Control system and method for an insulation piece production line

Abstract

The application relates to the technical field of production control, in particular to a control system and method for an insulation piece production line.In the application, a perception module collects temperature signals, deformation monitoring signals and viscosity state signals in real time; a main control module generates a fused process state matrix by fusing three signals through time sequence alignment and space registration, constructs and dynamically updates a first current shrinkage dynamic prediction model based on the matrix, material properties and environmental parameters; the model is used to predict the spatial non-uniform shrinkage distribution atlas of a subsequent forming stage; a collaborative regulation instruction set is generated by solving the atlas through a reverse thermal coupling algorithm, the instruction set including temperature compensation instructions, extrusion back pressure and transmission rate collaborative instructions; and an execution module links and controls corresponding actuators according to the instructions, so as to dynamically offset the non-uniform shrinkage power caused by the spatial temperature gradient difference.

Description

Technical Field

[0001] The present invention relates to the technical field of production control, and in particular to a control system and method for an insulation component production line. Background Art

[0002] During the molding and production of insulating parts, mold structural asymmetry and uneven material distribution can cause spatial temperature gradient differences within the insulating parts. This non-uniform thermal field distribution leads to significant spatial differences in the thermal stress accumulation rate and shrinkage direction in different regions, which in turn causes local warping and dimensional deviations in the product. Although existing control technologies have deployed temperature and deformation detection methods, due to the lack of multi-physics field dynamic coupling modeling, it is difficult to establish a real-time mapping relationship between temperature gradient and shrinkage deformation.

[0003] At the same time, the execution unit based on fixed temperature zone adjustment has the problem of insufficient spatial resolution. Its coarse-grained partitioned temperature control mechanism cannot match the refined thermal gradient evolution morphology. In addition, the dynamic impact of viscosity changes on the contraction process is not included in the real-time control closed loop, resulting in compensation instructions lagging in the time dimension and mismatching in the spatial dimension, which ultimately aggravates the local deformation control deviation. Summary of the Invention

[0004] The present invention is directed to a control system and method for an insulation component production line to address the aforementioned technical issues, including the problem of deformation control deviation caused by spatial temperature gradient differences during the insulation component molding process.

[0005] To achieve the above objectives, one of the objectives of the present invention is to provide a control system for an insulation component production line, comprising a sensing module, a main control module, and an execution module, wherein:

[0006] The perception module collects temperature distribution and changes at different positions of the insulating parts through the temperature sensor array installed in the mold area and near the conveyor belt of the production line to obtain temperature signals; scans the insulating parts through a non-contact measuring device to dynamically capture the amplitude and rate of physical dimension changes to collect deformation monitoring signals in real time; and collects viscosity state signals reflecting the rheological properties of the polymer melt through the online rheological sensor in the barrel; this process completely covers the thermal, mechanical and rheological fields of the insulating parts, providing a full-dimensional data foundation for the accurate perception of spatial temperature gradient differences.

[0007] The multi-source signal fusion unit in the main control module uses timing alignment and spatial registration technology to temporally and spatially correlate temperature signals, deformation monitoring signals and viscosity state signals, and generates a fusion process state matrix containing temperature, deformation and viscosity coupling characteristics through an adaptive weighted algorithm; this unit breaks the temporal and spatial separation of multi-physical field data, establishes a dynamic correlation model between non-uniform temperature gradients and shrinkage rates, and avoids control lags caused by signal asynchrony.

[0008] The coupled dynamic modeling unit in the main control module is used to construct and update the first current shrinkage dynamic prediction model based on the fusion process state matrix, material property parameters and environmental parameters; the model uses the nonlinear thermomechanical coupling equation as the core architecture, maps the thermal stress distribution field inside the insulating part to realize the evolution of the thermal state and the shrinkage state, and dynamically corrects the thermal conductivity and viscoelastic damping factor through real-time parameter identification technology; the unit accurately quantifies the thermal stress conduction path caused by temperature differences, dynamically tracks the impact of material viscoelastic changes on the shrinkage process, and significantly improves the restoration of the physical mechanism of the first current shrinkage dynamic prediction model.

