt to the physical property fluctuations of different batches of materials.

[0130] The embodiment gives the system the self-adaptive learning ability to the material physical property fluctuation; during the production process, the system continuously records the actual head pressure , extrusion flow and temperature data at a specific speed and temperature, forming a measured data set; using the inversion algorithm to correct the pre-stored material rheological property data online; Specifically, the system calculates the current theoretical pressure value based on the simplified head flow equation , wherein is the head geometry constant; calculate the deviation ratio of the actual pressure and the theoretical pressure ; update the consistency coefficient using the exponential weighted moving average method EWMA, the update formula is:

[0131]

[0132] wherein is the preset learning rate, for example, the value is 0.05, used to smooth the noise; the system will update Real-time writing flow model parameter library for next cycle shear heat contribution rate calculation to adapt to the physical property fluctuations of different batches of materials; Note: to distinguish from the symbols representing power in the previous embodiments , the pressure symbols in this embodiment are represented by ;

[0133] This embodiment solves the calculation deviation problem caused by the distortion of pre-set rheological data in the scenarios of raw material batch replacement or the use of recycled materials through online inversion correction technology; This mechanism gives the system the ability to evolve online, ensuring the continuous accuracy of shear heat calculation, thereby ensuring the reliability of energy efficiency control strategies in long-period operation.

[0134] Embodiment 8:

[0135] The adaptive execution module outputs cooperative control instructions, specifically including: decomposing the total thermal energy demand into mechanical shear heat component and resistance heating component; under the premise of ensuring that the total thermal energy demand meets the melting condition, by adjusting the screw speed to increase the proportion of the mechanical shear heat component; simultaneously reducing the set value of the resistance heating component, and sending cooling or heating suppression instructions in advance according to the thermal-mechanical response lag time difference to prevent temperature overshoot.

[0136] This embodiment details the final execution logic of the control instructions, which is the landing point of achieving energy-saving goals; the system decomposes the calculated total thermal energy demand into a mechanical shear heat component and a resistance heating component ; under the premise of ensuring that the material is completely melted and does not undergo thermal degradation, the system actively fine-tunes to increase the screw speed, aiming to increase the proportion of efficient mechanical shear heat component; the simultaneous reduction of the resistance heating component reduction value satisfies the following energy equivalent mapping relationship: , where is the preset electromechanical thermal conversion efficiency constant ; the system simultaneously reduces the set value of the resistance heating component, and executes timing control according to the aforementioned calculated thermal-mechanical response lag time difference : for example, in response to predicting that shear heat will cause temperature rise in seconds, the system immediately sends a heating suppression instruction at the current time, and pre-starts the fan at low speed at a specific time before arrives to prevent temperature overshoot;

[0137] In actual operation, the embodiment realizes a high energy efficiency operation mode mainly based on internal mechanical self-heating and supplemented by external resistance auxiliary heating by actively reconfiguring the proportion of energy sources; in cooperation with the precise timing control based on time difference, the scheme not only greatly reduces the electric heating energy consumption, but also improves the plasticizing quality by using shear heat, and truly realizes the dual optimization of process and energy efficiency.

[0138] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application rather than limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A control system for an energy-saving cable extrusion production process, characterized in that, include: The data acquisition module is configured to acquire real-time operating parameters of the extrusion production line and call preset material rheological property data. The real-time operating parameters include: screw speed, temperature of each zone of the barrel, melt temperature, main motor power, extrusion flow rate and ambient temperature. The rheological-thermal coupling analysis module is configured to calculate the shear heat contribution rate under the current working condition based on the screw speed, the material rheological property data, and the main motor power. The thermomechanical response decoupling module is configured to determine the thermomechanical response lag time difference between mechanical shear heat and barrel heat conduction based on the shear heat contribution rate and the preset system thermal inertia model. The energy efficiency optimization calculation module is configured to generate a dynamic thermal balance control strategy for unsteady-state operating conditions based on the heat engine response lag time difference and a preset unit output energy consumption target, specifically including: Utilize the aforementioned heat engine response lag time difference; When the production line is in a non-steady-state phase of speed increase or decrease, the melt temperature overshoot is predicted at future moments based on the model predictive control algorithm. A dynamic thermal balance control strategy is generated by constructing an objective function that minimizes the energy consumption per unit output and incorporates the melt temperature deviation as a soft constraint penalty term. The optimal heating power compensation value within the time difference of the thermodynamic response lag is solved in reverse. The adaptive execution module is configured to output coordinated control commands to the heating and cooling system and the screw drive system based on the dynamic thermal balance control strategy, so as to minimize the system energy consumption.

