An alloy material processing process data acquisition and feedback system

Abstract

The present application belongs to the technical field of intelligent monitoring of alloy hot working process, and relates to a data acquisition and feedback system for alloy material working process. The present application synchronously acquires state data and temperature data of the alloy material at a reference frequency through a data acquisition unit, and automatically switches to a diagnostic frequency when the data changes abnormally. A stage judgment unit identifies the working stage according to the state data and working time, and calculates the temperature difference. A regulation and control generation unit calculates the equipment regulation and control amount based on the temperature difference, thermal response parameters and stage planning time. An execution feedback unit executes the control instruction and monitors the temperature response, and triggers a warning when the temperature response continuously deviates. The present application solves the problems of inaccurate temperature control and response lag in the alloy hot working process, realizes real-time intelligent monitoring and self-adaptive regulation and control of the working process, improves the accuracy and stability of temperature control, effectively guarantees the working quality of the alloy material, and enhances the intelligent control level of the hot working process.

Description

Technical Field

[0001] This invention belongs to the field of intelligent monitoring technology for alloy hot working processes, and relates to a data acquisition and feedback system for alloy material processing. Background Technology

[0002] In the hot working of alloy materials, the process typically consists of multiple sequentially executed processing steps, and the effectiveness of each step is highly sensitive to the accuracy of temperature control. The accuracy of temperature control directly determines the evolution path of the material's microstructure, the formation mechanism of its mechanical properties, and the dimensional and performance consistency of the final product. Therefore, achieving highly synchronized acquisition and closed-loop feedback control of material state and temperature parameters is crucial for improving the stability, product consistency, and energy efficiency of hot working.

[0003] However, most existing data acquisition and feedback systems still have certain limitations when facing the nonlinear and time-varying characteristics of material processing. Specifically, these limitations are as follows: (1) When a material undergoes a phase change or is in a heat-sensitive range, its state and temperature often exhibit rapid dynamic evolution. Existing systems mostly use preset fixed sampling frequencies, making it difficult to flexibly adjust the acquisition strategy according to real-time changes. This can easily lead to the omission of key process information or response delays, thereby affecting the timeliness and accuracy of control. In addition, when judging whether a processing stage has changed, existing methods often rely mainly on preset time nodes or single temperature thresholds, failing to incorporate the evolution of the actual physical state of the material into the comprehensive judgment criteria. This may result in inaccurate stage identification, leading to lag or malfunction of control commands.

[0004] (2) Regarding temperature control strategies, most existing methods rely on proportional adjustment based on the temperature deviation at the current moment, failing to incorporate multi-dimensional factors such as the material's thermal response characteristics at the current stage, the response patterns at historical stages, and the remaining controllable time at this stage into the control model. This simplified control logic is difficult to adapt to the dynamically changing thermal dynamics during processing, easily leading to insufficient system response or excessive control. This not only limits the control quality and stability of the system under complex operating conditions but also affects its potential for energy efficiency optimization. Summary of the Invention

[0005] In view of this, in order to solve the problems mentioned in the background technology, a data acquisition and feedback system for alloy material processing is proposed.

[0006] The objective of this invention can be achieved through the following technical solution: a data acquisition and feedback system for alloy material processing, comprising: a data acquisition unit, used to synchronously acquire state data and temperature data of alloy material at a reference frequency in the current processing step, and automatically switch to a diagnostic frequency when the change amplitude of state data or temperature data between adjacent acquisition cycles exceeds the normal fluctuation range.

[0007] The stage judgment unit is used to identify whether the current processing stage has been entered based on the currently collected status data and processing time. If the current processing stage has not been entered, the current temperature difference is determined by combining the current measured temperature with the target temperature corresponding to the current stage.

[0008] The control generation unit is used to calculate the equipment control amount based on the current temperature difference, current thermal response parameters, historical thermal response parameters of the current processing stage, planned duration, and remaining time until the next processing stage.

[0009] The execution feedback unit is used to convert the control quantity into control commands and send them to the actuator. After the command is executed, it continuously monitors the temperature response. If the temperature continues to deviate from the allowable deviation range of the target temperature during continuous steady-state operation, an early warning is triggered.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention introduces an adaptive sampling mechanism based on dynamic switching of state and temperature, and combines the dual criteria of processing time and material state for stage identification, which effectively solves the problem of insufficient dynamic response of traditional fixed frequency sampling to material phase change or heat-sensitive range. The method can automatically switch to the diagnostic frequency according to the real-time state and temperature change amplitude, ensuring the integrity of key process information and response timeliness, thereby improving the accuracy of data acquisition and the timeliness of control commands.

