Insulation pouring dynamic regulation method and system based on rheological data driving

Abstract

The application provides a rheological data-driven insulating part pouring dynamic regulation method and system, relates to the technical field of data processing, and reflects the correlation between the material flow capacity and the solidification process by acquiring viscosity data, shear response data and solidification stage data, constructing a real-time rheological state model, and outputting corresponding rheological state data; based on the rheological state data, the feature parameters are extracted, the pouring process is divided into stages, and target flow control data is generated; deviation data is generated by combining the pressure and temperature data in the mold cavity, the flow resistance change trend is determined, and the pouring pressure and pouring speed are fed forward adjusted accordingly; in the end compensation stage, pressure compensation regulation is realized according to the viscosity growth inflection point, the dynamic control of the pouring process is realized, and the material flow capacity and the solidification process are matched.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for dynamic control of insulator casting based on rheological data. Background Technology

[0002] In existing technologies, the casting and molding of insulating components is typically achieved based on preset process parameters of the casting or casting equipment, such as controlling material flow and mold filling by setting fixed casting pressure, temperature, and holding time. Some improved solutions introduce sensors to monitor mold cavity pressure or temperature and adjust equipment parameters through simple closed-loop control, but overall, they still rely mainly on empirical parameters or offline experimental data, lacking real-time perception and dynamic coupling control of material rheological properties.

[0003] During the casting of large electrical insulation components (such as epoxy resin insulating sleeves), the viscosity of the material changes significantly with temperature and curing reaction. If a fixed casting pressure (such as 10–15 MPa) and constant flow rate are still used, a sudden increase in flow resistance is likely to occur in the later stages of casting, leading to incomplete filling in some areas or the formation of air bubbles. For example, in thick-walled areas, the resin cannot completely fill the corner structure due to premature thickening, ultimately forming internal voids and defects, affecting insulation performance and withstand voltage strength. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for dynamic control of the casting of insulating components based on rheological data, in order to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0006] A first aspect is a dynamic control method for casting insulating components based on rheological data, the method comprising:

[0007] The viscosity data, shear response data, and curing stage data of the insulating material to be poured are obtained at the current pouring temperature. The viscosity data, shear response data, and curing stage data are coupled and analyzed to construct a real-time rheological state model that reflects the correlation between the material's flowability and the curing process. The real-time rheological state data containing flowability indicators and curing process status information is output.

[0008] Based on real-time rheological state data, characteristic parameters representing the material flow attenuation trend are extracted. Based on the characteristic parameters, the casting process is divided into stages: initial filling stage, intermediate filling stage, and end compensation stage. Target flow control data containing target flow rate and allowable resistance range are generated for each stage.

[0009] The system acquires real-time pressure and temperature data within the mold cavity, fuses and calculates the real-time pressure and temperature data to obtain the current actual flow state data, and compares and analyzes the actual flow state data with the target flow control data to generate deviation data reflecting the degree and rate of deviation of the flow capacity.

[0010] Based on the rate of change information in the deviation data, the growth trend of the flow resistance is determined, and the pouring pressure and pouring speed are feedforward corrected and dynamically adjusted according to the growth trend to generate dynamic pouring control parameters with trend compensation characteristics.

[0011] The insulation material is poured according to the dynamic pouring control parameters. During the end compensation stage, the pressure compensation amount is increased in advance and the compensation duration is adjusted based on the viscosity growth inflection point predicted by real-time rheological state data. This generates end region filling control results that are synchronized with the curing process, so that the material flow capacity of the end region matches the curing process.

[0012] Preferably, the process of constructing a real-time rheological state model includes:

[0013] Viscosity data, shear response data, and curing stage data are synchronized and matched according to the acquisition time to form a unified time series data.

[0014] The unified time series data is segmented and processed. The viscosity change and shear response change are calculated in adjacent time periods. Flow response parameters characterizing the instantaneous flowability of the material are generated by normalization weighting. The reaction process position of the corresponding time period is determined based on the solidification stage data, and reaction process parameters are generated.

[0015] The flow response parameters and reaction process parameters are paired according to the time correspondence, and the changes of the flow response parameters with the reaction process parameters in each time period are continuously recorded to establish the correspondence between the flow capacity and the monotonic change of the curing process.

[0016] Identify the turning point where the rate of change of flow capacity changes abruptly in the correspondence, and use this turning point as the key node for flow capacity decay to generate a flow capacity index that includes the rate of change of flow capacity and the location of the key node.

[0017] A real-time rheological state model is constructed based on the flowability index, and real-time rheological state data characterizing the current material flowability and solidification process state are output through the real-time rheological state model.

[0018] Preferably, the process of determining the stage of the casting process based on characteristic parameters includes:

[0019] Extract the rate of change of flow capacity indicators from real-time rheological state data over a continuous time period, and perform differential processing on the rate of change to generate trend feature parameters that characterize the degree of acceleration of change.

[0020] Based on the numerical range and direction of change of the trend characteristic parameters, a stable range of change rate corresponding to the initial filling stage, a continuously decreasing range of change rate corresponding to the intermediate filling stage, and an accelerated decreasing range of change rate corresponding to the end compensation stage are established. Each range is limited by a joint judgment condition of change rate range and change rate difference results.

[0021] The current rate of change and trend characteristic parameters are matched with each interval item by item. When the conditions of the rate of change range and the degree of change acceleration of the corresponding interval are met at the same time, the current stage of the pouring process is determined.

[0022] When a phase transition is determined, the corresponding flow capacity index value is recorded as the phase transition boundary, and the target flow control data for the corresponding phase is generated based on the phase transition boundary, so that the control objectives of different phases are consistent with the flow capacity change status.

[0023] Preferably, the process of generating dynamic casting control parameters includes:

[0024] The deviation data is continuously sampled in chronological order, the deviation change between adjacent sampling points is calculated, the flow resistance change rate is generated, and the flow resistance change direction is determined based on the consistency of the change rate direction over multiple consecutive time periods, thus forming the flow resistance trend parameter.

[0025] The correlation between the flow resistance trend parameter and the flow capacity index in the real-time rheological state data is determined. When the flow capacity index decreases and the rate of change of flow resistance continues to increase, it is determined to be a flow capacity decay process.

[0026] During the process of flow capacity decay, the adjustment range of the pouring pressure is determined according to the magnitude of the rate of change of flow resistance, and the adjustment range of the pouring speed is determined according to the rate of decrease of the flow capacity index, generating a corresponding feedforward adjustment amount so that the adjustment direction is opposite to the direction of flow capacity change.

[0027] The feedforward adjustment is applied to the current pouring pressure and pouring speed before the deviation data reaches the target flow control data limit range, forming a pre-adjusted dynamic pouring control parameter.

[0028] Preferably, establishing a correspondence between flowability and the monotonic change of curing process includes:

[0029] The flow response parameters within each time period are sorted according to the acquisition time, and the sorted flow response parameters are matched with the corresponding reaction process parameters to generate an initial data pair sequence.

[0030] The direction of change of flow response parameters of adjacent data pairs in the initial data pair sequence is determined, the direction of change determination result is generated, and the effective data pairs with the same direction of change are selected according to the direction of change determination result to generate an effective data sequence.

[0031] Data pairs with opposite directions of change in the valid data sequence are removed, and the resulting data gaps are connected to generate a continuous data sequence.

[0032] The continuous data sequence is sorted according to the reaction process parameters, and the sorting results are checked for monotonicity to generate a monotonic data sequence that satisfies that the flow response parameters change in one direction with the reaction process parameters.

[0033] Establish the correspondence between flowability and curing process based on monotonic data sequences, and output monotonic mapping results to characterize the trend of flowability change.

[0034] Preferably, the flow capacity index, which includes the rate of change of flow capacity and the location of key nodes, is generated, including:

[0035] The changes in flow response parameters between adjacent time periods are calculated and processed to generate a sequence of flow capacity change rates arranged in chronological order.

