Remote control system and method for hot press

Abstract

The present invention discloses a remote control system and method for a hot press, which relate to the technical field of coupling analysis, including collecting physical field data and uploading it to a remote control center; constructing a dynamic physical field coupling analysis model based on the physical field data, dynamically correcting the physical field data, and realizing physical field association; according to the results of the dynamic correction, using a multi-physical field adaptive optimization algorithm in combination with the physical field data and the results of the dynamic correction to automatically adjust the hot press parameters; directly transmitting the adjusted hot press parameters to the hot press remote control unit to complete the operation adjustment; the present invention defines and dynamically corrects the coupling relationship between the temperature field, pressure field and stress field through the multi-physical field coupling analysis model, thereby realizing the association analysis and dynamic adjustment of the physical field.

Description

Technical Field

[0001] The present invention relates to the technical field of coupling analysis, in particular to a remote control system of a hot press and a method thereof. Background Art

[0002] As an important processing equipment, hot press is widely used in fields such as composite material molding and electronic component packaging. Its core lies in achieving high-precision processing and performance optimization of materials by controlling heating and pressure. With the development of industrial intelligence, traditional hot presses are gradually evolving towards intelligence and remote control. Collecting data through sensors and combining algorithm optimization parameters has become an important trend in the development of hot press technology. However, most hot presses currently still focus on the measurement and control of a single physical field, and fail to fully consider the coupling relationship between temperature field, pressure field and stress field, resulting in limited processing accuracy and consistency. In addition, most existing control systems are localized single-machine control, which makes it difficult to achieve remote real-time adjustment and lacks the ability to dynamically respond to complex real-time working conditions, restricting the further improvement of production efficiency and equipment intelligence.

[0003] In response to the above problems, existing technologies still face many challenges in multi-physical field coupling analysis and optimization control; first, traditional hot presses find it difficult to effectively collect and analyze data from multiple physical fields, and ignore the dynamic coupling between temperature fields, pressure fields, and stress fields, resulting in delayed or inaccurate parameter adjustments, which in turn affects processing stability and process effects; second, existing technologies lack efficient adaptive optimization algorithms, and are unable to correct parameters based on real-time data, let alone combine historical data for intelligent prediction and decision-making; finally, traditional systems find it difficult to achieve remote and precise control, especially in complex processing scenarios, where the adjustment of equipment operating parameters often relies on manual intervention, resulting in low efficiency and large errors. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a remote control method for a hot press to solve the problem of analyzing multiple physical field data.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a remote control method for a hot press, which includes collecting physical field data and uploading it to a remote control center; constructing a dynamic physical field coupling analysis model based on the physical field data, dynamically correcting the physical field data, and realizing physical field association; according to the results of the dynamic correction, using a multi-physical field adaptive optimization algorithm combined with the physical field data and the results of the dynamic correction to automatically adjust the hot press parameters; and directly transmitting the adjusted hot press parameters to the hot press remote control unit to complete the operation adjustment.

[0008] As a preferred solution of the remote control method of a hot press described in the present invention, the physical field data includes temperature field data, pressure field data, and stress field data.

[0009] As a preferred solution of the remote control method of a hot press according to the present invention, the specific steps of constructing a dynamic physical field coupling analysis model are as follows:

[0010] The input is defined as physical field data, and the output is the physical field data corrected after dynamic adjustment;

[0011] Define the coupling relationship between temperature field data and pressure field data;

[0012] Define the coupling relationship between temperature field data and stress field data;

[0013] Define the coupling relationship between pressure field data and stress field data;

[0014] According to the defined physical field data coupling relationship, the physical field data is dynamically adjusted and corrected. The expression is:

[0015]

[0016] in, is the partial derivative of temperature with time, is the sign of the partial derivative, T is the temperature, C1 is the thermal conductivity constant, is the Laplace operator, T(u,v,t) is the time-varying temperature distribution on the two-dimensional plane, Q(u,v,t) is the time-varying heat source term on the two-dimensional plane, f(P(u,v,t)) is the pressure field coupling term, P(u,v,t) is the time-varying pressure distribution on the two-dimensional plane, g(σ(x,y,z,t)) is the stress field coupling term, σ(x,y,z,t) is the time-varying stress distribution in three-dimensional space, u is the horizontal coordinate in the two-dimensional plane, v is the vertical coordinate in the two-dimensional plane, t is the time variable, x is the horizontal coordinate in the three-dimensional space, y is the vertical coordinate in the three-dimensional space, and z is the height direction position in the three-dimensional space;

[0017] According to the real-time collected temperature field data, the heat source item is dynamically adjusted and the corrected temperature field data is output;

[0018] According to the real-time collected pressure field data, the pressure distribution is dynamically adjusted and the corrected pressure field data is output;

[0019] According to the real-time collected stress field data, the stress distribution is dynamically adjusted and the corrected stress field data is output;

[0020] An online calibration mechanism is introduced to adaptively adjust and calibrate physical field data.

