Multi-field coupling crankshaft iron mold sand-coated low-carbon casting control method, system and equipment

Abstract

The invention discloses a multi-field coupling crankshaft iron mold sand-coated low-carbon casting control method, system and equipment, and relates to the technical field of casting process control. The multi-field coupling crankshaft iron mold sand-coated low-carbon casting control method, system and equipment comprise the following steps that S1, heat, stress and flow related state information is collected, and a key process state parameter set is constructed and preprocessed; s2, identifying a casting stage and an abnormal state based on the key process state parameter set; s3, after entering a regulation process, evaluating regulation and control intensity according to state feedback; and S4, tracking the regulated state response, and generating a response level based on the corresponding relationship between the regulated state and the target state. The problems that in existing crankshaft iron mold sand-coated casting, the heating temperature, the cooling rate and the sand-coated rhythm are set depending on experience and are difficult to adjust in real time according to the metal liquid flowing state, the mold heating change and the stress concentration trend, and adjustment lags are caused are solved.

Description

Technical Field

[0001] This invention relates to the field of casting process control technology, specifically to a method, system, and equipment for controlling low-carbon casting of multi-field coupled crankshaft iron molds with sand coating. Background Technology

[0002] With the continuous growth in demand for high-quality castings, crankshaft iron mold sand casting is widely used in the automotive, shipbuilding, and construction machinery industries. This process rapidly forms the parts using iron molds and then coats the surface with sand to improve thermal insulation and surface quality, offering advantages such as high production efficiency and stable casting performance. In recent years, the development direction of high-quality castings has gradually shifted from single performance improvement to a synergistic approach of green, low-carbon, and refined processes, prompting higher requirements for casting processes in terms of multi-field coupled control and data-driven management.

[0003] For example, invention patent CN108788033B discloses a magnesium alloy casting cooling system, comprising: an upper cooling chamber located at the top of a crystallizer, connected to an upper cooling medium pipeline, the upper cooling medium pipeline having an upper control valve; a lower cooling chamber located at the bottom of the crystallizer, connected to a lower cooling medium pipeline, the lower cooling medium pipeline having a lower control valve; a first thermocouple located on the crystallizer wall corresponding to the solidification start point of the magnesium alloy; a second thermocouple located on the crystallizer wall corresponding to the liquid core endpoint of the magnesium alloy; and a control device connected to the first thermocouple, the second thermocouple, the upper control valve, and the lower control valve, respectively. Furthermore, a magnesium alloy casting cooling method is also disclosed. The magnesium alloy casting cooling system of this invention has a simple process, produces high-quality magnesium alloy products, and has wide adaptability.

[0004] For example, invention patent CN110681852B discloses a casting manufacturing system suitable for continuously and mass-producing small cast steel castings using relatively simple equipment. The casting manufacturing system comprises: multiple furnaces storing molten metal for casting steel and arranged in a row; a pouring machine having ladles that receive molten metal from the furnaces, the pouring machine moving in a direction parallel to the row of furnaces, tilting the ladle to pour the molten metal into molds; and a mold conveyor line intermittently conveying multiple molds arranged parallel to the direction of the pouring machine's movement, positioned on the opposite side of the furnaces. The casting manufacturing system further includes a temperature sensor that measures the temperature of the molten metal in the ladle and generates an alarm when the measured temperature is lower than a specified temperature.

[0005] In existing crankshaft iron mold sand casting, heating temperature, cooling flow, and sand coating rhythm largely rely on experience-based settings. Temperature control is mainly based on preset power, cooling flow is fixedly distributed by region, and the sand coating process is advanced according to node times, lacking the ability to perceive real-time operating conditions. Faced with changes in the state of the molten metal, fluctuations in the thermal response of the mold, and the risk of stress concentration, adjustment methods are generally lagging and uncoordinated, easily leading to defects such as shrinkage porosity, cracks, and uneven microstructure, while also causing production instability and energy consumption fluctuations.

[0006] To address the above issues, there is an urgent need for a multi-field coupled crankshaft iron mold sand-coated low-carbon casting control method, system, and equipment. Summary of the Invention

[0007] Technical problems to be solved

[0008] To address the shortcomings of existing technologies, this invention provides a multi-field coupled crankshaft iron mold sand coating low-carbon casting control method, system, and equipment. It solves the problem that in existing crankshaft iron mold sand coating casting, the heating temperature, cooling rate, and sand coating rhythm rely on experience settings and are difficult to adjust in real time according to the flow state of the molten metal, the heating changes of the mold, and the stress concentration trend, resulting in adjustment lag.

[0009] Technical solution

[0010] To achieve the above objectives, the present invention provides the following technical solution: a multi-field coupled crankshaft iron mold sand-coated low-carbon casting control method, comprising the following steps: S1: collecting thermal, stress, and flow-related state information, constructing a key process state parameter set and performing preprocessing; S2: identifying casting stages and abnormal states based on the key process state parameter set, adjusting the monitoring frequency and control parameter update rhythm based on the degree of deviation, and deciding whether to enter the adjustment process; S3: after entering the adjustment process, evaluating the control intensity based on state feedback, and controlling the heating power, cooling range, and sand coating rhythm based on the control intensity; S4: tracking the state response after control, generating a response level based on the correspondence between the state after control and the target state, and performing parameter locking, control frequency adjustment, and data benchmark update in layers according to the response level.