[0011] (2) This invention dynamically corrects the control amount calculated based on the current temperature difference by integrating the current stage thermal response parameters, historical steady-state thermal response parameters, stage planned duration and remaining time until the next stage, replacing the adjustment logic that only depends on the current temperature difference. This method avoids the risk of response lag or over-adjustment by analyzing the thermal response differences of the material at each stage and correcting the control amount in real time. At the same time, it achieves energy efficiency optimization and process consistency assurance by optimizing the matching relationship between the control amplitude and energy input. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram showing the connection of each unit in the alloy material processing data acquisition and feedback system of the present invention.

[0014] Figure 2 This is a flowchart of the method for determining whether to proceed to the next processing stage in this invention.

[0015] Figure 3 This is a flowchart of the current temperature difference identification method in this invention. Detailed Implementation

[0016] 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.

[0017] Please see Figure 1 As shown, the present invention provides a data acquisition and feedback system for alloy material processing, comprising: a data acquisition unit, a stage judgment unit, a control generation unit, and an execution feedback unit. The connection relationship between the units is as follows: the data acquisition unit and the stage judgment unit are connected, the stage judgment unit and the control generation unit are connected, and the control generation unit and the execution feedback unit are connected.

[0018] The data acquisition unit is used to synchronously acquire the state data and temperature data of the alloy material at a reference frequency during the current processing step. When the change in state data or temperature data between adjacent acquisition cycles exceeds the normal fluctuation range, it automatically switches to the diagnostic-level frequency.

[0019] After the current processing step is started, the data acquisition unit synchronously acquires the state data and temperature data of the alloy material at a preset reference frequency.

[0020] Furthermore, the method for acquiring the state data and temperature data of the alloy material is as follows: the state data and temperature data of the alloy material are simultaneously acquired by a first non-contact sensing device and a second non-contact sensing device respectively installed on the processing equipment.

[0021] Considering that the physical state of materials during thermal processing, such as phase change, deformation, and surface reflectivity, is closely related to temperature, if the two are not synchronized, it will lead to inaccurate subsequent judgments. Therefore, a hardware-level synchronization mechanism is adopted.

[0022] In each sampling cycle, the same hardware trigger signal simultaneously initiates data acquisition operations for both the first non-contact sensing device and the second non-contact sensing device. The system acquires data at a reference frequency or a diagnostic-level frequency, and the time interval between two adjacent acquisitions is called the acquisition cycle.

[0023] The first non-contact sensing device and the second non-contact sensing device each output valid data once within a preset response window after receiving the hardware trigger signal, and mark it with the same time identifier.

[0024] The preset response window is set to be no less than the maximum response time required by the one with the longer response time between the first non-contact sensing device and the second non-contact sensing device, with an additional 20% time margin reserved.

[0025] In a preferred embodiment, if the maximum response time of the first sensing device is 8 milliseconds and the maximum response time of the second sensing device is 12 milliseconds, then the length of the preset response window should be at least 14.4 milliseconds; for ease of hardware implementation, it can be rounded to 15 milliseconds.

[0026] The time difference between the acquisition time of the state data and the temperature data is equal to the response time difference required for the two sensing devices to output valid data from receiving the hardware trigger signal. The state data is at least one process response signal that can characterize the current physical state or phase transition process of the material.

[0027] For example, hot working of alloy materials includes a variety of typical processes, such as solution treatment, age hardening, annealing, quenching, etc. Taking the solution-aging heat treatment process as an example, it is further divided into a heating stage, a solution holding stage, a quenching and cooling stage, and an aging precipitation stage.

[0028] During the heating stage, eddy current response signals reflecting the change of material resistivity with temperature can be used as state data; during the solution treatment and heat preservation stage, electromagnetic impedance signals characterizing the homogenization of solute atoms can be used as state data; during the quenching and cooling stage, thermal radiation or infrared temperature gradient signals related to cooling rate and thermal stress can be used as state data; during the aging precipitation stage, high-frequency eddy current or permeability response parameters sensitive to the size and density of precipitated phases can be used as state data.

[0029] The temperature data is a thermal state signal of the material surface or near-surface region.

[0030] It should be explained that in the hot working process of alloys, temperature only reflects the thermal state, while the actual physical state of the material directly determines whether it has completed the current process target. If only temperature is relied upon for stage judgment or control, it is easy to make misjudgments due to thermal hysteresis or local temperature difference. Introducing state data as a key criterion in parallel with temperature can achieve dual verification of the material's actual progress: on the one hand, it is used to accurately identify the timing of processing stage switching, and on the other hand, it provides process feedback basis for temperature control, thereby improving the accuracy of the entire closed-loop control system.

[0031] Considering that the material state and temperature fluctuations are small during the steady-state processing stage, high-frequency data acquisition is not required; however, when phase transitions, equipment malfunctions, or process disturbances occur, the data will show abrupt changes.

[0032] Therefore, the system determines in real time whether the changes in status or temperature data during adjacent sampling periods exceed the normal fluctuation range. If so, it automatically switches the sampling frequency to a diagnostic-level frequency, such as 10 times per second or higher.