[0021] As a preferred solution of the remote control method of a hot press described in the present invention, wherein: the online calibration mechanism is introduced to adaptively adjust and calibrate the physical field data, and the specific steps are:

[0022] Input the corrected temperature field data, dynamically adjust the thermal conductivity constant, and output the calibrated thermal conductivity constant;

[0023] Input the corrected stress field data, dynamically adjust the stress field parameters, and output the calibrated stress distribution;

[0024] Input the corrected pressure field data and the corrected stress field data, dynamically calibrate the parameters of the pressure field coupling term and the stress field coupling term, and output the calibrated pressure field coupling coefficient and the stress field coupling coefficient.

[0025] As a preferred solution of the remote control method of a hot press described in the present invention, wherein: the multi-physics field adaptive optimization algorithm is used in combination with the physical field data and the results of dynamic correction to automatically adjust the parameters of the hot press, the specific steps are as follows:

[0026] According to the corrected physical field data, the hot press parameters are dynamically adjusted through the multi-physics field adaptive optimization algorithm, combined with the historical operation data and the output of the dynamic physical field coupling analysis model. The expression is:

[0027] U o =min{∫[(T t -T'(u,v,t)) 2 +(P t -P'(u,v,t)) 2 +(σ t -σ'(x,y,z,t)) 2 ]dV};

[0028] Among them, U o is the optimization objective function, min is the minimization operator, ∫ is the spatial integral symbol, dV is the volume unit, T t is the target temperature distribution, T'(u,v,t) is the actual temperature field distribution that changes with time on the two-dimensional plane, (T t -T'(u,v,t)) 2 is the square of the temperature error, P t is the target pressure distribution, P'(u,v,t) is the actual pressure distribution on the two-dimensional plane that changes with time, (P t -P'(u,v,t)) 2 is the square of the pressure error, σ t is the target stress distribution, σ'(x,y,z,t) is the actual stress distribution in three-dimensional space that changes with time, (σt -σ'(x,y,z,t)) 2 is the square of the stress error;

[0029] Set the judgment threshold based on the comparison results between real-time physical field data and optimization targets;

[0030] According to the optimized target temperature distribution, the heat conduction constant and the heat source term are adjusted to generate the target temperature curve;

[0031] According to the optimized target pressure distribution, the pressure field coupling coefficient is adjusted to generate a pressure distribution curve;

[0032] Generate the hot pressing time setting value based on the optimization target stress distribution and optimization results.

[0033] As a preferred solution of the remote control method of a hot press according to the present invention, wherein: the setting of the judgment threshold is specifically performed as follows:

[0034] When T'(u,v,t) <T t , then increase the heating power;

[0035] When T'(u,v,t)>T t , then reduce the heating power;

[0036] When T'(u,v,t)=T t , then keep the current heating power unchanged;

[0037] When P'(u,v,t) <P t , then increase the applied pressure;

[0038] When P'(u,v,t)>P t , then reduce the pressure;

[0039] When P'(u,v,t)=P t , then keep the current pressure unchanged;

[0040] When σ'(x,y,z,t)<σ t , then adjust the pressure field coupling term and increase the loading pressure;

[0041] When σ'(x,y,z,t)>σ t , then adjust the pressure field coupling term to reduce the loading pressure;

[0042] When σ'(x,y,z,t)=σ t , the current loading pressure remains unchanged.

[0043] As a preferred solution of the remote control method of a hot press according to the present invention, wherein: the adjusted hot press parameters are directly transmitted to the hot press remote control unit to complete the operation adjustment, the specific steps are:

[0044] Convert the adjusted parameters into hot press execution instructions and send them to the hot press control center via radio communication;

[0045] Adjust the heating power distribution according to the target temperature curve;

[0046] According to the pressure distribution curve, uniform force is achieved;

[0047] Adjust the hot pressing time according to the hot pressing time setting value.