[0011] Furthermore, the specific steps for collecting thermal, stress, and flow-related state information, constructing a key process state parameter set, and performing preprocessing are as follows: The process of collecting thermal, stress, and flow-related state information and constructing a key process state parameter set includes: collecting temperature sensor data from the mold surface and center to obtain the current mold temperature value; calling the temperature reference curve extracted from historical stable operating conditions to determine the target reference temperature value; measuring real-time values ​​with stress gauges deployed at key parts of the mold to form the current mold stress value, and combining the output of stress sensors deployed at local measuring points to obtain the measuring point stress value; collecting flow data in real time from flow sensors on the cooling supply pipeline to form the current cooling supply flow rate value; and directly acquiring the current molten metal flow rate value through an immersion flow velocity sensor, while calling the set... The flow reference curve established during the design phase yields the standard molten metal flow rate value; the instantaneous thermocouple sampling signals deployed in the casting area generate the current instantaneous temperature value; after performing heating, cooling, and sand coating adjustment actions, the data collected by the secondary sensors are called to update the adjusted mold temperature and stress values, forming a complete set of key process state parameters; the set of key process state parameters is preprocessed: the data units and formats of the temperature, stress, flow rate, and velocity fields are standardized; values ​​exceeding physical limits and those with abnormal acquisition are removed; short-term missing data is interpolated and completed, and continuously missing data is marked as unusable; each field is resampled and aligned according to a unified timestamp; physical constraint verification between fields is performed, and logically conflicting data is identified and eliminated; the set of key process state parameters is standardized and normalized.

[0012] Furthermore, the specific steps for identifying casting stages and abnormal states based on key process state parameter sets are as follows: For a complete acquisition cycle based on a single casting task, calculate the standard deviation of stress values ​​at measurement points in each cycle under historical qualified casting conditions; statistically analyze the distribution of standard deviations for all cycles and set the first quartile as the stress fluctuation threshold; filter stable cycles with standard deviations less than the stress fluctuation threshold; perform a weighted average calculation on the stress values ​​at measurement points within the cycle to obtain the target reference stress value; acquire the current mold temperature value, the target reference temperature value, and the current mold stress value; and retrieve the mold temperature value acquisition data recorded in the previous cycle to obtain the mold stress value from the previous cycle. Temperature value; calculate the square of the difference between the current mold temperature value and the target reference temperature value, and divide it by the square of the target reference temperature value to obtain the temperature offset term; then calculate the square of the difference between the current mold stress value and the target reference stress value, and divide it by the square of the target reference stress value to obtain the stress offset term; add the temperature offset term and the stress offset term to form the basic offset part; calculate the difference between the current mold temperature value and the mold temperature value of the previous cycle, divide it by the target reference temperature value, and then multiply it by the temperature change trend weighting coefficient to obtain the trend adjustment term; add the basic offset part and the trend adjustment term to obtain the state offset intensity value.

[0013] Furthermore, the specific steps for adjusting the monitoring frequency and control parameter update rhythm based on the degree of offset and determining whether to enter the adjustment process are as follows: The adjustment calculation and acquisition control strategy is executed in stages according to the state offset intensity value: the state offset intensity value is compared with the offset threshold in real time, the offset threshold including a first-level offset threshold and a second-level offset threshold; when the state offset intensity value is greater than or equal to the first-level offset threshold, the acquisition frequency of temperature and stress is increased, the parameter adaptive update operation is paused, and the adjustment intensity calculation process is entered; when the state offset intensity value is greater than the second-level offset threshold but less than the first-level offset threshold, the current acquisition point is marked as a key monitoring area, a backup parameter scheme is loaded, and the adjustment operation judgment is postponed; when the state offset intensity value is less than or equal to the second-level offset threshold, the current acquisition frequency and parameter configuration are maintained, and the adjustment calculation channel is closed.

[0014] Furthermore, after entering the adjustment process, the specific steps for evaluating the control intensity based on state feedback are as follows: Divide the historical cooling process into cycles based on a complete cooling phase; calculate the standard deviation of the cooling supply flow rate value within each cycle; statistically analyze the distribution of the standard deviations of all cycles and set the first quartile as the flow fluctuation threshold; filter stable cycles with a standard deviation less than the flow fluctuation threshold; perform an average calculation on the cooling supply flow rate value within the cycle to obtain the reference cooling flow rate value; obtain the current cooling supply flow rate value, the current molten metal flow rate value, the standard molten metal flow rate value, the target reference temperature value, and the current instantaneous temperature. Temperature value; Divide the current cooling supply flow rate value by the reference cooling flow rate value to obtain the heat flow ratio term; Divide the current molten metal flow rate value by the standard molten metal flow rate value, and use the ratio as the base to perform exponentiation with the flow rate adjustment index as the power to obtain the flow rate response term; Add the heat flow ratio term and the flow rate response term to form the physical input term; Calculate the difference between the current instantaneous temperature value and the target reference temperature value, and then divide it by the target reference temperature value, using it as the input of the hyperbolic tangent function to obtain the temperature offset adjustment term; Multiply the physical input term and the temperature offset adjustment term to obtain the control adjustment amplitude value.

[0015] Furthermore, the specific steps for controlling heating power, cooling range, and sand coating rhythm based on the control intensity are as follows: The thermal control adjustment and sand coating control strategies are executed in stages according to the control adjustment amplitude value: The control adjustment amplitude value and the control threshold are compared in real time, the control threshold including a primary control threshold and a secondary control threshold; when the control adjustment amplitude value is greater than or equal to the primary control threshold, the heating power output is increased and switched to continuous heating, the cooling spray area is expanded, and the sand coating trigger interval is shortened; when the control adjustment amplitude value is greater than the secondary control threshold but less than the primary control threshold, the set temperature difference range of the heating target is expanded, the spray frequency is increased, and the spray timing is adjusted, compressing the waiting time between steps in the sand coating progress rhythm; when the control adjustment amplitude value is less than or equal to the secondary control threshold, the current heating power, cooling flow rate, and sand coating control logic remain unchanged, without introducing additional intervention.