[0033] Furthermore, when the change in state data or temperature data between adjacent acquisition cycles exceeds the normal fluctuation range, the automatic switch to the diagnostic frequency includes: in the current processing procedure, the procedure is divided into multiple processing stages according to the preset time progress and material state.

[0034] For example, in the hot processing of the alloy material, each processing stage is configured with a planned start time and a corresponding state judgment benchmark value; based on the running time of the current processing process and the collected state data, it is determined whether to enter the next processing stage: only when the running time is not less than the planned start time of the next processing stage and the currently collected state data is not less than the state judgment benchmark value corresponding to the next processing stage, it is determined that the next processing stage has been entered.

[0035] Acquire the state data sequence and temperature data sequence recorded during the most recent continuous steady-state operation within the current stage.

[0036] Furthermore, the method for setting the steady-state operation period is as follows: the current processing stage contains a sequence of M consecutive acquisition cycles, where M≥3 and is an integer, and the consecutive acquisition cycle refers to the cycle that is sequentially adjacent in time and has no missing data at the same sampling frequency.

[0037] It should be noted that M≥3 and is an integer is because the determination of steady-state operation requires a sufficient number of continuous data points to eliminate interference from random fluctuations or single-point noise. Using only two periods is insufficient to distinguish between trend changes and random disturbances; however, if data from three or more consecutive periods all satisfy the fluctuation constraints, the system can be preliminarily considered to be in a statistically stable state, providing a reliable basis for calculating standard deviation, thermal response parameters, or allowable deviations. In practical applications, M1 is typically taken as 3 to 5, balancing sensitivity and robustness.

[0038] For each period in the corresponding sequence during steady-state operation, excluding the first period, the absolute difference between the state data and the state data of the previous period is less than or equal to the upper limit of state fluctuation, and the absolute difference between the temperature data and the temperature data of the previous period is less than or equal to the upper limit of temperature fluctuation.

[0039] The standard deviation of the state data sequence is calculated, and then multiplied by a preset factor to obtain the upper limit of the fluctuation of the state data. The standard deviation of the temperature data sequence is calculated, and then multiplied by the same preset factor to obtain the upper limit of the fluctuation of the temperature data.

[0040] In a preferred embodiment, the preset multiplier is 3. This value is based on the 3σ principle in statistics: under the assumption of normal distribution, approximately 99.7% of the data points fall within the range of mean ± 3 times the standard deviation. Therefore, multiplying the standard deviation by 3 as the upper limit of fluctuation can effectively cover normal process fluctuations while remaining sensitive to abnormal changes.

[0041] This multiplier is applicable to most steady-state hot processing processes; in other embodiments, it can also be adjusted between 2.5 and 3.5 according to process stability requirements, but it should not be lower than 2 or higher than 4, in order to balance the false alarm rate and the false alarm rate.

[0042] In the current acquisition cycle, calculate the absolute difference between the current status data and the status data of the previous acquisition cycle, and the absolute difference between the temperature data and the temperature data of the previous acquisition cycle.

[0043] If the absolute difference of the status data is greater than the upper limit of the status data fluctuation, or the absolute difference of the temperature data is greater than the upper limit of the temperature data fluctuation, then the current sampling frequency will be switched from the reference frequency to the diagnostic frequency.

[0044] When a data sequence consistent with steady-state operation is identified at the diagnostic-level frequency, the acquisition frequency is restored to the reference frequency.

[0045] It should be explained that, in each acquisition cycle, considering that during steady-state operation, the changes in state data and temperature data between adjacent acquisition cycles are small and stable, while when the processing enters a non-steady-state state, the changes may increase significantly.

[0046] Therefore, by calculating the absolute difference between the current state data or temperature data and the previous period in real time, if any difference exceeds the corresponding fluctuation limit, it is determined that the current process has deviated from the steady state and there is dynamic disturbance. At this time, the sampling frequency is automatically switched from the reference frequency to a higher density diagnostic frequency to improve the dynamic capture capability. When a data sequence that meets the steady state judgment condition, i.e., the change has not exceeded the limit in multiple consecutive periods, is continuously collected at the diagnostic frequency, it is considered that the process has returned to stability and then returns to the reference frequency.

[0047] In a preferred embodiment, the solution treatment-aging heat treatment process of the aluminum alloy is monitored. In the initial stage, state data such as electromagnetic response signals and temperature data are synchronously acquired at a reference frequency (1 Hz, i.e., one acquisition cycle per second). During the solution treatment and holding stage, if the operating time is ≥12 minutes, the system identifies the most recent continuous steady-state operation period, comprising three consecutive acquisition cycles, with a state data standard deviation of 0.7 units and a temperature data standard deviation of 1.0℃. Multiplying both by a preset factor of 3 yields an upper limit for state fluctuation of 2.1 units and an upper limit for temperature fluctuation of 3.0℃.