[0036] The rate of change of flow capacity in adjacent time periods is compared and processed to generate a rate difference sequence. Continuity analysis is then performed on the rate difference sequence to generate a trend sequence.

[0037] Based on the change trend sequence, determine the consistency of the change direction of the change rate difference within a continuous time period, and generate the cumulative change result;

[0038] When the change direction reverses in the cumulative change results and the difference in the rate of change before and after the reversal meets the mutation judgment condition set based on the range of change rate difference, the corresponding time period is determined as the rate of change mutation interval, and mutation interval data is generated.

[0039] Extract the time position when the difference in the rate of change first reaches the mutation judgment condition from the data of the mutation interval, generate the key node position, and correlate the key node position with the flow capacity change rate sequence to generate the flow capacity index.

[0040] Preferably, based on the numerical range and direction of change of the trend characteristic parameters, a stable rate of change interval corresponding to the initial filling stage, a continuously decreasing rate of change interval corresponding to the intermediate filling stage, and an accelerated rate of change interval corresponding to the final compensation stage are established, including:

[0041] Extract key node locations and corresponding trend feature parameter change data from the real-time rheological state model, perform time series segmentation processing on the trend feature parameter change data, and generate segmented trend data.

[0042] Statistical analysis and processing are performed on the trend characteristic parameters before the key node positions in the segmented trend data to generate the stability judgment result of the rate of change, and the stable interval of the rate of change is determined based on the judgment result.

[0043] The trend characteristic parameters of key node locations in the adjacent time period are continuously analyzed and processed to generate a judgment result of continuous decrease in the rate of change, and the interval of continuous decrease in the rate of change is determined based on the judgment result.

[0044] The trend characteristic parameters after the key node position are analyzed by increasing amplitude to generate the result of accelerated decrease in the rate of change, and the range of accelerated decrease in the rate of change is determined based on the result.

[0045] Based on the time distribution relationship of the stable rate of change interval, the continuously decreasing rate of change interval, and the accelerating rate of change interval, the stage division result corresponding to the time series is generated, and the interval mapping relationship used for stage determination is output.

[0046] Secondly, a dynamic control system for casting insulating components based on rheological data, the system comprising:

[0047] The rheological state modeling module is used to acquire viscosity data, shear response data, and curing stage data of the insulating material to be poured at the current pouring temperature. It performs coupled analysis and processing on the viscosity data, shear response data, and curing stage data to construct a real-time rheological state model that reflects the correlation between the material's flowability and the curing process, and outputs real-time rheological state data containing flowability indicators and curing process status information.

[0048] The stage determination module is used to extract characteristic parameters that characterize the material flow attenuation trend based on real-time rheological state data, and to determine the stage of the casting process based on the characteristic parameters, dividing it into the initial filling stage, the intermediate filling stage and the end compensation stage, and generating target flow control data including the target flow rate and allowable resistance range for each stage.

[0049] The deviation data generation module is used to acquire real-time pressure data and real-time temperature data in the mold cavity, perform fusion calculation on the real-time pressure data and real-time temperature data to obtain the current actual flow state data, and compare and analyze the actual flow state data with the target flow control data to generate deviation data that reflects the degree of deviation and rate of change of flow capacity.

[0050] The dynamic control module is used to determine the growth trend of flow resistance based on the rate of change information in the deviation data, and to perform feedforward correction and dynamic adjustment of the pouring pressure and pouring speed according to the growth trend, generating dynamic pouring control parameters with trend compensation characteristics.

[0051] The end-compensation control module is used to execute the pouring of insulating materials according to the dynamic pouring control parameters. During the end-compensation stage, based on the viscosity growth inflection point predicted by real-time rheological state data, the pressure compensation amount is increased in advance and the compensation duration is adjusted to generate end-area filling control results synchronized with the curing process, so that the material flow capacity of the end area is matched with the curing process.

[0052] The above-described solution of the present invention has at least the following beneficial effects:

[0053] By acquiring viscosity data, shear response data, and curing stage data, and constructing a real-time rheological state model, a correspondence is established between the material's flowability and the curing process, thereby avoiding the problem of relying solely on preset process parameters for control.

[0054] Based on this, by extracting characteristic parameters from rheological state data and dividing the process into stages, the casting process is transformed from fixed parameter control to segmented regulation according to changes in material state, thereby adapting to the characteristic that the material viscosity changes with the curing process.

[0055] Furthermore, by combining pressure and temperature data within the mold cavity to generate deviation data, and by adjusting the pouring pressure and pouring speed based on the deviation trend, the control action intervenes in advance before the flow resistance increases, thereby reducing the impact of the sudden increase in flow resistance in the later stages of pouring.

[0056] Based on this, by adjusting the pressure compensation amount and duration according to the viscosity growth inflection point during the end compensation stage, the thick-walled area and complex structure area continue to be continuously filled during the material thickening process, thereby reducing the probability of local insufficient filling and bubble inclusion, and reducing the impact of internal void defects on insulation performance and withstand voltage strength. Attached Figure Description

[0057] Figure 1 This is a flowchart of a dynamic control method for casting insulating components based on rheological data provided in an embodiment of the present invention. Detailed Implementation

[0058] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0059] like Figure 1 As shown, embodiments of the present invention propose a dynamic control method for the casting of insulating components based on rheological data, the method comprising:

[0060] The viscosity data, shear response data, and curing stage data of the insulating material to be poured at the current pouring temperature are obtained. The viscosity data, shear response data, and curing stage data are coupled and analyzed to construct a real-time rheological state model that reflects the correlation between the material's flowability and the curing process. The real-time rheological state model is a mapping relationship model between flowability and curing process.

[0061] Based on real-time rheological state data, characteristic parameters representing the material flow attenuation trend are extracted. Based on the characteristic parameters, the casting process is divided into stages: initial filling stage, intermediate filling stage, and end compensation stage. Target flow control data containing target flow rate and allowable resistance range are generated for each stage.

[0062] The system acquires real-time pressure and temperature data within the mold cavity, fuses and calculates the real-time pressure and temperature data to obtain the current actual flow state data, and compares and analyzes the actual flow state data with the target flow control data to generate deviation data reflecting the degree and rate of deviation of the flow capacity.

[0063] Based on the rate of change information in the deviation data, the growth trend of the flow resistance is determined, and the pouring pressure and pouring speed are feedforward corrected and dynamically adjusted according to the growth trend to generate dynamic pouring control parameters with trend compensation characteristics.

[0064] The insulation material is poured according to the dynamic pouring control parameters. During the end compensation stage, the pressure compensation amount is increased in advance and the compensation duration is adjusted based on the viscosity growth inflection point predicted by real-time rheological state data. This generates end region filling control results that are synchronized with the curing process, so that the material flow capacity of the end region matches the curing process.

[0065] In this embodiment of the invention, by acquiring viscosity data, shear response data, and curing stage data, and performing coupled analysis on the multi-source data, a real-time rheological state model reflecting the correlation between the material's flowability and the curing process is constructed. This enables a unified characterization of the material's flow behavior at different curing stages, and outputs real-time rheological state data containing flowability indicators and curing process status information, providing a continuous and quantifiable state basis for subsequent casting control.

[0066] By extracting characteristic parameters of flow capacity change based on real-time rheological state data, and dividing the casting process into stages according to the rate and trend of change, the division of the initial filling stage, intermediate filling stage and end compensation stage corresponds to the actual flow capacity change process of the material. This allows for the generation of matching target flow control data for different stages, enabling the control strategy to be adjusted according to the material state change.

[0067] By acquiring real-time pressure and temperature data within the mold cavity and comparing them with target flow control data, deviation data reflecting the degree and rate of change of flow capability is generated. This allows the actual flow state within the mold cavity to correspond with the target control state, thus providing a direct basis for subsequent regulation.

[0068] By performing time series analysis on the deviation data and determining the changing trend of the flow resistance, feedforward corrections are made to the pouring pressure and pouring speed based on the changing trend. This allows the adjustment actions to be implemented in advance before the deviation expands, thereby maintaining the continuous filling state of the material as the flowability decreases and avoiding local flow interruption due to adjustment lag.