[0016] Further, the specific steps for generating a response level based on the correspondence between the regulated state and the target state in the tracking and regulation of the state response are as follows: Tracking the regulated state response, calculating the regulation response effect value based on the correspondence between the regulated mold temperature value and the regulated mold stress value relative to the target reference temperature value and the target reference stress value; obtaining the regulated mold temperature value, the target reference temperature value, the regulated mold stress value, and the target reference stress value; calculating the difference between the regulated mold temperature value and the target reference temperature value, dividing by the target reference temperature value, and squaring the ratio to obtain the temperature deviation term; calculating the difference between the regulated mold stress value and the target reference stress value, dividing by the target reference stress value, squaring the ratio, and multiplying by the stress deviation weighting coefficient to obtain the stress deviation term; adding the temperature deviation term and the stress deviation term, then adding one, as the denominator; using a constant one as the numerator, dividing the numerator by the denominator to obtain the regulation response effect value.

[0017] Furthermore, the specific steps for implementing parameter locking, control frequency adjustment, and data benchmark update based on response level are as follows: Based on the control response effect value, a target correction and control tolerance control strategy is implemented in stages: The control response effect value is compared with an effective threshold in real time, where the effective threshold includes a primary effective threshold and a secondary effective threshold; when the control response effect value is greater than or equal to the primary effective threshold, the update of the target reference temperature value and the target reference stress value is paused, the acquisition cycle and heating control parameters are frozen, and feedback amplification adjustment is stopped; when the control response effect value is greater than the secondary effective threshold but less than the primary effective threshold, the nozzle opening frequency is reduced, the stability of the adjustment is judged based on the rate continuity during the water pressure adjustment process, the rate of change of cooling water pressure is limited, the sampling frequency is increased, and the comparison benchmark range is adjusted; when the control response effect value is less than or equal to the secondary effective threshold, the target temperature is lowered, the thermocouple placement is expanded, the abnormal stress value is reconstructed, an alarm flag is written, and conservative control is initiated.

[0018] The second aspect of this invention provides a multi-field coupled crankshaft iron mold sand-coated low-carbon casting control system, comprising: a multi-source physical acquisition module, a process state identification module, a parameter adaptive control module, and a control effect evaluation module. The multi-source physical acquisition module is used to acquire thermal, stress, and flow-related state information, construct a set of key process state parameters, and perform preprocessing. The process state identification module is used to identify casting stages and abnormal states based on the key process state parameter set, adjust the monitoring frequency and control parameter update rhythm based on the degree of deviation, and determine whether to enter the adjustment process. The parameter adaptive control module is used to evaluate the control intensity based on state feedback after entering the adjustment process, and control the heating power, cooling range, and sand-coating rhythm based on the control intensity. The control effect evaluation module is used to track the state response after control, generate a response level based on the correspondence between the state after control and the target state, and perform parameter locking, control frequency adjustment, and data benchmark update in layers according to the response level.

[0019] The third aspect of this invention provides a multi-field coupled crankshaft iron mold sand-coated low-carbon casting control device, comprising: a state data construction unit, a stage identification and scheduling unit, an adjustment command generation unit, and a feedback response analysis unit; the state data construction unit is used to collect thermal state information, stress state information, and flow state information, construct a set of key process state parameters, and perform field standardization, time alignment, and anomaly removal; the stage identification and scheduling unit is used to identify casting stages and abnormal states, and adjust the acquisition frequency, control parameter rhythm, and adjustment process judgment according to the state deviation intensity value; the adjustment command generation unit is used to calculate the adjustment amplitude value and control the output mode of heating power, cooling spray range, and sand coating rhythm in a graded manner; the feedback response analysis unit is used to calculate the control response effect value and perform parameter freezing, sampling frequency adjustment, and abnormal state control in a graded manner.

[0020] Beneficial effects

[0021] The present invention has the following beneficial effects:

[0022] (1) The present invention constructs a set of key process state parameters based on multi-source state data and performs field unification and anomaly removal, which helps to ensure the data stability and expression consistency of subsequent identification and adjustment calculations, and realizes the structured processing and standardized input of casting process state monitoring data.

[0023] (2) The present invention uses temperature offset, stress offset and trend adjustment to form the state offset intensity value, and uses this value as the basis to perform dynamic scheduling of acquisition frequency and parameter update, thereby realizing quantitative determination of the control entry of the casting process and hierarchical control of acquisition behavior.

[0024] (3) This invention introduces heat flow ratio, flow rate response and temperature offset adjustment to construct control adjustment range value, thereby driving the graded execution of heating power, cooling range and sand covering rhythm, so that the control mode of each physical behavior in the casting process matches the real-time state, and realizes the linkage between control action and parameter state.

[0025] (4) The present invention generates the control response effect value based on the correspondence between the temperature and stress state after control and the target state, and uses its value range as the basis for the classification of control frequency, parameter locking and data update, thereby realizing the feedback closed loop of the response after casting control and the dynamic correction of the control strategy.

[0026] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0027] Figure 1 This is a flowchart of the multi-field coupled crankshaft iron mold sand-coated low-carbon casting control method of the present invention;

[0028] Figure 2 This is a structural diagram of the multi-field coupled crankshaft iron mold sand-coated low-carbon casting control system of the present invention;

[0029] Figure 3 This is a distribution diagram of the offset intensity values ​​under various working conditions of the present invention;

[0030] Figure 4 This is a comparison diagram of temperature and stress before and after the adjustment of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Please see Figures 1-4This invention provides a technical solution: a multi-field coupled crankshaft iron mold sand coating low-carbon casting control method, comprising the following steps: S1: collecting thermal, stress, and flow-related state information, constructing a key process state parameter set and performing preprocessing; S2: identifying casting stages and abnormal states based on the key process state parameter set, adjusting the monitoring frequency and control parameter update rhythm based on the degree of deviation, and deciding whether to enter the adjustment process; S3: after entering the adjustment process, evaluating the control intensity based on state feedback, and controlling the heating power, cooling range, and sand coating rhythm based on the control intensity; S4: tracking the state response after control, generating a response level based on the correspondence between the state after control and the target state, and performing parameter locking, control frequency adjustment, and data benchmark update in layers according to the response level.