[0048] In the second aspect, the present invention provides a remote control system for a hot press, comprising an acquisition module, a correction module, an adjustment module and an operation module; the acquisition module is used to acquire physical field data and upload it to a remote control center; the correction module is used to construct a dynamic physical field coupling analysis model based on the physical field data, dynamically correct the physical field data, and realize physical field association; the adjustment module is used to automatically adjust the hot press parameters based on the results of dynamic correction, using a multi-physical field adaptive optimization algorithm combined with the physical field data and the results of dynamic correction; the operation module is used to directly transmit the adjusted hot press parameters to the hot press remote control unit to complete the operation adjustment.

[0049] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the remote control method for a hot press as described in the first aspect of the present invention is implemented.

[0050] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the remote control method for a hot press as described in the first aspect of the present invention is implemented.

[0051] The beneficial effects of the present invention are as follows: the present invention defines and dynamically corrects the coupling relationship between the temperature field, pressure field and stress field through a multi-physical field coupling analysis model, thereby realizing correlation analysis and dynamic adjustment of the physical field; real-time acquisition of physical field data and introduction of an online calibration mechanism solve the problem of inaccurate control caused by neglect of the interaction of multiple physical fields in traditional technology; the invention can accurately capture the dynamic coupling effect between the physical fields, making the physical field data more accurate and providing a reliable basis for subsequent parameter optimization; ultimately, the invention effectively improves the processing consistency and accuracy during the operation of the hot press, meets the demand for high-quality processing under complex working conditions, and significantly enhances the intelligence and reliability of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 This is a flow chart of a remote control method for a hot press in Example 1.

[0054] Figure 2 This is a module diagram of a remote control system for a hot press in Example 1. DETAILED DESCRIPTION

[0055] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0056] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0057] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0058] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, provides a remote control method for a hot press, comprising the following steps:

[0059] S1. Collect physical field data and upload it to the remote control center.

[0060] Furthermore, the physical field data includes temperature field data, pressure field data, stress field data and historical operation data;

[0061] Install temperature sensors, pressure sensors, and stress sensors on key components of the hot press (such as hot press plates, molds, and hydraulic presses);

[0062] Real-time collection of physical field data generated during the hot pressing process: temperature distribution (temperature field data), pressure distribution (pressure field data), and stress concentration state (stress field data), and uploading the collected data to the remote control center using a wireless communication module (such as Wi-Fi or LoRa);

[0063] Temperature field data is the surface temperature distribution of the hot press plate recorded in the form of discrete coordinates and collected by temperature sensors;

[0064] The pressure field data is the pressure distribution on the hot platen surface, which is collected by the pressure sensor;

[0065] The stress field data is the stress concentration in the contact area between the hot press plate and the workpiece, which is collected by the stress sensor and recorded as;

[0066] Historical operation data refers to the historical records related to equipment performance, operating status or physical field parameters accumulated during the operation of the equipment. It includes historical physical field data, operating parameter records (such as the heating power, pressure setting value, hot pressing time of the hot press, etc.) and operating result records (such as finished product quality, fault information, etc.);

[0067] It should be noted that by installing temperature, pressure and stress sensors on the key components of the hot press and collecting physical field data (temperature field, pressure field, stress field) during the hot pressing process in real time, comprehensive monitoring of the hot pressing process is achieved; the data is uploaded to the remote control center using a wireless communication module to ensure data real-time and transmission efficiency; this step provides high-quality data support for subsequent multi-physical field coupling analysis and parameter optimization by accurately obtaining the surface temperature distribution, pressure distribution and stress concentration of the hot pressing plate, significantly improving the ability to recognize the processing status and laying the foundation for high-precision remote control.

[0068] S2. Based on the physical field data, a dynamic physical field coupling analysis model is constructed to dynamically correct the physical field data and realize physical field association.

[0069] The input is defined as physical field data, and the output is the physical field data corrected after dynamic adjustment;

[0070] Define the coupling relationship between temperature field data and pressure field data. The pressure distribution will affect the heat transfer efficiency of the contact interface. For example, the greater the pressure, the faster the heat transfer rate. Therefore, it is necessary to introduce the influence of the pressure field on the temperature field, which can be expressed as:

[0071] f(P(u,v,t))=a·P(u,v,t) b ;

[0072] Among them, f(P(u,v,t)) is the pressure field coupling term, which represents the influence of pressure distribution on temperature field. P(u,v,t) is the time-varying pressure distribution on a two-dimensional plane. a is the proportional coefficient of pressure to heat conduction, which represents the basic intensity of the influence of pressure on heat conduction. Its specific value depends on the physical properties of the material and experimental data. For example, if a=0.5, it means that the change in heat conduction efficiency is 0.5 times under unit pressure. b is the nonlinear degree of the influence of pressure on heat conduction, which represents the trend of change in heat conduction efficiency with increasing pressure. If b=1, it represents a linear relationship; if b>1 or b<1, it represents a nonlinear relationship. For example, if b=1.2, it means that the influence of pressure on heat conduction is nonlinear, and this influence will become more significant with increasing pressure. a and b are pressure field coupling coefficients, which represent the nonlinear influence of pressure on heat conduction.