[0009] The shrinkage field deduction unit in the main control module is used to output the shrinkage state evolution trajectory of different areas of the insulating part during the subsequent cooling and solidification process by calculating the accumulation process of thermoelastic strain at each spatial position under the non-uniform temperature gradient based on the fusion process state matrix and the first current shrinkage dynamic prediction model, and generate a spatial non-uniform shrinkage distribution map (marking the shrinkage direction vector and magnitude of each coordinate point); predict the shrinkage deviation area and evolution path caused by local temperature differences in advance, and provide key decision-making basis for active intervention.

[0010] The collaborative compensation solver in the main control module analyzes the shrinkage magnitude and direction vector of each spatial coordinate point in the spatial non-uniform shrinkage distribution map. The compensation solver compares the map with the design reference geometry of the insulation component to quantify the shrinkage deformation to be offset. Based on the inverse thermal-mechanical coupling algorithm, a two-dimensional instruction is generated, where:

[0011] Temperature compensation instruction: calculate the compensation temperature gradient value of the mold temperature control zone through the non-uniform heat transfer model;

[0012] Extrusion back pressure and transmission rate coordination instruction: Calculate the material flow front pressure compensation value based on the viscoelastic damping factor correction result and rheological resistance effect;

[0013] Finally, a timing coupling strategy is used to achieve regional matching and dynamic coordination of the two types of instructions; the collaborative compensation solution unit reversely solves the shrinkage deformation into executable physical control parameters, realizes customized compensation on demand, and neutralizes non-uniform thermal stress from the source.

[0014] The execution module parses the collaborative adjustment instruction set and executes it in different dimensions. The temperature field control is based on the compensation temperature gradient value, and the heating coil power and cooling valve opening of the mold partition are dynamically adjusted; the molding rate control is based on the pressure compensation value of the material flow front, and the extruder servo system speed and the transmission belt inverter speed are linked to control, and the flow channel hydraulic proportional valve opening is fine-tuned; the execution module matches the millimeter-level temperature difference compensation requirements in the spatial dimension, and coordinates the cooling rate and material rheological response in the time dimension to achieve high-precision collaborative action of the actuator and directly suppress spatial shrinkage deviation.

[0015] A second object of the present invention is to provide a method for controlling a control system of an insulation component production line, comprising the following steps:

[0016] S1. Real-time acquisition of temperature signals on the insulation production line, deformation monitoring signals representing deformation trends of insulation parts, and viscosity state signals representing the current viscosity of the material;

[0017] S2. Receive and fuse the temperature signal, the deformation monitoring signal, and the viscosity state signal;

[0018] S3. Based on the fused signal and preset insulation material property parameters and environmental parameters, construct and update a first current shrinkage dynamic prediction model that reflects the evolution of the insulation thermal state and shrinkage state;

[0019] S4. Predicting a spatially non-uniform shrinkage distribution map of the insulating component in a subsequent molding stage using the first current shrinkage dynamic prediction model;

[0020] S5. Based on the predicted spatial non-uniform shrinkage distribution map, generating in real time a coordinated adjustment instruction set for offsetting the spatial non-uniform shrinkage;

[0021] S6. According to the collaborative adjustment instruction set, the process parameter actuators on the production line are regulated.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. The sensing module enables global synchronous acquisition of temperature, viscosity, and deformation signals on the insulation parts production line, providing the main control module with a dynamic mapping basis for spatial temperature gradient differences. The main control module uses timing alignment and spatial registration technology to generate a fusion process state matrix, accurately correlating thermal field distribution with shrinkage evolution. The constructed self-correcting first-current shrinkage dynamic prediction model quantifies the physical conduction path from temperature differences to shrinkage deformation through nonlinear thermomechanical coupling equations. The output spatially non-uniform shrinkage distribution map locates the spatial coordinates and evolution trend of deformation deviations in advance.

[0024] 2. The deformation path is predicted through the spatial non-uniform shrinkage distribution map, and the inverse thermo-mechanical coupling algorithm is used to generate partition temperature gradient compensation instructions and extrusion back pressure and transmission rate coordination instructions. In the execution module, the mold temperature zone heating ring, cooling valve, extruder servo system and transmission belt inverter are linked and controlled with millimeter-level precision to dynamically neutralize the non-uniform shrinkage force caused by spatial temperature gradient differences, thereby suppressing warpage and dimensional defects in real time during the insulation molding process. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a schematic diagram of the overall module unit of the present invention;

[0026] Figure 2 Schematic diagram of the method steps of the present invention.