[0033] Specifically, the process involves collecting thermal, stress, and flow-related state information, constructing a key process state parameter set, and preprocessing it. The specific steps are as follows: Collecting thermal, stress, and flow-related state information; constructing the key process state parameter set includes: collecting temperature sensor data from the mold surface and center to obtain the current mold temperature; calling the temperature reference curve extracted from historical stable conditions to determine the target reference temperature value. The temperature reference curve is established using process data from no fewer than 50 sets of castings and verified through joint analysis based on CFD simulation and thermal response measurement, used to describe the temperature evolution trend at different casting stages; and obtaining real-time values ​​from stress gauges deployed at key parts of the mold to form the current mold stress value, combined with the output of stress sensors deployed at local measuring points to obtain the measuring point values. Stress value; flow sensors on the cooling supply pipeline collect real-time supply data to form the current cooling supply flow rate value; the molten metal flow rate is directly collected by an immersion flow velocity sensor to obtain the current molten metal flow velocity value, and at the same time, the standard molten metal flow velocity value is obtained by calling the flow reference curve established in the design stage. This reference curve is composed of flow velocity distribution data at a typical filling section, and is generated based on experimental measurements and CFD simulation results of the filling process. It is suitable for structural comparison and response evaluation under similar process conditions; the instantaneous temperature value is generated by the sampling signal of the instantaneous thermocouples deployed in the casting area; after performing heating, cooling and sand covering adjustment actions, the data collected by the sensors for secondary adjustment is called to update the mold temperature value and mold stress value after adjustment, forming a complete set of key process state parameters. Preprocessing of the key process state parameter set: unifying the data units and formats of temperature, stress, flow rate, and velocity fields; removing values ​​that exceed physical limits and those with abnormal acquisition; performing interpolation to complete short-term missing data and marking continuously missing data as unusable; resampling and aligning each field according to a unified timestamp; performing physical constraint verification between fields, identifying and eliminating logically conflicting data; and performing standardization and normalization processing on the key process state parameter set.

[0034] In this implementation plan, by collecting thermal, stress, and flow-related state information during the casting process, a set of process state parameters containing key variables is constructed, and field standardization, anomaly removal, missing data repair, and time alignment are performed. Through standardization and normalization transformation, the stability and computability of the data are improved, providing an accurate, complete, and consistent input foundation for the identification and control command generation in the casting stage.

[0035] Specifically, the casting stage and abnormal state are identified based on a set of key process state parameters. The specific steps are as follows: For a complete acquisition cycle based on a single casting task, calculate the standard deviation of the stress values ​​at measurement points in each cycle of historical qualified casting conditions. Statistically analyze the distribution of the standard deviations for all cycles. Using at least 40 sets of stable operating condition data as a sample base, set the first quartile as the stress fluctuation threshold. Select cycles with a standard deviation below this threshold as stable segments. Perform a weighted average calculation on the stress values ​​at measurement points within the cycle to obtain the target reference stress value. Obtain the current mold temperature value, the target reference temperature value, and the current mold stress value. Retrieve the mold temperature data recorded in the previous cycle. Calculate the square of the difference between the current mold temperature value and the target reference temperature value, and divide by the square of the target reference temperature value to obtain the temperature offset term. Similarly, calculate the square of the difference between the current mold stress value and the target reference stress value, and divide by the square of the target reference stress value to obtain the stress offset term. Add the above two items to form the basic offset part. The difference between the current mold temperature and the mold temperature in the previous cycle is calculated, divided by the target reference temperature, and then multiplied by a temperature change trend weighting coefficient to obtain the trend adjustment term. This trend adjustment term is obtained by fitting the temperature change rate over two consecutive sampling cycles to a historical thermal response sensitivity curve, and its value ranges from 0 to 1. It is used to adjust the intensity of the temperature trend's influence on the overall state offset. Finally, the basic offset is added to the trend adjustment term to obtain the state offset intensity value.

[0036] The specific calculation method for the state offset intensity value is as follows:

[0037]

[0038] In the formula, Indicates the state offset intensity value. This indicates the current mold temperature value. Indicates the target reference temperature value. This indicates the current mold stress value. Indicates the target reference stress value. This indicates the mold temperature value from the previous cycle. This represents the weighting coefficient for temperature change trends. The state offset intensity value is constructed based on the normalized Euclidean distance and the first-order temperature difference, integrating the steady-state offset and dynamic trends of temperature and stress, and is used to quantify the degree of deviation between the current operating condition and the reference state.

[0039] Table 1 shows the state offset strength value data table provided in the embodiments of this application. The current mold temperature value for condition 1 is set to 540.0, the target reference temperature value is set to 600.0, the current mold stress value is set to 100.0, the target reference stress value is set to 120.0, and the mold temperature value of the previous cycle is set to 510.0; the current mold temperature value for condition 2 is set to 570.0, the target reference temperature value is set to 600.0, the current mold stress value is set to 110.0, the target reference stress value is set to 120.0, and the mold temperature value of the previous cycle is set to 550.0; the current mold temperature value for condition 3 is set to 600.0, the target reference temperature value is set to 600.0, and the current mold stress value is set to 510.0. The current mold temperature value is set to 120.0, the target reference stress value is set to 120.0, and the mold temperature value of the previous cycle is set to 590.0. For condition 4, the current mold temperature value is set to 630.0, the target reference temperature value is set to 600.0, the current mold stress value is set to 135.0, the target reference stress value is set to 120.0, and the mold temperature value of the previous cycle is set to 610.0. For condition 5, the current mold temperature value is set to 660.0, the target reference temperature value is set to 600.0, the current mold stress value is set to 145.0, the target reference stress value is set to 120.0, and the mold temperature value of the previous cycle is set to 620.0.