[0069] By predicting the viscosity growth inflection point based on real-time rheological state data during the end-compensation stage, and increasing the pressure compensation amount and adjusting the compensation duration before the inflection point is reached, the change in flowability in the end region is kept consistent with the solidification process, thereby reducing local incomplete filling and internal defects caused by sudden changes in flowability.

[0070] In a preferred embodiment of the present invention, obtaining viscosity data, shear response data, and curing stage data of the insulating material to be poured at the current pouring temperature includes:

[0071] A viscosity detection unit is installed at the feed end of the casting equipment or the inlet of the mold cavity to continuously sample the insulating material flowing through the detection position, and the viscosity data is calculated based on the correspondence between the pressure change and the flow rate change when the material passes through the detection channel.

[0072] A shear response detection unit is set up in the shear action region to obtain the shear response data of the material by recording the deformation changes of the material under different flow velocity conditions.

[0073] The curing stage data can be segmented and marked based on the pre-established curing process correspondence of the insulating material to be poured within the current pouring temperature range, combined with the pouring time and temperature change process.

[0074] Viscosity data, shear response data, and curing stage data are recorded synchronously in chronological order, and the raw rheological data set is output for subsequent processing.

[0075] In a preferred embodiment of the present invention, real-time pressure data and real-time temperature data are fused and calculated to obtain current actual flow state data. The actual flow state data is then compared and analyzed with target flow control data to generate deviation data reflecting the degree and rate of deviation of flow capacity, including:

[0076] Real-time pressure data and corresponding real-time temperature data at multiple locations within the mold cavity are collected and synchronized in chronological order to generate a combined pressure and temperature data sequence.

[0077] Real-time pressure data and real-time temperature data are correlated according to the same time point and the same collection location, and the actual flow state data is obtained by integrating the combined effects of pressure increase and temperature change on the flow state.

[0078] The actual flow status data and the target flow control data are compared item by item within the same time period to determine the degree of difference between the two and generate deviation data for the corresponding time period.

[0079] By comparing and processing deviation data over a continuous time period, the changing trend of the degree of deviation is determined, and deviation data characterizing the rate of change of deviation is generated.

[0080] In a preferred embodiment of the present invention, during the end-compensation stage, based on the viscosity growth inflection point predicted by real-time rheological state data, the pressure compensation amount is increased in advance and the compensation duration is adjusted to generate an end-region filling control result synchronized with the curing process, including:

[0081] Extract the changes in flow capacity indicators from real-time rheological state data over a continuous time period, and identify the key nodes where the rate of change changes from a stable change to an accelerated change, and take these key nodes as the inflection points of viscosity growth.

[0082] When a location close to a critical node is detected, the pressure compensation is increased in advance based on the decreasing flow capacity, so that the material can obtain additional driving force before the viscosity rises rapidly.

[0083] Adjust the duration of pressure compensation based on the duration of the rate of change in flowability, so that the compensation process covers the critical time period of viscosity growth.

[0084] During the compensation process, the flow status is continuously monitored to ensure that the material in the end region remains in continuous flow throughout the curing process, generating end region filling control results that are synchronized with the curing process.

[0085] In a preferred embodiment of the present invention, the process of constructing a real-time rheological state model includes:

[0086] Viscosity data, shear response data, and curing stage data are synchronized and matched according to the acquisition time to form a unified time series data.

[0087] The unified time series data is segmented, and the viscosity change amplitude and shear response change amplitude are calculated in adjacent time periods. Flow response parameters characterizing the instantaneous flowability of the material are generated by normalization and weighting. The reaction process position of the corresponding time period is determined based on the curing stage data, and reaction process parameters are generated. The reaction process parameters are used to characterize the positional order of the curing stage data in the continuous curing process.

[0088] The flow response parameters and reaction process parameters are paired according to the time correspondence, and the changes of the flow response parameters with the reaction process parameters in each time period are continuously recorded to establish the correspondence between the flow capacity and the monotonic change of the curing process.

[0089] Identify the turning point where the rate of change of flow capacity changes abruptly in the correspondence, and use this turning point as the key node for flow capacity decay to generate a flow capacity index that includes the rate of change of flow capacity and the location of the key node.

[0090] A real-time rheological state model is constructed based on the flowability index, and real-time rheological state data characterizing the current material flowability and solidification process state are output through the real-time rheological state model.

[0091] In this embodiment of the invention, viscosity data, shear response data, and curing stage data are synchronously matched according to the acquisition time to form unified time series data. This allows data from different sources to be processed correspondingly under the same time reference, thereby avoiding data misalignment caused by differences in acquisition time. By segmenting the unified time series data and extracting flow response parameters and reaction process parameters, a direct correlation is established between material flow behavior and the curing process. Furthermore, by continuously recording the changes in flow response parameters with reaction process parameters and constructing a monotonically changing correspondence, the flowability change process is made continuous and directionally consistent. By identifying the turning points where the rate of change abruptly changes and determining key nodes, the structural changes in the flowability change process are clearly identified. Finally, a real-time rheological state model is constructed based on the flowability index, and corresponding state data is output, enabling continuous characterization of the material's flowability changes at different curing stages and providing a unified data foundation for subsequent stage determination and control adjustment.

[0092] In a preferred embodiment of the present invention, the uniform time series data is segmented, the viscosity change amplitude and shear response change amplitude are calculated within adjacent time periods, and flow response parameters characterizing the instantaneous flowability of the material are generated by normalized weighting, including:

[0093] The unified time series data after synchronization and matching is segmented according to a preset time window, where the length of the time window is set according to the rheological change rate of the casting material.

[0094] Within each time window, the difference between the viscosity values ​​at the start and end of the window is calculated to obtain the viscosity change range within that time window.

[0095] Within the same time window, the variation amplitude of the shear response data is calculated. The shear response data consists of the relationship between the shear rate and the corresponding shear stress. In practice, the shear stress value under the condition that the shear rate is kept constant is selected as the characterization index. The variation amplitude of the shear response is obtained by calculating the difference between the shear stress values ​​at the beginning and end of the time window.

[0096] Flow response parameters are constructed based on the viscosity change range and the shear response change range to characterize the instantaneous flow capability of the material within the time window.

[0097] In one embodiment, the flow response parameters can be calculated using the following mathematical formula: ;

[0098] : No. Flow response parameters within a time window;

[0099] : No. The start time of each time window;

[0100] Time window length (satisfying) );

[0101] : No. The end time of each time window;

[0102] :time The viscosity function;

[0103] At a constant shear rate Under the conditions, at time Shear stress;

[0104] Preset constant shear rate;

[0105] : Normalized weighting coefficient for viscosity variation;

[0106] : Normalized weighting coefficient for shear response change.

[0107] This formula uses a unified time window Within the experiment, the changes in viscosity and shear stress at the start and end times were calculated using differential methods, and after normalization, they were weighted and combined to obtain the flow response parameters characterizing the instantaneous flowability of the material. .

[0108] In one embodiment, the viscosity function can be expressed using the following mathematical formula: .

[0109] In a preferred embodiment of the present invention, a real-time rheological state model is constructed based on the flowability index, and real-time rheological state data characterizing the current material flowability and solidification process state is output through the real-time rheological state model, including:

[0110] The flowability indicators are arranged in the order of the reaction process, and the changes in flowability at each time period are integrated to generate a data sequence of flowability changes with the curing process.

[0111] Establish a mapping relationship between flow capacity and solidification process based on data sequence, so that each solidification stage corresponds to a unique flow capacity state;

[0112] During the pouring process, the input data of the current time period is matched with the mapping relationship to determine the current flowability state and solidification stage of the material.

[0113] The output contains real-time rheological state data including the current flow capacity status and corresponding solidification stage information, which is used for subsequent stage determination and control adjustment.