2. The control system for an energy-saving cable extrusion production process according to claim 1, characterized in that, Based on the screw speed, the material rheological property data, and the main motor power, the shear heat contribution rate under the current operating condition is calculated, including: Call the screw rotation speed and the material rheological property data; A viscous dissipation model based on the properties of non-Newtonian fluids is constructed to calculate the internal heat power converted from mechanical friction. The ratio of the internal thermal power to the total enthalpy change power required for the melting process is calculated to generate the shear heat contribution rate, which characterizes the proportion of mechanical energy converted into thermal energy.

3. The control system for an energy-saving cable extrusion production process according to claim 1, characterized in that, Based on the shear heat contribution rate and the preset system thermal inertia model, the thermomechanical response lag time difference between mechanical shear heat and barrel heat conduction is determined, including: Extract the time-series fluctuation frequency characteristics of the shear heat contribution rate; The preset system thermal inertia model is invoked to obtain the heat conduction time constant of the barrel heating and cooling system; By comparing the fluctuation frequency characteristics with the heat conduction time constant, the thermomechanical response lag time difference between the melt temperature change caused by screw speed adjustment and the barrel wall temperature response is calculated.

4. The control system for an energy-saving cable extrusion production process according to claim 1, characterized in that, The generation process of the dynamic thermal balance control strategy also includes process capability index constraint logic: Real-time monitoring of the statistical distribution of key geometric dimensions of the product; Calculate the current process capability index; Determine the relationship between the process capability index and the preset quality threshold: If the process capability index is lower than the quality threshold, a size stability priority signal is generated to correct the optimal heating power compensation value and to prioritize the generation of a size priority control strategy that ensures product size stability. If the process capability index is higher than or equal to the quality threshold, an energy efficiency priority signal is generated to maintain a dynamic thermal balance control strategy aimed at optimal energy efficiency.

5. The control system for an energy-saving cable extrusion production process according to claim 1, characterized in that, The system also includes an environmental disturbance compensation module, configured as follows: The ambient temperature is collected in real time; Calculate the correlation between the ambient temperature change and the heat dissipation rate of the barrel to generate the ambient thermal influence coefficient; The environmental thermal influence coefficient is input as a feedforward variable into the energy efficiency optimization calculation module to modify the dynamic heat balance control strategy in order to offset external heat exchange disturbances.

6. The control system for an energy-saving cable extrusion production process according to claim 1, characterized in that, The rheological-thermal coupling analysis module also includes a material property self-learning unit, configured as follows: Record the actual pressure, flow rate, and temperature correlation data during the production process; The pre-stored material rheological property data are corrected online using the corresponding relationship data; The rheological model parameters used to calculate the shear heat contribution rate are updated to accommodate the property fluctuations of different batches of materials.

7. The control system for an energy-saving cable extrusion production process according to claim 1, characterized in that, The adaptive execution module outputs cooperative control commands, specifically including: The total heat energy demand is decomposed into mechanical shear heat component and resistance heating component. Under the premise of ensuring that the total heat energy demand meets the melting conditions, the proportion of the mechanical shear heat component is increased by adjusting the screw speed; The set value of the resistance heating component is reduced synchronously, and a cooling or heating suppression command is sent in advance based on the time difference of the thermodynamic response to prevent temperature overshoot.

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