[0073] Define the coupling relationship between temperature field data and stress field data. Temperature changes will cause thermal expansion or contraction of the material, which in turn affects the stress distribution inside the material. For example, when the temperature gradient is large, stress concentration is likely to occur, which can be expressed as:

[0074]

[0075] σ=E*ε;

[0076] Among them, g(σ(x,y,z,t)) is the stress field coupling term, c is the proportionality coefficient when the stress is less than the yield strength, which represents the influence of stress on temperature. Its specific value depends on the thermal expansion coefficient and elastic modulus of the material. For example, if c=0.3, it means that under unit stress, the temperature change is 0.3 times. d is when the stress is greater than or equal to the yield strength. This is a proportionality coefficient, which represents the nonlinear effect of stress on temperature. Its specific value also depends on the plastic deformation characteristics of the material and experimental data. For example, if d=0.1, it means that under high stress, the temperature change is proportional to the square of the stress. σ(x,y,z,t) is the stress distribution that changes with time in three-dimensional space. c and d are stress field coupling coefficients. σ is stress, E is elastic modulus, ε is strain, σ y is the yield strength of the material, which indicates the stress value at which the material begins to deform plastically. This value can be obtained through mechanical testing of the material (such as tensile testing). For example, if σ y =100MPa, it means that when the stress reaches 100MPa, the material begins to undergo plastic deformation.

[0077] Define the coupling relationship between pressure field data and stress field data. The uneven distribution of pressure will directly lead to changes in material deformation and stress concentration areas, which can be expressed as:

[0078] σ l(x,y,z,t)=h(P(u,v,t));

[0079] Among them, σ l (x, y, z, t) is the local stress. Local stress refers to the stress value measured at a specific location and time point in the material. It describes the stress state at a point (x, y, z) and a time t in three-dimensional space. h(P(u, v, t)) is the mapping function from pressure to local stress. It indicates how pressure affects the local stress distribution. It can be a linear function or a nonlinear function, depending on the constitutive relationship of the material. P(u, v, t) is the time-varying pressure distribution on a two-dimensional plane.

[0080] The linear relationship is expressed as:

[0081] h(P(u,v,t))=k·P(u,v,t);

[0082] Where k is a proportionality coefficient that indicates the degree of influence of pressure on local stress. For example, if k = 0.8, it means that the change in local stress is 0.8 times under unit pressure.

[0083] The nonlinear relationship is expressed as:

[0084] h(P(u,v,t))=k1·P(u,v,t)+k2·P(u,v,t) 2 ;

[0085] Among them, k1 is the proportional coefficient of the linear term, which indicates the linear effect of pressure on local stress at low pressure. That is, when the pressure is small, the change in local stress is proportional to the pressure. For example, if k1 = 0.6, it means that the change in local stress is 0.6 times under unit pressure, which means that in the low pressure range, the local stress increases linearly with the increase in pressure. k2 is the proportional coefficient of the quadratic term, which indicates the nonlinear effect of pressure on local stress at high pressure. Specifically, it describes that with the increase in pressure, the change in local stress is no longer a simple linear relationship, but grows quadratically. For example, if k2 = 0.1, it means that at high pressure, the change in local stress is not only proportional to the pressure, but also proportional to the square of the pressure, with a proportional coefficient of 0.1, which indicates that in the high pressure range, the local stress will increase faster with the increase in pressure.

[0086] The specific values ​​of k1 and k2 are usually determined by experimental data or the constitutive relationship of the material. These coefficients reflect the mechanical response characteristics of the material under different pressure levels. k1 mainly describes the elastic behavior of the material under low pressure, that is, within the elastic range, stress is proportional to strain (Hooke's law). K2 describes the plastic behavior or nonlinear behavior of the material under high pressure, that is, after exceeding a certain critical pressure, the stress-strain relationship of the material is no longer linear, but exhibits nonlinear characteristics.