[0040] Table 1. Data on State Offset Intensity Values

[0041]

[0042] like Figure 3 The figure shows the distribution of state deviation intensity values ​​for each operating condition provided in this application embodiment. According to the data in the image and table, the secondary deviation threshold is 0.065, the primary deviation threshold is 0.120, and the state deviation intensity values ​​for the five operating conditions fluctuate between 0.02 and 0.15. The state deviation intensity value for operating condition 5 is 0.15, exceeding the primary deviation threshold, indicating a significant deviation and requiring immediate adjustment. The deviation intensity value for operating condition 1 is 0.11, between the two thresholds, representing a moderate deviation; it should be closely monitored, and backup parameters should be prepared. Operating conditions 2 and 4 are 0.06 and 0.07 respectively, both close to the secondary threshold, indicating a preliminary deviation trend. The deviation intensity value for operating condition 3 is 0.02, far below the two thresholds, indicating a stable state and requiring no adjustment. This figure can be used to visually determine the degree of state deviation for each operating condition, providing a tiered control basis for cooling adjustment, heating correction, and parameter updates.

[0043] like Figure 4The figure shows a comparison of temperature and stress before and after adjustment according to an embodiment of this application. The figure illustrates the trends of mold temperature and stress changes before and after adjustment for conditions 1 to 5. Before adjustment, the temperature was generally between 610℃ and 620℃, and after adjustment, all temperatures decreased to varying degrees, with the lowest dropping to approximately 585℃, indicating that heat input was effectively suppressed. The stress value also gradually decreased from 140 MPa before adjustment to approximately 115 MPa after adjustment, showing a continuous downward trend, indicating that the adjustment measures effectively alleviated thermal stress concentration. After adjustment, both temperature and stress showed a significant downward trend in each condition, reflecting that the process state after adjustment is closer to the target setting range, which helps reduce defect risks and improve molding stability. This figure can intuitively reflect the adjustment response effect, providing a basis for subsequent adjustment strategy optimization and response level evaluation.

[0044] In this implementation plan, by calculating the degree of deviation between the current temperature and stress relative to the reference value and incorporating the temperature change trend for adjustment, a quantitative expression of the casting state deviation intensity is achieved, providing a unified indicator basis for identifying stage transitions, monitoring working condition stability, and judging abnormal evolution trends.

[0045] Specifically, the monitoring frequency and control parameter update rhythm are adjusted based on the degree of offset to determine whether to enter the adjustment process. The specific steps are as follows: Adjustment calculation and acquisition control strategies are executed in stages according to the state offset intensity value. The state offset intensity value is compared with the offset threshold in real time, including a primary offset threshold and a secondary offset threshold. When the state offset intensity value is greater than or equal to the primary offset threshold, the acquisition frequency of temperature and stress is increased to accelerate the state response tracking rhythm. At the same time, the parameter adaptive update operation under the current task is paused to avoid interference judgment, and the adjustment intensity calculation process is directly entered. When the state offset intensity value is greater than the secondary offset threshold but less than the primary offset threshold, the current acquisition point is marked as a key monitoring area, and a backup parameter scheme containing fields such as thermal control boundary, cooling delay, and spray rhythm is loaded. The adjustment operation judgment is delayed, and the buffer observation state is entered. When the state offset intensity value is less than or equal to the secondary offset threshold, the current acquisition frequency and parameter configuration remain unchanged, and the adjustment calculation channel is closed to avoid repeated triggering of invalid intervention.

[0046] In this implementation scheme, a dynamic hierarchical control mechanism based on the state offset intensity value is realized. The sampling frequency and control parameter update rhythm can be adjusted according to the degree of offset, and the adjustment process can be reasonably determined to improve the matching and response efficiency of monitoring and adjustment behavior.

[0047] Specifically, after entering the adjustment process, the intensity of the adjustment is evaluated based on the status feedback. The specific steps are as follows: Divide the historical cooling process into cycles based on a complete cooling phase, calculate the standard deviation of the cooling supply flow rate value in each cycle, statistically analyze the distribution of the standard deviation of all cycles, and take no less than 40 sets of stable cooling conditions as samples, and set the first quartile as the flow rate fluctuation threshold; screen the cycles with a standard deviation lower than the threshold, and perform an average calculation on the cooling supply flow rate value in the cycle to obtain the reference cooling flow rate value. The process involves obtaining the current cooling supply flow rate, current molten metal flow rate, standard molten metal flow rate, target reference temperature, and current instantaneous temperature. The current cooling supply flow rate is divided by the reference cooling flow rate to obtain the heat flow ratio term. The current molten metal flow rate is divided by the standard molten metal flow rate, and the ratio is used as the base. This ratio is then exponentially raised to the power of the flow rate regulation index to obtain the flow rate response term. A response relationship model between the cooling channel and molten metal flow is constructed in the process simulation environment. The flow rate regulation index is calculated using the nonlinear fitting result of the flow rate deviation term in the regulation amplitude function. The specific value is typically between 0.5 and 2.0, used to characterize the nonlinear amplification effect of velocity changes on process regulation. The heat flow ratio term and the flow rate response term are added to form the physical input term. The difference between the current instantaneous temperature and the target reference temperature is calculated and divided by the target reference temperature. This difference is used as the input to the hyperbolic tangent function to obtain the temperature offset regulation term. Finally, the physical input term and the temperature offset regulation term are multiplied to obtain the regulation adjustment amplitude value.

[0048] The specific calculation method for the adjustment range value is as follows:

[0049]

[0050] In the formula, This indicates the magnitude of the regulatory adjustment. This indicates the current cooling supply flow rate. This represents the reference cooling flow rate value. This indicates the current flow rate of the molten metal. This represents the standard molten metal flow rate value. Indicates the flow rate regulation index. This represents the current instantaneous temperature value. This represents the target reference temperature value. The adjustment range is obtained by fitting historical operating conditions' flow rate, velocity, and temperature difference data using a nonlinear least squares method. The fitting process incorporates physical response relationships to construct a functional mapping between the adjustment range and multivariate inputs.

[0051] This implementation plan achieves a quantitative assessment of the control intensity by integrating multi-source state data such as cooling flow rate, molten metal flow rate, and temperature deviation into a unified control index. This index can accurately reflect the current operating conditions' response to control and provide a basis for the intensity of subsequent control actions.