[0027] In the figure: 100, perception module; 200, main control module; 201, multi-source signal fusion unit; 202, coupled dynamic modeling unit; 203, contraction field deduction unit; 204, collaborative compensation solution unit; 300, execution module. DETAILED DESCRIPTION

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0029] Next, see Figure 1 One of the purposes of this embodiment is to provide a control system for an insulation component production line, which includes a sensing module 100 , a main control module 200 and an execution module 300 .

[0030] The sensing module 100 is used to obtain in real time the temperature signal on the insulation production line, the deformation monitoring signal representing the deformation trend of the insulation, and the viscosity state signal representing the current viscosity of the material, specifically including:

[0031] By installing a temperature sensor array at key locations on the production line (such as near molds and conveyor belts), the temperature signal of the insulation part currently being processed is collected in real time. This temperature signal accurately reflects the temperature distribution and change process of the material at different locations and at different times during the production process.

[0032] Using a non-contact measuring device (such as a high-precision laser rangefinder or vision system), the moving insulation component is continuously scanned to collect its deformation monitoring signal in real time. This deformation monitoring signal dynamically captures the magnitude and rate of physical dimensional change of the insulation component during the molding process, revealing its dimensional change trend.

[0033] The properties of the molten insulating material are directly measured through a dedicated online rheological sensor (such as a sensor installed in the barrel or flow channel), and the viscosity state signal representing the molten state is collected in real time. The viscosity state signal directly indicates the rheological properties of the polymer melt and its changes over time, reflecting the flow resistance and viscosity inside the material.

[0034] The multi-source signal fusion unit 201 in the main control module 200 receives three types of core process signals transmitted by the perception module 100 in real time through a high-speed data interface, namely, temperature signal, deformation monitoring signal and viscosity state signal.

[0035] To achieve collaborative analysis of multi-source heterogeneous data, the multi-source signal fusion unit 201 uses temporal alignment and spatial registration technology to spatially and temporally correlate temperature signals from different physical locations (such as the mold area and cooling section), deformation monitoring signals synchronized with motion trajectories, and dynamically collected viscosity state signals. The execution process of the temporal alignment and spatial registration technology is as follows:

[0036] First, a unified clock reference is established, and the acquisition time of all input signals is marked by the timestamp of the high-speed data interface. Based on the motion trajectory of the production line conveyor belt, the continuous scanning point cloud of the deformation monitoring signal is compensated for position synchronization to ensure that the time series of each spatial coordinate point is strictly aligned with the acquisition time of the temperature signal and viscosity state signal. At the same time, the physical position coordinates of the temperature sensor array in the mold area and the cooling section are transformed into the spatial coordinate system, and the dynamic scanning coordinate system of the deformation monitoring signal and the barrel flow channel coordinate system of the viscosity state signal are mapped to the global spatial grid of the insulation part. Finally, the millisecond-level synchronous association of the three types of signals in the time and space dimensions is achieved, providing a temporally and spatially consistent input source for multi-source data fusion.

[0037] During the fusion process, an adaptive weighting algorithm integrates the confidence and real-time rate of change of each signal, eliminating the effects of sensor noise and transmission delays. Ultimately, a fused process state matrix is ​​generated, encompassing the coupled characteristics of temperature, deformation, and viscosity. This matrix dynamically integrates the physical state of the entire production line at a millisecond-level update frequency, providing a high-confidence, multi-dimensional input source for subsequent modeling. The adaptive weighting algorithm is implemented as follows:

[0038] First, based on the real-time signal confidence index (determined by the sensor calibration status, historical noise variance, and instantaneous signal-to-noise ratio) and the real-time signal change rate (calculated by the difference of adjacent time series data), the fusion weights of the temperature signal, deformation monitoring signal, and viscosity state signal are dynamically allocated. The weight of the signal with a sharp increase in the rate of change (such as a sudden temperature drop in the cooling section) within the time window is automatically increased, and the weight of the signal with reduced confidence (such as the deformation monitoring signal obscured by the material) is attenuated. At the same time, a sliding window statistical filter is used to suppress transient interference. Finally, a fusion process state matrix is ​​output that integrates the dynamic distribution of the temperature field, the continuity of the deformation trend, and the coupling characteristics of the viscosity change. This matrix maintains a high-confidence representation of the physical state of the entire production line at a millisecond update frequency.