[0114] In a preferred embodiment of the present invention, the process of determining the stage of the pouring process based on characteristic parameters includes:

[0115] Extract the rate of change of flow capacity indicators from real-time rheological state data over a continuous time period, and perform differential processing on the rate of change to generate trend feature parameters that characterize the degree of acceleration of change.

[0116] Based on the numerical range and direction of change of the trend characteristic parameters, a stable range of change rate corresponding to the initial filling stage, a continuously decreasing range of change rate corresponding to the intermediate filling stage, and an accelerated decreasing range of change rate corresponding to the end compensation stage are established. Each range is limited by a joint judgment condition of change rate range and change rate difference results.

[0117] The current rate of change and trend characteristic parameters are matched with each interval item by item. When the conditions of the rate of change range and the degree of change acceleration of the corresponding interval are met at the same time, the current stage of the pouring process is determined.

[0118] When a phase transition is determined, the corresponding flow capacity index value is recorded as the phase transition boundary, and the target flow control data for the corresponding phase is generated based on the phase transition boundary, so that the control objectives of different phases are consistent with the flow capacity change status.

[0119] In this embodiment of the invention, by extracting the rate of change of flowability indicators from real-time rheological state data and performing differential processing on the rate of change to generate trend characteristic parameters, the flowability change process is transformed from a single numerical change into an information expression including the direction and degree of change. By establishing different intervals based on the range of change rates and the differential results of change rates, the stage division is based on the flowability change itself, rather than a preset time or fixed parameters. By matching the current rate of change and trend characteristic parameters with each interval, and determining the current casting stage when the corresponding conditions are met, the stage determination result is consistent with the actual flow state of the material. By recording the flowability indicator value as a boundary during stage switching and generating target flow control data for the corresponding stage based on the boundary, the control targets of different stages can correspond to the flowability change process, thereby achieving linkage between stage division and control strategy.

[0120] In a preferred embodiment of the present invention, the method for determining the range of change rate and the degree of acceleration of change conditions for the corresponding interval includes:

[0121] The flow capacity index values ​​are obtained from real-time rheological state data over a continuous period of time, and the rate of change data sequence corresponding to each time period is determined based on the difference between adjacent time periods.

[0122] By comparing the rate of change of adjacent time periods in the rate of change data sequence again, the magnitude and direction of the rate of change are determined, thereby generating trend characteristic parameters that characterize the degree of acceleration of change.

[0123] Statistical processing is performed on the rate of change data sequence to extract the time intervals in which the direction of change is consistent and the magnitude of change remains stable within a continuous time period, and the range of the rate of change value corresponding to the time interval is determined as the stable range of the rate of change.

[0124] The intervals in which the rate of change continuously decreases and no reversal occurs within multiple consecutive time periods are identified, and the range of the rate of change within these intervals is defined as the intervals in which the rate of change continuously decreases.

[0125] By analyzing the trend characteristic parameters, when the rate of change decreases gradually increases over a continuous period of time, and the rate of change in each period shows an increasing trend compared to the previous period, the corresponding time interval is determined as the interval of accelerated rate of change decrease.

[0126] Record the range of change rate values ​​and the range of acceleration values ​​corresponding to the stable change rate interval, the continuously decreasing change rate interval, and the accelerated decrease change rate interval, respectively, as the interval determination conditions when determining the stage.

[0127] In a preferred embodiment of the present invention, the process of generating dynamic casting control parameters includes:

[0128] The deviation data is continuously sampled in chronological order, the deviation change between adjacent sampling points is calculated, the flow resistance change rate is generated, and the flow resistance change direction is determined based on the consistency of the change rate direction over multiple consecutive time periods, thus forming the flow resistance trend parameter.

[0129] The correlation between the flow resistance trend parameter and the flow capacity index in the real-time rheological state data is determined. When the flow capacity index decreases and the rate of change of flow resistance continues to increase, it is determined to be a flow capacity decay process.

[0130] During the process of flow capacity decay, the adjustment range of the pouring pressure is determined according to the magnitude of the rate of change of flow resistance, and the adjustment range of the pouring speed is determined according to the rate of decrease of the flow capacity index, generating a corresponding feedforward adjustment amount so that the adjustment direction is opposite to the direction of flow capacity change.

[0131] The feedforward adjustment is applied to the current pouring pressure and pouring speed before the deviation data reaches the target flow control data limit range, forming a pre-adjusted dynamic pouring control parameter.

[0132] In this embodiment of the invention, by continuously sampling deviation data and calculating the change between adjacent sampling points, a flow resistance change rate is generated, enabling the flow state change within the mold cavity to be expressed in a time series format. By determining the consistency of the change rate direction over multiple time periods, a flow resistance trend parameter is formed, providing a basis for trend judgment of flow state changes. By establishing a correspondence between the flow resistance trend parameter and flow capacity indicators, and identifying a flow capacity decay process when flow capacity decreases and flow resistance continuously increases, control adjustments can respond to specific changes. By determining the adjustment range of casting pressure and casting speed based on the flow resistance change rate and the flow capacity decrease rate, respectively, a feedforward adjustment amount is generated, ensuring the adjustment direction corresponds to the flow capacity change direction. By applying adjustment before the deviation data reaches the target control range, the control action intervenes in the flow state change process in advance, thereby maintaining the continuous flow state of the material during the casting process.

[0133] In a preferred embodiment of the present invention, the adjustment range of the pouring pressure is determined based on the magnitude of the rate of change of the flow resistance, and the adjustment range of the pouring speed is determined based on the rate of decrease of the flow capacity index, thereby generating a corresponding feedforward adjustment amount, including:

[0134] The variation of deviation data over a continuous time period is processed to obtain a sequence of flow resistance change rates. Based on the magnitude of the values ​​in each time period of the sequence, the flow resistance change rate is classified into multiple rate level intervals corresponding to different degrees of change.

[0135] For different rate ranges, the corresponding pouring pressure adjustment range is preset. When the rate of change of flow resistance is in a certain range, the pouring pressure adjustment range corresponding to that range is selected, and the adjustment direction is determined to be to increase the pouring pressure.

[0136] The changes in flow capacity indicators over a continuous time period are obtained from real-time rheological state data. The rate of decline of the flow capacity indicators is calculated, and the rate of decline is classified into multiple rate level intervals corresponding to different degrees of decline.

[0137] For different descent rate ranges, the corresponding pouring speed adjustment range is preset. When the descent rate of the flowability index is in a certain range, the pouring speed adjustment range corresponding to that range is selected, and the adjustment direction is determined to be to reduce the pouring speed.

[0138] The determined adjustment ranges for pouring pressure and pouring speed are combined to generate a corresponding feedforward adjustment. This feedforward adjustment is applied to the current pouring pressure and pouring speed before the deviation data reaches the target flow control data limit, thus achieving early adjustment. The pressure compensation amount in the end-compensation stage is the compensation control amount formed based on the pouring pressure adjustment range.

[0139] The method for setting the preset pouring pressure adjustment range includes:

[0140] Based on historical casting process data, the cavity filling state and defect distribution corresponding to different flow resistance change rates are extracted, and the casting process with no defects or defects that meet the process requirements is used as a reference sample.

[0141] In the reference sample, the correlation between the rate of change of flow resistance and the corresponding change of pouring pressure is statistically analyzed in chronological order to form the correlation data between the rate of change of flow resistance and the adjustment requirements of pouring pressure.

[0142] The associated data is divided into intervals, and the rate of change of flow resistance is divided into multiple rate level intervals in ascending order. The range of injection pressure adjustment required to maintain stable filling within each rate level interval is calculated.

[0143] For each rate level range, a casting pressure adjustment range that allows the material to maintain continuous flow within the range without causing local underfilling is selected, and the midpoint of this adjustment range is taken as the corresponding casting pressure adjustment range.

[0144] The adjustment range of the pouring pressure corresponding to each rate level range is continuously verified, so that the adjustment range between adjacent ranges increases step by step, thereby generating a set of pouring pressure adjustment ranges that gradually increase with the rate of change of flow resistance.