[0087] According to the defined physical field data coupling relationship, the dynamic physical field coupling analysis model continuously receives the real-time collected physical field data, and dynamically adjusts and corrects the physical field data according to the defined coupling relationship. The expression is:

[0088]

[0089] in, It is the partial derivative of temperature over time, which indicates the rate of change of temperature T with time t at the coordinate point (u, v). It is the symbol of partial derivative, which indicates the rate of change of a function with respect to a certain variable while other variables remain unchanged. T is the temperature, and C1 is the thermal conductivity constant, which indicates the thermal conductivity of the material. is the Laplace operator, which represents the spatial diffusivity of temperature on a two-dimensional plane. T(u,v,t) is the time-varying temperature distribution on a two-dimensional plane. Q(u,v,t) is the time-varying heat source term on a two-dimensional plane, which represents the heat input at the coordinate point (u,v) by the hot press. f(P(u,v,t)) is the pressure field coupling term, which represents the influence of the pressure distribution on the temperature field. P(u,v,t) is the time-varying pressure distribution on a two-dimensional plane. g(σ(x,y,z,t)) is the stress field coupling term, which represents the influence of stress concentration on the temperature field. σ(x,y,z,t) is the time-varying stress distribution in three-dimensional space. u is the horizontal coordinate in the two-dimensional plane, v is the vertical coordinate in the two-dimensional plane, t is the time variable, which represents the change of the physical field with time. x is the horizontal coordinate in the three-dimensional space, y is the vertical coordinate in the three-dimensional space, and z is the height position in the three-dimensional space.

[0090] This formula describes the dynamic changes of the temperature field, integrates the heat source term, pressure field coupling term and stress field coupling term into the model, and realizes the precise correlation and dynamic adjustment between multiple physical fields; it can reflect the changes of temperature with time and space in real time, and dynamically optimize the heat source configuration and hot pressing parameters by combining the effects of pressure distribution and stress concentration on heat conduction; through this formula, precise control of the temperature distribution of the hot press can be achieved, ensuring the uniformity and stability of the hot pressing process, improving processing quality and efficiency, and avoiding local overheating or stress concentration problems.

[0091] According to the real-time collected temperature field data, the heat source item is dynamically adjusted (if the temperature deviates from the target value, it is corrected by adjusting the heating power) and the corrected temperature field data is output;

[0092] According to the real-time collected pressure field data, the pressure distribution is dynamically adjusted (the pressure application area is corrected) and the corrected pressure field data is output;

[0093] Based on the real-time collected stress field data, the stress distribution is dynamically adjusted, the material mechanical response parameters (such as elastic modulus and yield strength) are updated to adapt to the current stress distribution, and the corrected stress field data is output;

[0094] An online calibration mechanism is introduced to adaptively adjust and calibrate physical field data.

[0095] S2.1. Introduce an online calibration mechanism to adaptively adjust and calibrate physical field data. Specifically,

[0096] Input the corrected temperature field data, dynamically adjust the thermal conductivity constant according to the corrected temperature field data to adapt to environmental changes, and output the calibrated thermal conductivity constant;

[0097] Input the corrected stress field data. Based on the corrected stress field data and its correlation with external conditions (such as temperature, strain, damage, etc.), dynamically adjust the stress field parameters (elastic modulus and yield strength of the material) to enhance the adaptability of the material and output the calibrated stress distribution.

[0098] The corrected pressure field data and the corrected stress field data are input, and the parameters of the pressure field coupling term and the stress field coupling term are dynamically calibrated according to the corrected pressure field data and the corrected stress field data, and the calibrated pressure field coupling coefficient and the stress field coupling coefficient are output.

[0099] It should be noted that by constructing a dynamic physical field coupling analysis model, combining the real-time collected physical field data (temperature field, pressure field, stress field) and their coupling relationship, the physical field data is dynamically corrected and adjusted to achieve the association and adaptive optimization of multiple physical fields; based on the coupling model, the heat source term, pressure distribution and material mechanical parameters (such as elastic modulus and yield strength) are dynamically adjusted to adapt to different processing conditions; an online calibration mechanism is introduced to adaptively adjust the thermal conductivity constant and coupling coefficient to further improve the model accuracy and material response capability; this step effectively improves the operating stability and processing accuracy of the hot press, ensuring optimized hot pressing effects under complex working conditions and extending the life of the equipment.

[0100] S3. Based on the results of dynamic correction, the multi-physics field adaptive optimization algorithm is used to combine the physical field data and the results of dynamic correction to automatically adjust the hot press parameters.