[0039] The coupled dynamic modeling unit 202 in the main control module 200 constructs and continuously updates a first current shrinkage dynamic prediction model based on the fused signal (i.e., the fusion process state matrix) in combination with preset insulation material property parameters (such as thermal expansion coefficient, specific heat capacity, phase transition critical point) and environmental parameters (such as ambient humidity and pressure fluctuation compensation coefficient). This model, with nonlinear thermomechanical coupling equations as its core architecture, maps the material phase change dynamics driven by the temperature signal, the rheological resistance effect dominated by the viscosity state signal, and the real-time shrinkage rate feedback from the deformation monitoring signal into the internal thermal stress distribution field of the insulation, i.e., the thermal state evolution.

[0040] By embedding the material shrinkage constitutive equation and heat transfer boundary conditions, the thermoelastic strain accumulation process of the insulation component under non-uniform temperature gradients is calculated in real time, and the coupled evolution trend of its microcrystalline phase and macroscopic geometric form, namely the shrinkage state evolution, is output. Each time new data is input, the first current shrinkage dynamic prediction model dynamically corrects the thermal conductivity and viscoelastic damping factor through real-time parameter identification technology to ensure that the thermal state evolution and shrinkage state evolution are always highly consistent with the actual physical processes of the production line. The execution process of the real-time parameter identification technology is as follows:

[0041] This technology is triggered every time the first current contraction dynamic prediction model receives new input data, and is used to dynamically correct the core parameters of the model (thermal conductivity and viscoelastic damping factor);

[0042] Based on the temperature signal change gradient input in real time from the fusion process state matrix and the shrinkage rate feedback from the deformation monitoring signal, the theoretical prediction value of the thermal stress distribution field inside the insulation component at the current moment is calculated. The actual measured data of the shrinkage state evolution caused by the accumulation of thermoelastic strain in the actual physical process of the production line is simultaneously obtained, and the dynamic error field between the output value of the nonlinear thermomechanical coupling equation and the measured value is established.

[0043] An optimization method is used to iteratively solve the minimization conditions of the error field, and the thermal conductivity is reversely adjusted within milliseconds to match the heat transfer boundary conditions of the non-uniform temperature gradient. At the same time, the viscoelastic damping factor is updated to approximate the rheological resistance effect represented by the viscosity state signal. Ultimately, the thermal state evolution and contraction state evolution output by the first current contraction dynamic prediction model continue to track the actual physical process of the production line, ensuring strong consistency between the model prediction and the actual state of the production line.

[0044] The shrinkage field deduction unit 203 in the main control module 200 performs the following technical processes based on the first current shrinkage dynamic prediction model updated in real time by the fusion process state matrix:

[0045] The first current shrinkage dynamic prediction model analyzes the transient thermal stress distribution field within the insulation component using a nonlinear thermal coupling equation based on the evolution of the thermal and shrinkage states of the entire production line at the current moment, combined with continuously input real-time temperature signals, viscosity state signals, and deformation monitoring signals. The nonlinear thermal coupling equation serves as the core framework of the first current shrinkage dynamic prediction model, used to map the thermal stress distribution field (i.e., thermal state evolution) within the insulation component. Its physical structure includes:

[0046] The temperature field phase change driving term quantifies the material phase change dynamics driven by real-time temperature signals into heat transfer flux under non-uniform temperature gradients, and describes the volume expansion and contraction of the material caused by temperature changes based on the thermal expansion coefficient;

[0047] The viscosity field resistance effect term converts the rheological properties of the polymer melt represented by the viscosity state signal into viscous dissipative force, and combines it with the viscoelastic damping factor to construct the inhibitory effect of rheological resistance on the accumulation of thermoelastic strain;

[0048] The real-time feedback term of the deformation field embeds the strain rate-related term into the material shrinkage constitutive equation through the real-time shrinkage rate feedback of the deformation monitoring signal, characterizing the dynamic effect of physical size change on thermal stress redistribution;

[0049] This equation describes the real-time coupling relationship between heat transfer, viscous resistance and elastic strain in a nonlinear differential form by combining heat transfer boundary conditions with environmental parameters (ambient humidity, pressure fluctuation compensation coefficient). It simultaneously solves the latent heat release caused by phase change due to temperature gradient, the constraint effect of rheological resistance on molecular chain motion, and the thermal-mechanical energy conversion process of shrinkage deformation feedback in the spatial domain. It ultimately outputs the transient thermal stress distribution field inside the insulating component and the corresponding evolution trend of the coupling between the microscopic crystalline phase and the macroscopic geometric morphology (i.e., the evolution of the shrinkage state).