[0145] The method for setting the preset pouring speed adjustment range includes:

[0146] Extract the rate of decrease of flowability index at different solidification stages from historical rheological data, and record the changes in pouring speed and final filling quality results within the corresponding time period;

[0147] Casting processes that maintain continuous material flow and do not exhibit bubble inclusions or void defects during the process of decreasing flowability are selected as reference samples for speed adjustment.

[0148] The correlation between the rate of decrease of the flowability index and the change of the casting speed in the reference sample was statistically processed, and the flow rate was divided into multiple ranges of decreasing rate in ascending order.

[0149] For each rate of decline, the range of pouring speed variation that can maintain the stable flow of the material is statistically analyzed, and the speed variation value that can avoid flow interruption within this range is selected as the corresponding pouring speed adjustment range.

[0150] The pouring speed adjustment range corresponding to each descent rate level range is continuously adjusted so that the pouring speed adjustment range changes stepwise with the increase of the descent rate of the flow capacity index, and ensures that there are no sudden changes between adjacent ranges, thereby forming a stable set of pouring speed adjustment ranges.

[0151] The set of pouring speed adjustment ranges and the set of pouring pressure adjustment ranges are jointly calibrated so that the combined adjustment of the two within the same time period can maintain the matching relationship between the material flowability and the curing process.

[0152] In a preferred embodiment of the present invention, establishing a correspondence between flowability and the monotonic change of curing process includes:

[0153] The flow response parameters within each time period are sorted according to the acquisition time, and the sorted flow response parameters are matched with the corresponding reaction process parameters to generate an initial data pair sequence.

[0154] The direction of change of flow response parameters of adjacent data pairs in the initial data pair sequence is determined, the direction of change determination result is generated, and the effective data pairs with the same direction of change are selected according to the direction of change determination result to generate an effective data sequence.

[0155] Data pairs with opposite directions of change in the valid data sequence are removed, and the resulting data gaps are connected to generate a continuous data sequence.

[0156] The continuous data sequence is sorted according to the reaction process parameters, and the sorting results are checked for monotonicity to generate a monotonic data sequence that satisfies that the flow response parameters change in one direction with the reaction process parameters.

[0157] Establish the correspondence between flowability and curing process based on monotonic data sequences, and output monotonic mapping results to characterize the trend of flowability change.

[0158] In this embodiment of the invention, flow response parameters are sorted according to acquisition time and matched with reaction process parameters to generate an initial data pair sequence, enabling the material flow behavior and the solidification process to be expressed in the same data structure. By determining the direction of change of adjacent data pairs and filtering out valid data sequences with consistent directions of change, the trend of change in the data sequence remains consistent. Data pairs with opposite directions of change are removed, and the resulting data gaps are connected, ensuring the data sequence maintains continuity while eliminating abnormal fluctuations. Monotonicity verification of the continuous data sequence generates a monotonic data sequence that satisfies the requirement that the flow response parameters change in a single direction with the reaction process parameters, ensuring a stable evolution direction for the flow capacity change process. Based on the monotonic data sequence, a correspondence between flow capacity and the solidification process is established, enabling a continuous mapping between the flow capacity change trend and the solidification process, providing a stable data foundation for key node identification and stage division.

[0159] In a preferred embodiment of the present invention, the direction of change of the flow response parameters of adjacent data pairs in the initial data pair sequence is determined to generate a direction of change determination result. Based on the direction of change determination result, valid data pairs with consistent direction of change are selected to generate a valid data sequence, including:

[0160] According to the order of the initial data pair sequence, the flow response parameter values ​​in the previous data pair and the next data pair are read in sequence, and the flow response parameter in the next data pair is compared with the flow response parameter in the previous data pair to see whether it increases, decreases or remains unchanged, thereby generating a corresponding change direction mark for each pair of adjacent data pairs.

[0161] Arrange the change direction markers of each adjacent data pair in chronological order to form a sequence of change direction determination results, and count the consistency of change direction markers in multiple consecutive adjacent data pairs.

[0162] When the change direction markers of multiple consecutive adjacent data pairs are all increasing, the consecutive segment is determined as a positive change segment; when the change direction markers of multiple consecutive adjacent data pairs are all decreasing, the consecutive segment is determined as a negative change segment; when the change direction markers of adjacent data pairs remain unchanged, the adjacent data pairs are assigned to a consecutive segment consistent with the dominant change direction before and after them.

[0163] Using continuous segments as the filtering unit, data pairs with consistent change directions and continuous lengths reaching the preset time period are retained, and the retained data pairs are output as valid data sequences according to their original arrangement order.

[0164] When there are segments in the initial data pair sequence where the direction of change frequently switches, segments where the number of direction changes exceeds a preset number are identified as abnormal fluctuation segments, and data pairs in these abnormal fluctuation segments are not included in the valid data sequence. Based on the expected direction of change in the flowability of the target insulating material during the curing process, continuous segments consistent with the expected direction of change are selected as valid data sequences.

[0165] In a preferred embodiment of the present invention, data pairs with opposite directions of change in the effective data sequence are removed, and the resulting data gaps are connected to generate a continuous data sequence, including:

[0166] The direction of change for each data pair in the valid data sequence is checked again. When the dominant direction of change for a data pair is inconsistent with that of its preceding and following data pairs, the data pair is identified as a data pair with the opposite direction of change.

[0167] Remove data pairs with the opposite direction of change from the valid data sequence, and record the adjacent retained data pairs before and after the deletion position to generate gap position information after removal;

[0168] When there is only one deleted data pair before and after the gap position after removal, the adjacent retained data pairs before and after the deletion position are directly connected in sequence to form a local continuous connection segment.

[0169] When multiple deleted data pairs exist consecutively in the gap position after removal, the retained data pair at the front of the deleted section is taken as the gap start point, and the retained data pair at the back of the deleted section is taken as the gap end point. The gap start point and the gap end point are continuously connected to form a cross-gap connection segment.

[0170] Each local continuous connection segment and the cross-gap connection segment are spliced ​​together in the original time order to generate a continuous data sequence, so that adjacent data pairs in the continuous data sequence are consistent in the direction of change and the data arrangement is continuous.

[0171] In a preferred embodiment of the present invention, the continuous data sequence is sorted according to the reaction process parameters, and the sorting result is checked for monotonicity to generate a monotonic data sequence that satisfies the requirement that the flow response parameters change in a unidirectional direction with the reaction process parameters, including:

[0172] Extract the reaction process parameters corresponding to each data pair in the continuous data sequence, and rearrange them according to the reaction process parameters from smallest to largest, so that the data pairs in the continuous data sequence form a sorting result consistent with the solidification progress order;

[0173] After the rearrangement is completed, the flow response parameters of adjacent data pairs in the sorting results are compared in turn to determine whether the flow response parameters of the next data pair continue to change in the same direction relative to the flow response parameters of the previous data pair, and a monotonicity verification result is generated.

[0174] When the flow response parameters of all adjacent data pairs in the sorting result show a continuous increase, the sorting result is determined as an increasing monotonic data sequence; when the flow response parameters of all adjacent data pairs in the sorting result show a continuous decrease, the sorting result is determined as a decreasing monotonic data sequence.

[0175] When there are individual adjacent data pairs in the sorting results that do not meet the condition of continuous increase or continuous decrease, the data pairs that do not meet the monotonicity condition are marked as data pairs to be corrected, and the data pairs to be corrected are removed. Then the monotonicity check is performed again.

[0176] When the flow response parameters of each adjacent data pair in the re-verified sorting result change in the same direction as the reaction process parameters advance, the sorting result is output as a monotonic data sequence that satisfies the requirement that the flow response parameters change in a single direction as the reaction process parameters advance.

[0177] In a preferred embodiment of the present invention, generating a flow capacity index that includes the rate of change of flow capacity and the location of key nodes includes:

[0178] The changes in flow response parameters between adjacent time periods are calculated and processed to generate a sequence of flow capacity change rates arranged in chronological order.