[0101] Furthermore, based on the corrected physical field data, the multi-physics field adaptive optimization algorithm is used to dynamically adjust the hot press parameters by combining historical operation data and the output of the dynamic physical field coupling analysis model. The expression is:

[0102] U o =min{∫[(T t -T'(u,v,t)) 2 +(P t -P'(u,v,t)) 2 +(σ t -σ'(x,y,z,t)) 2 ]dV};

[0103] Among them, U o is the optimization objective function. The smaller its value, the better the optimization effect. min is the minimization operator, which means that the value of the objective function should be reduced as much as possible by adjusting the model parameters to achieve the optimal state. ∫ is the spatial integral symbol, which means that the integral calculation is performed on the entire working area in the hot press. dV is the volume unit (small volume element), which means the volume accumulation of the integral in three-dimensional space. t is the target temperature distribution, which is defined by the process requirements. T'(u,v,t) is the actual temperature distribution that changes with time on the two-dimensional plane. It is the actual temperature distribution calculated by the dynamic correction formula. It is affected by the heat conduction constant, heat source term, pressure coupling term and stress coupling term. (T t -T'(u,v,t)) 2 is the square of the temperature error, which represents the square of the error between the target temperature distribution and the actual temperature distribution, P t is the target pressure distribution, which is defined according to the process requirements and represents the expected pressure field distribution. P'(u, v, t) is the actual pressure distribution on the two-dimensional plane that changes with time. It describes the change of the pressure field on the two-dimensional plane with time t during the operation of the hot press. (P t -P'(u,v,t)) 2 is the square of the pressure error, which represents the square of the error between the target pressure distribution and the actual pressure distribution, σ t is the target stress distribution, which describes the expected stress distribution inside the workpiece during processing to ensure that the workpiece will not be damaged or deformed due to stress concentration. σ'(x, y, z, t) is the actual stress distribution in three-dimensional space that changes with time. It describes the change of the stress field in three-dimensional space with time t during the operation of the hot press. (σ t -σ'(x,y,z,t)) 2 is the square of the stress error, which represents the square of the error between the target stress distribution and the actual stress distribution;

[0104] This formula achieves comprehensive optimization of temperature, pressure and stress distribution by constructing an optimization objective function and minimizing the target value; by calculating the square of the error between the target value and the actual distribution and integrating it over the entire working area, it can accurately evaluate the deviation in the hot pressing process; combined with dynamic adjustment of model parameters, the formula can guide the hot press to optimize the temperature, pressure and stress distribution in real time and generate the optimal control strategy; this formula effectively improves the accuracy and uniformity of the hot pressing process, ensures the quality of workpiece molding, and reduces energy consumption and material loss.

[0105] According to the comparison results between real-time physical field data and optimization targets, a judgment threshold is set to determine whether the hot press parameters need to be adjusted;

[0106] According to the optimized target temperature distribution, the heat conduction constant and heat source term are adjusted to optimize the temperature field distribution and generate the target temperature curve;

[0107] According to the optimized target pressure distribution, the pressure field coupling coefficient is adjusted to solve the problem of local pressure unevenness or abnormal pressure points, and the pressure distribution curve is generated;

[0108] According to the optimization target stress distribution and optimization results, the elastic modulus and yield strength of the material are dynamically updated, the stress field distribution is optimized, stress concentration is reduced, and the hot pressing time setting value is generated.

[0109] It should be noted that threshold judgment is a preliminary screening mechanism to determine whether adjustment is needed. Its purpose is to avoid frequent adjustments and maintain stability;

[0110] Optimization adjustment is a precise execution mechanism used to provide specific optimization solutions when adjustment is needed to ensure efficient and high-quality machining processes.

[0111] S3.1. Set the judgment threshold, specifically,

[0112] When T'(u,v,t) <T t , then increase the heating power;

[0113] When T'(u,v,t)>T t , then reduce the heating power;

[0114] When T'(u,v,t)=T t , then keep the current heating power unchanged;

[0115] When P'(u,v,t) <P t , then increase the applied pressure;

[0116] When P'(u,v,t)>P t , then reduce the pressure;

[0117] When P'(u,v,t)=P t, then keep the current pressure unchanged;

[0118] When σ'(x,y,z,t)<σ t , then adjust the pressure field coupling term and increase the loading pressure;

[0119] When σ'(x,y,z,t)>σ t , then adjust the pressure field coupling term to reduce the loading pressure;

[0120] When σ'(x,y,z,t)=σ t , the current loading pressure remains unchanged.

[0121] It should be noted that the core function of the online calibration mechanism is to ensure the accuracy of physical field data and the reliability of the model, which belongs to the stage of data processing and model calibration; while the automatic adjustment of hot press parameters is based on the calibrated data, and the control parameters are generated and executed through the optimization algorithm, which directly affects the operation of the hot press equipment; the two have different functions and distinct levels, but they work closely together in the whole to achieve high precision and high efficiency of remote control of the hot press.