[0050] For the subsequent forming stage, material property parameters (thermal expansion coefficient, specific heat capacity, phase transition critical point) and environmental parameters (ambient humidity, pressure fluctuation compensation coefficient) are embedded in the shrinkage constitutive equation, and the accumulation process of thermoelastic strain at each spatial position under non-uniform temperature gradient is calculated with a millisecond update frequency;

[0051] By synchronously integrating the rheological resistance effect dominated by the viscosity state signal and the real-time shrinkage rate feedback from the deformation monitoring signal, the coupling strength between the material's microscopic crystalline phase and macroscopic geometric morphology is dynamically deduced, and the shrinkage state evolution trajectory of different regions (mold area, cooling section) of the insulation part during the subsequent cooling and solidification process is output;

[0052] Finally, based on the real-time correction results of thermal conductivity and viscoelastic damping factor, a spatially non-uniform shrinkage distribution map of the insulating parts in the subsequent molding stage is accurately generated. This map fully characterizes the shrinkage magnitude and direction vector of each spatial coordinate point.

[0053] The collaborative compensation solving unit 204 in the main control module 200 generates collaborative adjustment instructions based on the spatial non-uniform shrinkage distribution map.

[0054] The collaborative compensation calculation unit 204 first analyzes the shrinkage magnitude and direction vector of each spatial coordinate point in the spatial non-uniform shrinkage distribution map, compares it with the design reference geometry of the insulation component in all dimensions, and quantifies the shrinkage deformation that needs to be offset in the subsequent forming stage through the compensation calculation engine. The execution process of the compensation calculation engine is as follows:

[0055] First, the shrinkage magnitude and direction vector of each spatial coordinate point in the spatial non-uniform shrinkage distribution map are analyzed and compared with the design reference geometry of the insulation component in a full-dimensional spatial grid.

[0056] Based on the geometric deviation value between the shrinkage vector of each coordinate point and the design benchmark, the three-dimensional deformation compensation component (i.e., the shrinkage deformation) is calculated in the global coordinate system of the production line. At the same time, combined with the temperature gradient change trend in the real-time updated fusion process state matrix and the shrinkage acceleration characteristics of the deformation monitoring signal, the compensation overflow effect generated by the thermoelastic strain accumulation process is dynamically corrected, and finally a spatially discretized shrinkage deformation distribution field updated at the millisecond level is generated as the input benchmark for the control variable mapping.

[0057] The collaborative compensation solving unit 204 combines the real-time updated fusion process state matrix (including temperature, deformation, and viscosity coupling characteristics) with the thermal state evolution data output by the first current shrinkage dynamic prediction model to dynamically establish a mapping relationship between the shrinkage compensation amount and the control variable;

[0058] Based on material property parameters (thermal expansion coefficient, phase change critical point) and environmental parameters (ambient humidity, air pressure fluctuation compensation coefficient), an inverse thermomechanical coupling algorithm is used to solve key adjustment parameters in real time. For the temperature field control dimension, the compensation temperature gradient value of the mold temperature control zone (mold area, cooling section) is calculated through a non-uniform heat transfer model, and temperature compensation instructions are generated to adjust the temperature control actuator. For the molding rate control dimension, based on the real-time correction results of the viscoelastic damping factor and the rheological resistance effect, the pressure compensation value of the material flow front is solved, and the extrusion back pressure and transmission rate coordination instructions are generated to control the hydraulic system of the molding equipment.

[0059] All adjustment instructions are regionally matched through a time-space coupling strategy to ensure that the temperature compensation instructions and the rate control instructions are dynamically coordinated in the timing and space domains, and ultimately output a millisecond-updated coordinated adjustment instruction set to directly drive the execution module 300 to implement closed-loop compensation control.