[0179] The rate of change of flow capacity in adjacent time periods is compared and processed to generate a rate difference sequence. Continuity analysis is then performed on the rate difference sequence to generate a trend sequence.

[0180] Based on the change trend sequence, determine the consistency of the change direction of the change rate difference within a continuous time period, and generate the cumulative change result;

[0181] When the change direction reverses in the cumulative change results and the difference in the rate of change before and after the reversal meets the mutation judgment condition set based on the range of change rate difference, the corresponding time period is determined as the rate of change mutation interval, and mutation interval data is generated.

[0182] Extract the time position when the difference in the rate of change first reaches the mutation judgment condition from the data of the mutation interval, generate the key node position, and correlate the key node position with the flow capacity change rate sequence to generate the flow capacity index.

[0183] In this embodiment of the invention, by calculating the changes in flow response parameters between adjacent time periods, a flow capacity change rate sequence is generated, transforming the flow capacity change process from discrete data into continuous change information. By comparing the change rate sequences and generating a change rate difference sequence, the relationship between changes in adjacent time periods is further expressed. By performing continuity analysis on the change rate difference sequence, a change trend sequence is generated, revealing the cumulative change characteristics during the change process. By performing consistency judgment on the change trend sequence and forming a cumulative change result, the staged trends of flow capacity change can be identified. By determining the change rate abrupt change interval when the change direction reverses and meets the abrupt change judgment condition, and extracting key node positions within this interval, the structural transformation during the flow capacity change process is clearly located. By associating the key node positions with the change rate sequence, a flow capacity index is generated, enabling the identification of the transition process from stable to accelerated flow capacity change, providing a basis for stage division and control regulation.

[0184] In a preferred embodiment of the present invention, the rate of change of adjacent time periods in the flow capacity change rate sequence is compared to generate a rate of change difference sequence, and a continuity analysis is performed on the rate of change difference sequence to generate a trend sequence, including:

[0185] Read the rate of change values ​​of adjacent time periods in the flow capacity change rate sequence in chronological order, compare the rate of change value of the later time period with the rate of change value of the previous time period to obtain the degree of change between the two, and use the degree of change as the rate of change difference of the corresponding time period to generate a rate of change difference sequence in sequence.

[0186] The direction of each difference in the rate of change difference sequence is determined. When the subsequent difference shows an increasing trend compared to the previous difference, it is marked as a positive change. When the subsequent difference shows a decreasing trend compared to the previous difference, it is marked as a negative change. When the magnitude of the difference change is within the preset difference change range, it is marked as a stable change.

[0187] The direction of change in each time period is marked and arranged in chronological order to form a sequence of direction of change. Continuity analysis is then performed on the sequence of direction of change to identify segments in which the direction of change remains consistent across multiple consecutive time periods.

[0188] By integrating the direction and magnitude of change in corresponding time periods using continuous segments as units, a trend sequence is generated, which can reflect the continuous evolution of the rate of change difference in the time dimension.

[0189] The method for setting the preset difference range includes:

[0190] The flow capacity change rate sequence was obtained from the historical casting process, and the change rate difference corresponding to each time period was statistically processed to form a change rate difference sample set.

[0191] The sample set of rate of change difference is sorted according to the numerical size, and the distribution frequency of the difference in different numerical intervals is counted to obtain the distribution interval of the rate of change difference and its corresponding concentration segment.

[0192] Identify the segments in the distribution range where the rate of change difference is concentrated, and use the range of difference corresponding to the segment as the basic fluctuation range to characterize the normal change level of the material under steady flow conditions.

[0193] The differences within the basic fluctuation range are further screened to remove abnormal deviations caused by sampling errors or instantaneous disturbances, and the remaining differences are subjected to interval compression to generate a reference difference range for characterizing stable changes.

[0194] The reference difference range is used as the preset difference change range to determine whether the change rate difference between adjacent time periods belongs to a stable change state.

[0195] In practical applications, the preset difference range is adaptively modified based on the current pouring temperature and batch differences of materials to ensure consistency with the current material rheological properties, thereby guaranteeing the accuracy of stable change determination.

[0196] In a preferred embodiment of the present invention, determining the consistency of the direction of change of the rate difference within a continuous time period based on the change trend sequence, and generating a cumulative change result, includes:

[0197] Analyze each continuous segment in the trend sequence segment by segment, count the number of time periods in each continuous segment where the direction of change remains consistent, and record the start and end positions of the continuous segment.

[0198] When the direction of change within a certain continuous segment remains consistent across multiple consecutive time periods, the continuous segment is defined as a segment with consistent direction of change, and the difference in the rate of change between time periods within that segment is accumulated and recorded to generate corresponding cumulative change data.

[0199] Based on the cumulative change data, within the same segment with the same direction of change, the difference in the rate of change of each time period is accumulated and recorded segment by segment in chronological order, so that the cumulative change of subsequent time periods reflects the continuous impact of the changes of previous time periods, thus forming a sequence of cumulative change results.

[0200] When the direction of change in the trend sequence changes from positive to negative or vice versa, the location of the change is marked as the direction reversal point. The direction reversal point is used as the dividing point of the cumulative change results, and corresponding cumulative change results are generated for different segments.

[0201] In a preferred embodiment of the present invention, the method for determining the mutation determination condition based on the range of change rate difference includes:

[0202] Statistical processing is performed on the rate of change difference sequence over the complete time range to extract the maximum, minimum and intermediate distribution range of the rate of change difference, and the overall range of change of the rate of change difference is determined accordingly.

[0203] Based on the overall range of change, the rate of change difference is divided into multiple intervals, and the difference range located in the high change interval is selected as the candidate range for mutation. At the same time, the reference range for mutation determination is determined by combining the segments in the cumulative change results where the change amplitude continues to increase. The high change interval is the interval closer to the maximum value in the distribution of rate of change difference.

[0204] In a trend sequence, when the rate of change difference in a certain time period enters the candidate range of abrupt change, and the direction of change corresponding to that time period is inconsistent with the direction of change of the previous continuous segment, that time period is marked as the abrupt change trigger point.

[0205] Further compare the difference in the rate of change before and after the mutation trigger point. When the difference in the rate of change corresponding to the mutation trigger point is higher than the difference in the rate of change of the previous time period, it is confirmed that the time period meets the mutation judgment condition.

[0206] The time period that meets the mutation determination criteria is output as the starting position of the rate of change mutation interval, and the range of the mutation interval is determined by combining the cumulative change results, so as to be used for the subsequent extraction of key node positions.

[0207] In a preferred embodiment of the present invention, based on the numerical range and direction of change of the trend characteristic parameters, a stable rate of change interval corresponding to the initial filling stage, a continuously decreasing rate of change interval corresponding to the intermediate filling stage, and an accelerated rate of change interval corresponding to the final compensation stage are established, including:

[0208] Extract key node locations and corresponding trend feature parameter change data from the real-time rheological state model, perform time series segmentation processing on the trend feature parameter change data, and generate segmented trend data.

[0209] Statistical analysis and processing are performed on the trend characteristic parameters before the key node positions in the segmented trend data to generate the stability judgment result of the rate of change, and the stable interval of the rate of change is determined based on the judgment result.

[0210] The trend characteristic parameters of key node locations in the adjacent time period are continuously analyzed and processed to generate a judgment result of continuous decrease in the rate of change, and the interval of continuous decrease in the rate of change is determined based on the judgment result.

[0211] The trend characteristic parameters after the key node position are analyzed by increasing amplitude to generate the result of accelerated decrease in the rate of change, and the range of accelerated decrease in the rate of change is determined based on the result.

[0212] Based on the time distribution relationship of the stable rate of change interval, the continuously decreasing rate of change interval, and the accelerating rate of change interval, the stage division result corresponding to the time series is generated, and the interval mapping relationship used for stage determination is output.