[0052] Specifically, the heating power, cooling range, and sand coating rhythm are controlled based on the intensity of the regulation. The specific steps are as follows: Thermal control and sand coating control strategies are implemented in stages according to the adjustment amplitude value. The adjustment amplitude value and the control threshold are compared in real time. The control threshold includes a primary control threshold and a secondary control threshold. When the adjustment amplitude value is greater than or equal to the primary control threshold, the heating power output is increased, and the system switches to continuous heating mode. The upper limit of the heating power is limited by the equipment's safety rating. Simultaneously, the cooling spray area is expanded, with the expanded area not exceeding 80% of the total controllable area of ​​the cooling channel. The sand coating trigger interval is shortened to within 50% of the current rhythm. If the adjustment amplitude value is between the primary and secondary thresholds, the set temperature difference range of the heating target is expanded, with the adjustment amplitude not exceeding 20% ​​of the original set value. The spray frequency is increased to within 1.5 times the baseline value, and the spray start and stop timing is optimized to match the actual heat load changes. At the same time, the waiting time between steps in the sand coating progress rhythm is reduced, with the reduction ratio controlled within 30%. If the adjustment range is less than or equal to the secondary control threshold, the current heating power, cooling flow rate and sand covering control logic will remain unchanged, and no additional intervention measures will be introduced.

[0053] In this implementation plan, the heating power, cooling range and sand covering rhythm are controlled in stages based on the adjustment range value. By setting different control thresholds, corresponding actions such as power increase, spray range expansion and rhythm compression are performed to achieve intensity adaptation and rhythm optimization of key physical processes.

[0054] Specifically, the process involves tracking the state response after regulation and generating a response level based on the correspondence between the regulated state and the target state. The specific steps are as follows: Track the state response after regulation and calculate the regulation response effect value based on the correspondence between the regulated mold temperature value and the regulated mold stress value relative to the target reference temperature value and the target reference stress value. Obtain the regulated mold temperature value, the target reference temperature value, the regulated mold stress value, and the target reference stress value. Calculate the difference between the regulated mold temperature value and the target reference temperature value, divide it by the target reference temperature value, and square the ratio to obtain the temperature deviation term. Then calculate the difference between the regulated mold stress value and the target reference stress value, divide it by the target reference stress value, square the ratio, and multiply it by the stress deviation weighting coefficient to obtain the stress deviation term. The stress deviation weighting coefficient is obtained by establishing a functional relationship between the degree of stress deviation and the defect risk, analyzing the changing trend of the probability of defect occurrence under different deviation levels, and using the sensitivity of this trend as the calculation basis. Its value ranges from 0.2 to 0.8 and is used to adjust the influence ratio of the stress term in the final result. Add the temperature deviation term and the stress deviation term together, then add one to get the denominator; use the constant one as the numerator, and divide the numerator by the denominator to obtain the control response effect value.

[0055] The specific calculation method for the regulation response effect value is as follows:

[0056]

[0057] In the formula, Indicates the value of the control response effect. This indicates the mold temperature value after adjustment. Indicates the target reference temperature value. This indicates the mold stress value after adjustment. Indicates the target reference stress value. This represents the stress deviation weighting coefficient. The control response effect value uses normalized temperature and stress deviation to construct a suppression term, which, combined with the stress weighting coefficient, forms a denominator gain control structure. The overall structure follows a suppression-type scoring function algorithm to evaluate the consistency between the control result and the target state.

[0058] In this implementation scheme, the deviation of the temperature and stress state after regulation from the target reference value is quantitatively calculated, and a response effect value is generated to evaluate the regulation result. This can uniformly measure the degree of recovery of the thermal stress state by the regulation behavior and provide a basis for subsequent control strategy adjustments.

[0059] Specifically, parameter locking, control frequency adjustment, and data benchmark updates are performed in tiers based on response levels. The specific steps are as follows: Target correction and control tolerance control strategies are implemented in tiers based on the control response effect value. The control response effect value is compared with the effective threshold in real time. The effective threshold includes a primary effective threshold and a secondary effective threshold. When the control response effect value is greater than or equal to the primary effective threshold, the update of the target reference temperature value and the target reference stress value is paused, the acquisition cycle and heating control parameters are frozen, feedback amplification adjustment is stopped, and control stability is maintained. When the control response effect value is between the secondary and primary effective thresholds, the nozzle opening frequency is reduced, and the stability of the adjustment process is judged based on the rate change during the cooling water pressure adjustment process. If necessary, the rate of water pressure change is limited to not exceeding the set threshold. At the same time, the sampling frequency is increased, and the comparison benchmark range is adjusted to a 10% tolerance deviation range centered on the current state and extended to both sides. When the control response effect value is less than or equal to the secondary effective threshold, the target temperature setpoint is lowered, the thermocouple coverage is expanded to fill the monitoring blind spots in key areas, and a reconstruction calculation is performed on the abnormal stress value, an alarm flag is written, and the system switches to conservative control mode.

[0060] This implementation plan achieves parameter locking, sampling frequency adjustment, and data benchmark updating based on the control response effect value. Through hierarchical response execution target freezing, control rhythm optimization, and abnormal state management, it ensures that the control strategy has stability and adaptability at different response levels.

[0061] like Figure 2The diagram shows the structure of the multi-field coupled crankshaft mold sand-coated low-carbon casting control system provided in this embodiment of the application. This system applies a multi-field coupled crankshaft mold sand-coated low-carbon casting control method, including: a multi-source physical acquisition module for acquiring thermal, stress, and flow-related state information, constructing a set of key process state parameters, and performing preprocessing operations such as field standardization, time alignment, and anomaly rejection; a process state identification module for identifying casting stages and abnormal states based on the key process state parameter set, dynamically adjusting the monitoring frequency and parameter update rhythm based on the degree of deviation, and determining whether to enter the adjustment process; a parameter adaptive control module for evaluating the control intensity based on state feedback after entering the adjustment process, and using this intensity value as the basis for execution, classifying and controlling the heating power output, cooling spray range, and sand coating advancement rhythm; and a control effect evaluation module for tracking the state response after control, generating a response level based on the deviation relationship between the controlled state and the target state, and performing parameter locking, sampling frequency adjustment, and data benchmark update operations accordingly.