[0060] The execution module 300 regulates the process parameter actuators on the production line according to the collaborative adjustment instruction set, specifically including:

[0061] First, the industrial real-time bus protocol receives and decouples the coordinated adjustment instruction set in milliseconds, parsing it into temperature compensation instructions, extrusion back pressure and transmission rate coordinated instructions;

[0062] In terms of temperature field control, the power modulation unit of the temperature control actuator is driven according to the compensation temperature gradient value of the mold temperature control zone (mold area, cooling section), dynamically adjusting the heating coil power and cooling valve opening at the specified spatial position, so that the compensation temperature gradient set by the non-uniform heat transfer model is accurately generated on the surface of the insulation part;

[0063] In terms of molding rate control, the extruder servo system and the conveyor belt inverter are linked and controlled according to the pressure compensation value at the material flow front. Back pressure compensation is achieved by adjusting the screw speed in real time, and the conveyor belt speed instruction is synchronously matched to balance the position of the material flow front. At the same time, based on the correction result of the viscoelastic damping factor, the opening of the flow channel hydraulic proportional valve is dynamically fine-tuned to suppress the rheological resistance fluctuation represented by the viscosity state signal.

[0064] All control actions strictly follow the time-space coupling strategy: in the spatial dimension, ensure that the boundaries of the temperature control zone and the rate control area coincide, and in the timing dimension, maintain millisecond-level synchronization between back pressure regulation and transmission acceleration, ultimately achieving closed-loop compensation of the internal thermal stress distribution field and shrinkage deformation of the insulating parts; during the control process, the actuator status is fed back to the collaborative compensation solution unit 204 in real time, forming a full closed-loop control chain for process status perception, prediction and control.

[0065] See also Figure 2 The second object of this embodiment is to provide a control system method for an insulation component production line, comprising the following steps:

[0066] S1. Real-time acquisition of temperature signals on the insulation production line, deformation monitoring signals representing deformation trends of insulation parts, and viscosity state signals representing the current viscosity of the material;

[0067] S2, receiving and fusing temperature signals, deformation monitoring signals and viscosity state signals;

[0068] S3. Based on the fused signal and preset insulation material property parameters and environmental parameters, construct and update a first current shrinkage dynamic prediction model that reflects the evolution of the insulation thermal state and shrinkage state;

[0069] S4. Predicting a spatially non-uniform shrinkage distribution map of the insulating component in a subsequent molding stage using the first current shrinkage dynamic prediction model;

[0070] S5. Based on the predicted spatial non-uniform shrinkage distribution map, generate a coordinated adjustment instruction set for offsetting the spatial non-uniform shrinkage in real time;

[0071] S6. According to the collaborative adjustment instruction set, the process parameter actuators on the production line are regulated.

[0072] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A control system for an insulation production line, characterized in that: It includes a perception module (100), a main control module (200) and an execution module (300), wherein: The sensing module (100) is used to obtain in real time the temperature signal on the insulation component production line, the deformation monitoring signal representing the deformation trend of the insulation component, and the viscosity state signal representing the current viscosity of the material; The main control module (200) receives and fuses the temperature signal, the deformation monitoring signal, and the viscosity state signal transmitted by the sensing module (100); the main control module (200) comprises a multi-source signal fusion unit (201), the multi-source signal fusion unit (201) being used to perform spatiotemporal correlation on the temperature signal, the deformation monitoring signal, and the viscosity state signal through time sequence alignment and spatial registration technology, and to generate a fusion process state matrix containing coupled features of temperature, deformation, and viscosity through an adaptive weighting algorithm; The main control module (200) constructs and updates a first current shrinkage dynamic prediction model reflecting the evolution of the thermal state and the evolution of the shrinkage state of the insulating part based on the fused signal and the preset insulating part material property parameters and environmental parameters; the main control module (200) includes a coupled dynamic modeling unit (202), and the coupled dynamic modeling unit (202) is used to construct and update the first current shrinkage dynamic prediction model based on the fusion process state matrix, the material property parameters and the environmental parameters; the model uses a nonlinear thermal coupling equation as a core architecture, maps the thermal stress distribution field inside the insulating part to realize the evolution of the thermal state and the shrinkage state, and dynamically corrects the thermal conductivity and the viscoelastic damping factor through real-time parameter identification technology; The main control module (200) uses the first current shrinkage dynamic prediction model to predict the spatial non-uniform shrinkage distribution map of the insulating component in the subsequent molding stage; The main control module (200) generates a coordinated adjustment instruction set for offsetting the spatial non-uniform shrinkage in real time based on the predicted spatial non-uniform shrinkage distribution map; The execution module (300) is used to regulate the process parameter actuators on the production line according to the coordinated adjustment instruction set issued by the main control module (200).