[0213] In this embodiment of the invention, key node positions and corresponding trend characteristic parameter change data are extracted from a real-time rheological state model and processed through time series segmentation to generate segmented trend data, thus decomposing the flow capacity change process according to a time structure. Statistical analysis of the trend characteristic parameters before the key node positions determines the stable rate of change intervals, expressing the characteristics of the material during the stable flow capacity phase. Continuous analysis of the trend characteristic parameters in the time period adjacent to the key node determines the continuously decreasing rate of change intervals, dividing the flow capacity gradually decaying phase. Incremental analysis of the trend characteristic parameters after the key node determines the accelerating rate of change intervals, identifying the rapid flow capacity decay phase. By integrating the intervals according to their time distribution, a phase division result corresponding to the time series is generated, and the interval mapping relationship is output, ensuring that the phase division is based on the flow capacity change process itself, thus maintaining consistency between the phase determination result and the actual flow state.

[0214] In a preferred embodiment of the present invention, statistical analysis is performed on the trend characteristic parameters before the key node positions in the segmented trend data to generate a stability determination result of the rate of change, and the stability interval of the rate of change is determined based on the determination result, including:

[0215] Extract all trend characteristic parameters before the key node positions from the segmented trend data, and form a stability analysis data sequence in chronological order;

[0216] The trend characteristic parameters of adjacent time periods in the stability analysis data sequence are compared to determine the direction and magnitude of change between time periods. When the direction of change is consistent and the magnitude of change is within the preset difference range in multiple consecutive time periods, the corresponding time period is marked as a stable change time period.

[0217] The number of consecutive stable change time periods is counted, and the corresponding start and end positions are recorded. When the number of consecutive stable change time periods reaches the preset number of time periods, the consecutive segment is determined as a stable candidate segment.

[0218] The trend characteristic parameters within the stable candidate segment are statistically analyzed to confirm that the rate of change within the segment does not fluctuate significantly throughout the segment, and the stability judgment result of the rate of change is output.

[0219] Based on the stability assessment results, the corresponding time interval is determined as the stable interval of the rate of change, and the range of values ​​of the trend characteristic parameters corresponding to this interval is recorded.

[0220] In a preferred embodiment of the present invention, the trend characteristic parameters of the key node location in the adjacent time period are subjected to continuous analysis processing to generate a determination result of continuous decrease in the rate of change, and the interval of continuous decrease in the rate of change is determined according to the determination result, including:

[0221] Extract trend characteristic parameters within a preset time range before and after the key node location to form a data sequence for adjacent segment analysis;

[0222] The trend characteristic parameters of adjacent time periods in the analysis data sequence of adjacent segments are compared segment by segment. When the trend characteristic parameter of the later time period continues to decrease compared with the previous time period, the time period is marked as a period of decreasing change.

[0223] Aggregate the time periods that are continuously marked as decreasing, count the length of the continuous decreasing time periods, and record the corresponding start and end times;

[0224] When the length of a continuous descent period reaches the preset number of time periods, and no direction reversal occurs within that period, the period is identified as a candidate continuous descent period.

[0225] Based on the statistical results of the continuously decreasing candidate segments, a result is generated to determine the continuously decreasing rate of change, and the candidate segment is identified as the interval with the continuously decreasing rate of change.

[0226] In a preferred embodiment of the present invention, the trend characteristic parameters after the key node position are analyzed by increasing amplitude to generate a determination result of accelerated rate of change, and the accelerated rate of change interval is determined based on the determination result, including:

[0227] Extract trend characteristic parameter data after key node positions and form an accelerated analysis data sequence according to time order;

[0228] The magnitude of change of trend characteristic parameters in adjacent time periods of the accelerated analysis data sequence is calculated to obtain the magnitude of change data for each time period.

[0229] Compare the magnitude of change within a continuous time period. When the magnitude of change in a later time period is greater than that in a previous time period, mark that time period as a period of increasing magnitude.

[0230] Statistical analysis is performed on consecutive time periods marked as increasing in magnitude. When the number of consecutive time periods reaches the preset number of time periods, and the magnitude of change shows a gradual increasing trend within the segment, the segment is identified as a candidate segment for accelerated decline.

[0231] Based on the statistical results of the candidate accelerated descent segments, an accelerated descent rate determination result is generated, and the corresponding time segment is determined as the accelerated descent rate interval.

[0232] Embodiments of the present invention also provide a dynamic control system for the casting of insulating components based on rheological data, the system comprising:

[0233] The rheological state modeling module is used to acquire viscosity data, shear response data, and curing stage data of the insulating material to be poured at the current pouring temperature. It performs coupled analysis and processing on the viscosity data, shear response data, and curing stage data to construct a real-time rheological state model that reflects the correlation between the material's flowability and the curing process, and outputs real-time rheological state data containing flowability indicators and curing process status information.

[0234] The stage determination module is used to extract characteristic parameters that characterize the material flow attenuation trend based on real-time rheological state data, and to determine the stage of the casting process based on the characteristic parameters, dividing it into the initial filling stage, the intermediate filling stage and the end compensation stage, and generating target flow control data including the target flow rate and allowable resistance range for each stage.

[0235] The deviation data generation module is used to acquire real-time pressure data and real-time temperature data in the mold cavity, perform fusion calculation on the real-time pressure data and real-time temperature data to obtain the current actual flow state data, and compare and analyze the actual flow state data with the target flow control data to generate deviation data that reflects the degree of deviation and rate of change of flow capacity.

[0236] The dynamic control module is used to determine the growth trend of flow resistance based on the rate of change information in the deviation data, and to perform feedforward correction and dynamic adjustment of the pouring pressure and pouring speed according to the growth trend, generating dynamic pouring control parameters with trend compensation characteristics.

[0237] The end-compensation control module is used to execute the pouring of insulating materials according to the dynamic pouring control parameters. During the end-compensation stage, based on the viscosity growth inflection point predicted by real-time rheological state data, the pressure compensation amount is increased in advance and the compensation duration is adjusted to generate end-area filling control results synchronized with the curing process, so that the material flow capacity of the end area is matched with the curing process.

[0238] It should be noted that this system is a system corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0239] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0240] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0241] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for dynamic control of insulating component casting based on rheological data, characterized in that, The method includes: The viscosity data, shear response data, and curing stage data of the insulating material to be poured are obtained at the current pouring temperature. The viscosity data, shear response data, and curing stage data are coupled and analyzed to construct a real-time rheological state model that reflects the correlation between the material's flowability and the curing process. The real-time rheological state data containing flowability indicators and curing process status information is output. Based on real-time rheological state data, characteristic parameters representing the material flow attenuation trend are extracted. Based on the characteristic parameters, the casting process is divided into stages: initial filling stage, intermediate filling stage, and end compensation stage. Target flow control data containing target flow rate and allowable resistance range are generated for each stage. The system acquires real-time pressure and temperature data within the mold cavity, fuses and calculates the real-time pressure and temperature data to obtain the current actual flow state data, and compares and analyzes the actual flow state data with the target flow control data to generate deviation data reflecting the degree and rate of deviation of the flow capacity. Based on the rate of change information in the deviation data, the growth trend of the flow resistance is determined, and the pouring pressure and pouring speed are feedforward corrected and dynamically adjusted according to the growth trend to generate dynamic pouring control parameters with trend compensation characteristics. The insulation material is poured according to the dynamic pouring control parameters. During the end compensation stage, the pressure compensation amount is increased in advance and the compensation duration is adjusted based on the viscosity growth inflection point predicted by real-time rheological state data. This generates end region filling control results that are synchronized with the curing process, so that the material flow capacity of the end region matches the curing process.