[0122] It should be noted that by automatically adjusting the hot press parameters based on dynamically corrected physical field data and combining a multi-physical field adaptive optimization algorithm, precise optimization and dynamic control of the temperature field, pressure field and stress field are achieved; by minimizing the objective function and combining real-time data, historical operation data and the output of the coupling analysis model, the thermal conductivity constant, heat source term, pressure field coupling coefficient and material mechanical parameters (such as elastic modulus and yield strength) are dynamically adjusted to optimize the temperature, pressure and stress distribution, generate the target curve and hot pressing time setting value; the threshold judgment mechanism avoids frequent adjustments and maintains overall stability; this step significantly improves processing accuracy, efficiency and equipment adaptability, ensuring high-quality hot pressing effects.

[0123] S4. The adjusted hot press parameters are directly transmitted to the hot press remote control unit to complete the operation adjustment.

[0124] Furthermore, the adjusted parameters are converted into execution instructions for the hot press and sent to the hot press control center via radio communication;

[0125] Adjust the heating power distribution according to the target temperature curve to ensure uniform surface temperature of the hot press plate;

[0126] According to the pressure distribution curve, the problem of insufficient or over-pressure in some areas can be solved to achieve uniform stress.

[0127] Adjust the hot pressing time according to the hot pressing time setting value to ensure that the workpiece material is fully formed without overheating or overpressure.

[0128] It should be noted that precise operational adjustments to the hot press are achieved by converting the adjusted hot press parameters into specific execution instructions and transmitting them to the hot press remote control unit. Dynamically adjust the heating power distribution based on the target temperature curve to ensure uniform surface temperature on the hot press platen. Optimize the pressure application area based on the pressure distribution curve to address localized pressure shortages or overpressure, achieving uniform force distribution. Precisely control the hot press time based on the set value to prevent overheating or overpressure of the workpiece material and ensure molding quality. This step directly applies the optimization results to equipment operation, significantly improving the stability and processing accuracy of the hot press process, while also enhancing equipment operating efficiency and product consistency.

[0129] This embodiment also provides a remote control system for a hot press, including: an acquisition module, a correction module, an adjustment module and an operation module; the acquisition module acquires physical field data and uploads it to a remote control center; the correction module constructs a dynamic physical field coupling analysis model based on the physical field data, dynamically corrects the physical field data, and realizes physical field association; the adjustment module automatically adjusts the hot press parameters based on the results of dynamic correction using a multi-physical field adaptive optimization algorithm combined with the physical field data and the results of dynamic correction; the operation module directly transmits the adjusted hot press parameters to the hot press remote control unit to complete the operation adjustment.

[0130] This embodiment also provides a computer device suitable for a remote control method of a hot press, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement a remote control method of a hot press as proposed in the above embodiment.

[0131] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0132] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements a remote control method for a hot press as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk.

[0133] In summary, the present invention defines and dynamically corrects the coupling relationship between the temperature field, pressure field and stress field through a multi-physical field coupling analysis model, thereby realizing correlation analysis and dynamic adjustment of the physical field; real-time acquisition of physical field data and the introduction of an online calibration mechanism solve the problem of inaccurate control caused by neglect of the interaction of multiple physical fields in traditional technology; it can accurately capture the dynamic coupling effect between the physical fields, making the physical field data more accurate, and providing a reliable basis for subsequent parameter optimization; ultimately, it effectively improves the processing consistency and accuracy during the operation of the hot press, meets the demand for high-quality processing under complex working conditions, and significantly enhances the intelligence and reliability of the equipment.