2. The control system for an insulation component production line according to claim 1, characterized in that: The main control module (200) includes a shrinkage field deduction unit (203), which is used to output the shrinkage state evolution trajectory of different areas of the insulation part during the subsequent cooling and solidification process by calculating the thermal elastic strain accumulation process of each spatial position under the non-uniform temperature gradient based on the fusion process state matrix and the first current shrinkage dynamic prediction model, and generate the spatial non-uniform shrinkage distribution map.

3. The control system for an insulation component production line according to claim 2, characterized in that: The main control module (200) includes a collaborative compensation solution unit (204), which is used to analyze the shrinkage magnitude and direction vector of each spatial coordinate point in the spatial non-uniform shrinkage distribution map, quantify the shrinkage deformation amount to be offset through a compensation amount solution engine, and generate a collaborative adjustment instruction set based on an inverse thermal-mechanical coupling algorithm.

4. The control system for an insulation component production line according to claim 3, characterized in that: The process of generating the collaborative adjustment instruction set by the collaborative compensation solution unit (204) specifically includes: In terms of temperature field control, the non-uniform heat transfer model is used to calculate the compensation temperature gradient value of the mold temperature control zone to generate temperature compensation instructions; In terms of molding rate control, the pressure compensation value at the material flow front is calculated based on the viscoelastic damping factor correction result and the rheological resistance effect, and the extrusion back pressure and transmission rate coordination instructions are generated; Regional matching and dynamic coordination of temperature compensation instructions and rate control instructions are achieved through space-time coupling strategy.

5. The control system for an insulation component production line according to claim 1, characterized in that: The process of the execution module (300) performing regulation includes: The coordinated adjustment instruction set is analyzed as a temperature compensation instruction, an extrusion back pressure and a transmission rate coordinated instruction; In terms of temperature field control dimension, the temperature control actuator is driven to dynamically adjust the heating coil power and cooling valve opening according to the compensated temperature gradient value; In terms of molding rate control, the extruder servo system and the conveyor belt inverter are controlled in conjunction with the pressure compensation value at the material flow front, and the opening of the flow channel hydraulic proportional valve is dynamically fine-tuned.

6. The control system for an insulation component production line according to claim 3, characterized in that: The compensation amount calculation engine quantifies the amount of shrinkage deformation that needs to be offset in the subsequent forming stage by comparing the spatial non-uniform shrinkage distribution map with the design reference geometry of the insulation component.

7. The control system for an insulation component production line according to claim 1, characterized in that: The sensing module (100) installs a temperature sensor array in the mold area and near the conveyor belt of the production line to collect temperature signals reflecting the temperature distribution and changes at different positions of the insulating part in real time; uses a non-contact measuring device to scan the insulating part to collect deformation monitoring signals in real time, and dynamically captures the amplitude and rate of its physical size change; and installs an online rheological sensor in the barrel to collect viscosity state signals reflecting the rheological characteristics of the polymer melt in real time.

8. A method of using the control system for an insulation component production line according to any one of claims 1 to 7, characterized in that: The method comprises the following steps: S1. Real-time acquisition of temperature signals on the insulation production line, deformation monitoring signals representing deformation trends of insulation parts, and viscosity state signals representing the current viscosity of the material; S2. Receive and fuse the temperature signal, the deformation monitoring signal, and the viscosity state signal; S3. Based on the fused signal and preset insulation material property parameters and environmental parameters, construct and update a first current shrinkage dynamic prediction model that reflects the evolution of the insulation thermal state and shrinkage state; S4. Predicting a spatially non-uniform shrinkage distribution map of the insulating component in a subsequent molding stage using the first current shrinkage dynamic prediction model; S5. Based on the predicted spatial non-uniform shrinkage distribution map, generating in real time a coordinated adjustment instruction set for offsetting the spatial non-uniform shrinkage; S6. According to the collaborative adjustment instruction set, the process parameter actuators on the production line are regulated.

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