2. The method for dynamic control of insulating component casting based on rheological data as described in claim 1, characterized in that, The process of constructing a real-time rheological state model includes: Viscosity data, shear response data, and curing stage data are synchronized and matched according to the acquisition time to form a unified time series data. The unified time series data is segmented and processed. The viscosity change and shear response change are calculated in adjacent time periods. Flow response parameters characterizing the instantaneous flowability of the material are generated by normalization weighting. The reaction process position of the corresponding time period is determined based on the solidification stage data, and reaction process parameters are generated. The flow response parameters and reaction process parameters are paired according to the time correspondence, and the changes of the flow response parameters with the reaction process parameters in each time period are continuously recorded to establish the correspondence between the flow capacity and the monotonic change of the curing process. Identify the turning point where the rate of change of flow capacity changes abruptly in the correspondence, and use this turning point as the key node for flow capacity decay to generate a flow capacity index that includes the rate of change of flow capacity and the location of the key node. A real-time rheological state model is constructed based on the flowability index, and real-time rheological state data characterizing the current material flowability and solidification process state are output through the real-time rheological state model.

3. The method for dynamic control of insulating component casting based on rheological data as described in claim 1, characterized in that, The process of determining the stage of the pouring process based on characteristic parameters includes: Extract the rate of change of flow capacity indicators from real-time rheological state data over a continuous time period, and perform differential processing on the rate of change to generate trend feature parameters that characterize the degree of acceleration of change. Based on the numerical range and direction of change of the trend characteristic parameters, a stable range of change rate corresponding to the initial filling stage, a continuously decreasing range of change rate corresponding to the intermediate filling stage, and an accelerated decreasing range of change rate corresponding to the end compensation stage are established. Each range is limited by a joint judgment condition of change rate range and change rate difference results. The current rate of change and trend characteristic parameters are matched with each interval item by item. When the conditions of the rate of change range and the degree of change acceleration of the corresponding interval are met at the same time, the current stage of the pouring process is determined. When a phase transition is determined, the corresponding flow capacity index value is recorded as the phase transition boundary, and the target flow control data for the corresponding phase is generated based on the phase transition boundary, so that the control objectives of different phases are consistent with the flow capacity change status.

4. The method for dynamic control of insulating component casting based on rheological data as described in claim 1, characterized in that, The process of generating dynamic casting control parameters includes: The deviation data is continuously sampled in chronological order, the deviation change between adjacent sampling points is calculated, the flow resistance change rate is generated, and the flow resistance change direction is determined based on the consistency of the change rate direction over multiple consecutive time periods, thus forming the flow resistance trend parameter. The correlation between the flow resistance trend parameter and the flow capacity index in the real-time rheological state data is determined. When the flow capacity index decreases and the rate of change of flow resistance continues to increase, it is determined to be a flow capacity decay process. During the process of flow capacity decay, the adjustment range of the pouring pressure is determined according to the magnitude of the rate of change of flow resistance, and the adjustment range of the pouring speed is determined according to the rate of decrease of the flow capacity index, generating a corresponding feedforward adjustment amount so that the adjustment direction is opposite to the direction of flow capacity change. The feedforward adjustment is applied to the current pouring pressure and pouring speed before the deviation data reaches the target flow control data limit range, forming a pre-adjusted dynamic pouring control parameter.

5. The method for dynamic control of insulating component casting based on rheological data as described in claim 2, characterized in that, Establish the corresponding relationship between flowability and the monotonic change of curing process, including: The flow response parameters within each time period are sorted according to the acquisition time, and the sorted flow response parameters are matched with the corresponding reaction process parameters to generate an initial data pair sequence. The direction of change of flow response parameters of adjacent data pairs in the initial data pair sequence is determined, the direction of change determination result is generated, and the effective data pairs with the same direction of change are selected according to the direction of change determination result to generate an effective data sequence. Data pairs with opposite directions of change in the valid data sequence are removed, and the resulting data gaps are connected to generate a continuous data sequence. The continuous data sequence is sorted according to the reaction process parameters, and the sorting results are checked for monotonicity to generate a monotonic data sequence that satisfies that the flow response parameters change in one direction with the reaction process parameters. Establish the correspondence between flowability and curing process based on monotonic data sequences, and output monotonic mapping results to characterize the trend of flowability change.

6. The method for dynamic control of insulating component casting based on rheological data according to claim 2, characterized in that, Generate flow capacity indices that include the rate of change of flow capacity and the locations of key nodes, including: The changes in flow response parameters between adjacent time periods are calculated and processed to generate a sequence of flow capacity change rates arranged in chronological order. The rate of change of flow capacity in adjacent time periods is compared and processed to generate a rate difference sequence. Continuity analysis is then performed on the rate difference sequence to generate a trend sequence. Based on the change trend sequence, determine the consistency of the change direction of the change rate difference within a continuous time period, and generate the cumulative change result; When the change direction reverses in the cumulative change results and the difference in the rate of change before and after the reversal meets the mutation judgment condition set based on the range of change rate difference, the corresponding time period is determined as the rate of change mutation interval, and mutation interval data is generated. Extract the time position when the difference in the rate of change first reaches the mutation judgment condition from the data of the mutation interval, generate the key node position, and correlate the key node position with the flow capacity change rate sequence to generate the flow capacity index.

7. The method for dynamic control of insulating component casting based on rheological data driving according to claim 3, characterized in that, Based on the numerical range and direction of change of the trend characteristic parameters, a stable rate of change interval is established for the initial filling stage, a continuously decreasing rate of change interval for the intermediate filling stage, and an accelerated rate of change interval for the final compensation stage, including: Extract key node locations and corresponding trend feature parameter change data from the real-time rheological state model, perform time series segmentation processing on the trend feature parameter change data, and generate segmented trend data. Statistical analysis and processing are performed on the trend characteristic parameters before the key node positions in the segmented trend data to generate the stability judgment result of the rate of change, and the stable interval of the rate of change is determined based on the judgment result. The trend characteristic parameters of key node locations in the adjacent time period are continuously analyzed and processed to generate a judgment result of continuous decrease in the rate of change, and the interval of continuous decrease in the rate of change is determined based on the judgment result. The trend characteristic parameters after the key node position are analyzed by increasing amplitude to generate the result of accelerated decrease in the rate of change, and the range of accelerated decrease in the rate of change is determined based on the result. Based on the time distribution relationship of the stable rate of change interval, the continuously decreasing rate of change interval, and the accelerating rate of change interval, the stage division result corresponding to the time series is generated, and the interval mapping relationship used for stage determination is output.

8. A dynamic control system for casting insulating components based on rheological data, characterized in that, The system, used in the method of any one of claims 1 to 7, comprises: The rheological state modeling module is used to acquire viscosity data, shear response data, and curing stage data of the insulating material to be poured at the current pouring temperature. It performs coupled analysis and processing on the viscosity data, shear response data, and curing stage data to construct a real-time rheological state model that reflects the correlation between the material's flowability and the curing process, and outputs real-time rheological state data containing flowability indicators and curing process status information. The stage determination module is used to extract characteristic parameters that characterize the material flow attenuation trend based on real-time rheological state data, and to determine the stage of the casting process based on the characteristic parameters, dividing it into the initial filling stage, the intermediate filling stage and the end compensation stage, and generating target flow control data including the target flow rate and allowable resistance range for each stage. The deviation data generation module is used to acquire real-time pressure data and real-time temperature data in the mold cavity, perform fusion calculation on the real-time pressure data and real-time temperature data to obtain the current actual flow state data, and compare and analyze the actual flow state data with the target flow control data to generate deviation data that reflects the degree of deviation and rate of change of flow capacity. The dynamic control module is used to determine the growth trend of flow resistance based on the rate of change information in the deviation data, and to perform feedforward correction and dynamic adjustment of the pouring pressure and pouring speed according to the growth trend, generating dynamic pouring control parameters with trend compensation characteristics. The end-compensation control module is used to execute the pouring of insulating materials according to the dynamic pouring control parameters. During the end-compensation stage, based on the viscosity growth inflection point predicted by real-time rheological state data, the pressure compensation amount is increased in advance and the compensation duration is adjusted to generate end-area filling control results synchronized with the curing process, so that the material flow capacity of the end area is matched with the curing process.

9. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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