[0134] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention 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 invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A remote control method for a hot press, characterized in that: include, Collect physical field data and upload it to the remote control center; Based on physical field data, a dynamic physical field coupling analysis model is constructed to dynamically correct physical field data and realize physical field association; According to the results of dynamic correction, the multi-physics field adaptive optimization algorithm is used to automatically adjust the hot press parameters by combining the physical field data and the results of dynamic correction; The adjusted hot press parameters are directly transmitted to the hot press remote control unit to complete the operation adjustment; The physical field data includes temperature field data, pressure field data, stress field data and historical operation data; The specific steps of constructing the dynamic physical field coupling analysis model are as follows: The input is defined as physical field data, and the output is the physical field data corrected after dynamic adjustment; Define the coupling relationship between temperature field data and pressure field data; Define the coupling relationship between temperature field data and stress field data; Define the coupling relationship between pressure field data and stress field data; According to the defined physical field data coupling relationship, the physical field data is dynamically adjusted and corrected. The expression is: ； in, is the partial derivative of temperature with time, is the symbol of partial derivative, is the temperature, is the thermal conductivity constant, is the Laplace operator, is the time-varying temperature distribution on a two-dimensional plane, is the time-varying heat source term on the two-dimensional plane, is the pressure field coupling term, is the time-varying pressure distribution on a two-dimensional plane, is the stress field coupling term, is the stress distribution in three-dimensional space that changes with time. is the horizontal coordinate of the two-dimensional plane, is the vertical coordinate of the two-dimensional plane, is the time variable, is the horizontal coordinate in three-dimensional space, is the vertical coordinate in three-dimensional space, is the height direction position in three-dimensional space; According to the real-time collected temperature field data, the heat source item is dynamically adjusted and the corrected temperature field data is output; According to the real-time collected pressure field data, the pressure distribution is dynamically adjusted and the corrected pressure field data is output; According to the real-time collected stress field data, the stress distribution is dynamically adjusted and the corrected stress field data is output; An online calibration mechanism is introduced to adaptively adjust and calibrate physical field data.

2. A remote control method for a hot press according to claim 1, characterized in that: The online calibration mechanism is introduced to adaptively adjust and calibrate the physical field data. The specific steps are: Input the corrected temperature field data, dynamically adjust the thermal conductivity constant, and output the calibrated thermal conductivity constant; Input the corrected stress field data, dynamically adjust the stress field parameters, and output the calibrated stress distribution; Input the corrected pressure field data and the corrected stress field data, dynamically calibrate the parameters of the pressure field coupling term and the stress field coupling term, and output the calibrated pressure field coupling coefficient and the stress field coupling coefficient.

3. A remote control method for a hot press according to claim 2, characterized in that: The multi-physics field adaptive optimization algorithm is used to automatically adjust the hot press parameters by combining the physical field data and the results of dynamic correction. The specific steps are: According to the corrected physical field data, the hot press parameters are dynamically adjusted through the multi-physics field adaptive optimization algorithm, combined with the historical operation data and the output of the dynamic physical field coupling analysis model. The expression is: ； in, is the optimization objective function, is the minimization operator, is the spatial integral symbol, is the volume unit, is the target temperature distribution, is the actual temperature distribution on the two-dimensional plane that changes with time, is the square of the temperature error, is the target pressure distribution, is the actual pressure distribution on the two-dimensional plane that changes with time, is the square of the pressure error, is the target stress distribution, is the actual stress distribution in three-dimensional space that changes with time. is the square of the stress error; Set the judgment threshold based on the comparison results between real-time physical field data and optimization targets; According to the optimized target temperature distribution, the heat conduction constant and the heat source term are adjusted to generate the target temperature curve; According to the optimized target pressure distribution, the pressure field coupling coefficient is adjusted to generate a pressure distribution curve; Generate the hot pressing time setting value based on the optimization target stress distribution and optimization results.

4. A remote control method for a hot press according to claim 3, characterized in that: The specific steps of setting the judgment threshold are as follows: when < , then increase the heating power; when > , then reduce the heating power; when = , then keep the current heating power unchanged; when < , then increase the applied pressure; when > , then reduce the pressure; when = , then keep the current pressure unchanged; when < , then adjust the pressure field coupling term and increase the loading pressure; when > , then adjust the pressure field coupling term to reduce the loading pressure; when = , the current loading pressure remains unchanged.

5. A remote control method for a hot press according to claim 4, characterized in that: The adjusted hot press parameters are directly transmitted to the hot press remote control unit to complete the operation adjustment. The specific steps are: Convert the adjusted parameters into hot press execution instructions and send them to the hot press control center via radio communication; Adjust the heating power distribution according to the target temperature curve; According to the pressure distribution curve, uniform force is achieved; Adjust the hot pressing time according to the hot pressing time setting value.

6. A remote control system for a hot press, based on the remote control method for a hot press according to any one of claims 1 to 5, characterized in that: Including, acquisition module, correction module, adjustment module and operation module; The acquisition module is used to collect physical field data and upload it to the remote control center; The correction module is used to construct a dynamic physical field coupling analysis model based on the physical field data, dynamically correct the physical field data, and realize physical field association; The adjustment module is used to automatically adjust the hot press parameters based on the results of the dynamic correction using a multi-physics field adaptive optimization algorithm combined with the physical field data and the results of the dynamic correction; The operation module is used to directly transmit the adjusted hot press parameters to the hot press remote control unit to complete the operation adjustment.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the remote control method for a hot press according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the remote control method for a hot press according to any one of claims 1 to 5 are implemented.

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