[0062] This implementation plan realizes a multi-module linkage control mechanism for the casting process. Through closed-loop collaboration of data acquisition, status identification, control execution and result evaluation, it completes the whole process control from status perception to parameter adjustment and then to feedback correction, improving the matching of responses and the continuity of control in each link.

[0063] The multi-field coupled crankshaft iron mold sand-coated low-carbon casting control equipment provided in this application embodiment applies a multi-field coupled crankshaft iron mold sand-coated low-carbon casting control method, including: a state data construction unit, used to collect thermal state information, stress state information, and flow state information, construct a set of key process state parameters, and complete field standardization, time alignment, and anomaly rejection processing operations; a stage identification and scheduling unit, used to identify casting stages and abnormal states, adjust the acquisition frequency and control parameter update rhythm in stages based on the state offset intensity value, and determine whether to enter the adjustment process; an adjustment command generation unit, used to calculate the adjustment amplitude value, and control the output strategy of heating power, cooling spray range, and sand coating rhythm in stages according to threshold levels to achieve dynamic adjustment of process parameters; and a feedback response analysis unit, used to calculate the control response effect value, and execute parameter locking, sampling frequency adjustment, and abnormal state reconstruction and intervention in layers according to the results.

[0064] This implementation plan realizes a control task division mechanism with status acquisition, stage identification, adjustment command generation and feedback analysis as the core. Through data transmission and calculation connection between functional units, a closed-loop execution chain is constructed from status perception to control execution and then to effect evaluation.

[0065] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0066] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A multi-field coupled crank iron mold sand coated low carbon casting control method, characterized in that, The method comprises the following steps: S1: Collecting heat, stress, and flow-related state information, constructing a set of key process state parameters, and preprocessing; S2: Identifying the casting stage and abnormal state based on the set of key process state parameters, adjusting the monitoring frequency and control parameter update rhythm in combination with the degree of deviation, and determining whether to enter the adjustment process; S3: After entering the adjustment process, evaluating the control intensity according to the state feedback, and controlling the heating power, cooling range, and sand covering rhythm according to the control intensity; S4: Tracking the state response after adjustment, generating a response level based on the correspondence between the state after adjustment and the target state, and executing parameter locking, control frequency adjustment, and data benchmark updating according to the response level.

2. The multi-field coupled crank iron mold sand coated low carbon casting control method according to claim 1, characterized by: The specific steps of collecting heat, stress, and flow-related state information, and constructing a set of key process state parameters and preprocessing are as follows: Collecting heat, stress, and flow-related state information, and constructing a set of key process state parameters includes: collecting temperature sensor data on the surface and center of the mold to obtain the current mold temperature value; calling the temperature reference curve extracted in the historical stable working condition to determine the target reference temperature value; the stress gauge arranged at the key parts of the mold measures the real-time value to form the current mold stress value, and the stress sensor output at the local measuring point is obtained to obtain the measuring point stress value; the flow sensor on the cooling supply pipeline real-time collects the supply flow data to form the current cooling supply flow value; the metal liquid flow rate is directly collected by the immersion type flow rate sensor to obtain the current metal liquid flow rate value, and the standard metal liquid flow rate value is obtained by calling the flow benchmark curve established in the design stage; the instantaneous thermocouple arranged in the casting area samples the signal to generate the current instantaneous temperature value; after the heating, cooling, and sand covering adjustment actions are performed, the data collected by the sensor is called again to update the adjusted mold temperature value and the adjusted mold stress value, and a complete set of key process state parameters is formed; The preprocessing of the set of key process state parameters includes: unifying the data units and formats of the temperature, stress, flow, and flow rate fields; removing values exceeding the physical limit and abnormal values; performing interpolation completion on short-time missing data, and marking continuous missing data as unavailable; resampling and aligning each field according to the unified timestamp; performing physical constraint verification between fields to identify and exclude logically conflicting data; and performing standardization and normalization processing on the set of key process state parameters.

3. The multi-field coupled crank iron mold sand coated low carbon casting control method according to claim 1, characterized in that: The specific steps of identifying the casting stage and abnormal state based on the set of key process state parameters are as follows: In a complete collection cycle of a single casting task, the standard deviation of the measuring point stress values in the historical qualified casting working condition is calculated, the standard deviation distribution of all cycles is counted, and the first quartile is set as the stress fluctuation threshold; stable cycles with a standard deviation less than the stress fluctuation threshold are selected, and the target reference stress value is calculated by weighted average of the measuring point stress values in the cycle; The current mold temperature value, the target reference temperature value, and the current mold stress value are obtained; The mold temperature value collected in the last cycle is called to obtain the mold temperature value in the last cycle; The square of the difference between the current mold temperature value and the target reference temperature value is calculated, and then divided by the square of the target reference temperature value to obtain the temperature deviation term; Re-calculate the difference between the current mold stress value and the target reference stress value, square it, and divide it by the square of the target reference stress value to obtain the stress offset term; Add the temperature offset term and the stress offset term to form the basic offset part; Calculate the difference between the current mold temperature value and the previous cycle mold temperature value, divide it by the target reference temperature value, and multiply it by the temperature change trend weight coefficient to obtain the trend adjustment term; Add the basic offset part and the trend adjustment term to obtain the state offset intensity value.

4. The multi-field coupled crank iron mold sand coated low carbon casting control method according to claim 1, characterized by: The combined offset degree adjusts the monitoring frequency, controls the parameter update rhythm, and determines whether to enter the adjustment process. The specific steps are as follows: According to the state offset intensity value, the adjustment calculation and the acquisition control strategy are executed in stages: the state offset intensity value is compared with the offset threshold value in real time, and the offset threshold value includes a first offset threshold value and a second offset threshold value; When the state offset intensity value is greater than or equal to the first offset threshold value, the acquisition frequency of temperature and stress is increased, the parameter self-adaptive update operation is suspended, and the adjustment intensity calculation process is entered; When the state offset intensity value is greater than the second offset threshold value and less than the first offset threshold value, the current acquisition point is marked as a key monitoring area, the standby parameter scheme is loaded, and the adjustment operation judgment is delayed; When the state offset intensity value is less than or equal to the second offset threshold value, the current acquisition frequency and parameter configuration are maintained, and the adjustment calculation channel is closed.

5. The multi-field coupled crank iron mold sand coated low carbon casting control method according to claim 1, characterized by: After entering the adjustment process, the control intensity is evaluated according to the state feedback. The specific steps are as follows: Divide the historical cooling process period into complete cooling stages, calculate the standard deviation of the cooling flow value in each period, and count the distribution of all period standard deviations and take the first quartile as the flow fluctuation threshold. The stable period with a standard deviation less than the flow fluctuation threshold is selected, and the average of the cooling flow value in the period is calculated to obtain the reference cooling flow value; the current cooling flow value, the current metal liquid flow rate value, the standard metal liquid flow rate value, the target reference temperature value, and the current instantaneous temperature value are obtained; Divide the current cooling flow value by the reference cooling flow value to obtain the heat flow proportion term; divide the current metal liquid flow rate value by the standard metal liquid flow rate value, and take the ratio as the base to raise to the power of the flow rate adjustment index to obtain the flow rate response term; Add the heat flow proportion term and the flow rate response term to form the physical input term; calculate the difference between the current instantaneous temperature value and the target reference temperature value, divide it by the target reference temperature value, and take it as the input of the hyperbolic tangent function to obtain the temperature offset adjustment term; multiply the physical input term and the temperature offset adjustment term to obtain the control adjustment amplitude value.

6. The multi-field coupled crank iron mold sand coated low carbon casting control method of claim 1, wherein: The control intensity is used as the basis for controlling the heating power, cooling range, and sand covering rhythm. The specific steps are as follows: According to the control adjustment amplitude value, the thermal control adjustment and sand covering control strategy are executed in stages: the control adjustment amplitude value is compared with the control threshold value in real time, and the control threshold value includes a first control threshold value and a second control threshold value; When the control adjustment amplitude value is greater than or equal to the first control threshold value, the heating power output is increased and switched to continuous heating, the cooling spray area range is expanded, and the sand covering trigger interval is shortened; When the regulation adjustment amplitude value is greater than the secondary regulation threshold value and less than the primary regulation threshold value, the set temperature difference interval of the heating target is expanded, the spraying frequency is increased, the spraying timing is adjusted, and the waiting time between steps in the sand covering propulsion rhythm is compressed; when the regulation adjustment amplitude value is less than or equal to the secondary regulation threshold value, the current heating power, cooling flow rate and sand covering control logic remain unchanged, and no additional intervention is introduced.

7. The multi-field coupled crank iron mold sand coated low carbon casting control method according to claim 1, characterized by: The state response after tracking regulation is generated based on the corresponding relationship between the state after regulation and the target state. The specific steps are as follows: The state response after tracking regulation is generated based on the corresponding relationship between the state after regulation and the target state. The specific steps are as follows: The state response after tracking regulation is generated based on the corresponding relationship between the state after regulation and the target state. The specific steps are as follows: The state response after tracking regulation is generated based on the corresponding relationship between the state after regulation and the target state. The specific steps are as follows: The state response after tracking regulation is generated based on the corresponding relationship between the state after regulation and the target state. The specific steps are as follows:

8. The multi-field coupled crank iron mold sand coated low carbon casting control method of claim 1, wherein: The state response after tracking regulation is generated based on the corresponding relationship between the state after regulation and the target state. The specific steps are as follows: The multi-source physical acquisition module, the process state identification module, the parameter adaptive regulation module and the regulation effect evaluation module are characterized in that:

9. The multi-field coupling crank iron mold sand-coated low-carbon casting control system, applying the multi-field coupling crank iron mold sand-coated low-carbon casting control method of any one of claims 1-8, comprising: The multi-source physical acquisition module is used to acquire thermal, stress and flow-related state information, construct a set of key process state parameters and perform preprocessing. The process state identification module is used to identify the casting stage and abnormal state based on the set of key process state parameters, adjust the monitoring frequency, control parameter update rhythm and decide whether to enter the adjustment process in combination with the offset degree. The parameter adaptive regulation module is used to evaluate the regulation intensity according to the state feedback after entering the adjustment process, and control the heating power, cooling range and sand covering rhythm based on the regulation intensity. ​ The control effect evaluation module is configured to track the state response after the control, generate a response level based on the corresponding relationship between the state after the control and the target state, and perform parameter locking, control frequency adjustment, and data benchmark updating in layers according to the response level.

10. The multi-field coupling crank iron mold sand-coated low-carbon casting control device, applying the multi-field coupling crank iron mold sand-coated low-carbon casting control method of any one of claims 1-8, comprising: The state data construction unit, the phase identification scheduling unit, the adjustment instruction generation unit, and the feedback response analysis unit are characterized by: The state data construction unit is configured to collect thermal state information, stress state information, and flow state information, construct a key process state parameter set, and perform field standardization, time alignment, and abnormality elimination. The phase identification scheduling unit is configured to identify the casting phase and abnormal state, and adjust the collection frequency, control parameter rhythm, and adjustment process determination according to the state deviation intensity value. The adjustment instruction generation unit is configured to calculate the control adjustment amplitude value, and control the output mode of the heating power, cooling spraying range, and covering sand rhythm in stages. The feedback response analysis unit is configured to calculate the control response effect value, and perform parameter freezing, sampling frequency adjustment, and abnormal state control in stages.

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