[0048] In the 1320th acquisition cycle, corresponding to a running time of 22 minutes, the absolute difference between the current status data and the previous cycle was calculated to be 2.5 units, exceeding 2.1 units; the temperature difference was 2.3℃, within the limit. Because the status data difference exceeded its upper fluctuation limit, an abnormal sudden change was determined, and the system immediately switched to the diagnostic frequency of 10Hz.

[0049] Subsequently, continuous data acquisition at 10Hz was conducted. Monitoring showed that, starting from cycle 1321, the state and temperature difference for three consecutive cycles did not exceed their respective fluctuation limits, confirming a return to steady state. At this point, the operation was still in the solution treatment and heat preservation phase. The acquisition frequency was then restored to the 1Hz reference frequency, and subsequent monitoring and phase judgments continued.

[0050] The stage judgment unit is used to identify whether the current processing stage has been entered based on the currently collected status data and processing time. If the current processing stage has not been entered, the current temperature difference is determined by combining the current measured temperature with the target temperature corresponding to the current stage.

[0051] The stage determination unit is used to identify whether the current processing stage has been entered based on the currently collected status data and processing progress time. Traditional methods rely solely on time judgment, which is prone to misjudgment due to individual material differences or equipment delays. This invention combines time thresholds and status thresholds to improve the accuracy of stage identification.

[0052] For further details, please refer to [link / reference]. Figure 2 As shown, the step of identifying whether the current processing stage has been entered based on the currently collected status data and processing time includes: obtaining the running time of the current processing process and reading the planned start time of the next processing stage; at the same time, obtaining the currently collected status data and reading the status judgment benchmark value corresponding to the next processing stage.

[0053] The process is considered to have entered the next processing stage only when the running time is not less than the planned start time and the status data is not less than the status judgment benchmark value.

[0054] In a preferred embodiment, the current processing time is first obtained as 41.8 minutes, and the planned start time of the next processing stage is read as 42 minutes; at the same time, the status data of the current collection cycle is obtained as 85 units, and the status judgment benchmark value corresponding to the next processing stage is read as 90 units.

[0055] Since the current running time of 41.8 min is less than the planned start time of 42 min, and the status data of 85 is less than the status judgment benchmark value of 90, the dual conditions of running time ≥ planned start time and status data ≥ status judgment benchmark value are not met. Therefore, it is determined that the next processing stage has not yet been entered and the current stage is still in progress. The temperature will continue to be adjusted according to the target temperature of this stage, such as 520℃.

[0056] The system only determines to officially enter the next processing stage when the running time reaches 42.1 minutes and the acoustic emission signal intensity rises to 93 units, both conditions being met simultaneously.

[0057] Considering that some processes, such as solution treatment and age hardening, depend on the internal state of the material rather than simply the progression of time, relying solely on time to determine the stage can easily lead to misjudgment. Introducing state data as a dual verification can ensure that the stage switching is consistent with the actual progress of the material.

[0058] If the system has not yet entered the next stage, it calculates the current temperature difference by combining the current measured temperature with the target temperature preset for the current stage. This temperature difference is used for subsequent control calculations.

[0059] For further details, please refer to [link / reference]. Figure 3 As shown, the current temperature difference identification method is as follows: based on the stage judgment result, confirm that any of the following situations are true: (a) the running time of the current processing process is less than the planned start time of the next processing stage.

[0060] (b) The material state data collected at the moment is less than the state judgment benchmark value corresponding to the next processing stage.

[0061] When condition (a) or condition (b) is met, read the target temperature value pre-configured for the current processing stage.

[0062] It should be explained that the purpose of setting conditions (a) and (b) is to ensure the dual reliability of stage identification: the time dimension prevents premature stage switching due to accidental fluctuations in state data, and the state dimension prevents ignoring the actual reaction process of the material by relying solely on time; only when either condition is met, i.e., the time has not arrived or the state has not been reached, will the system confirm that it is still in the current stage, and will use the target temperature corresponding to the current stage for regulation accordingly, thereby avoiding mismatch of control strategy caused by stage misjudgment.

[0063] Obtain the measured temperature value output by the temperature sensor during the current sampling period, and subtract the measured temperature value from the target temperature value as the current temperature difference.

[0064] Considering that the target temperature is the process setting value, while the measured temperature reflects the current thermal state, the difference between the two directly reflects the control requirements.

[0065] The control generation unit is used to calculate the equipment control amount based on the current temperature difference, current thermal response parameters, historical thermal response parameters of the current processing stage, planned duration, and remaining time until the next processing stage.

[0066] The control generation unit is used to calculate reasonable equipment control quantities, such as heating power adjustment and cooling water flow rate change, based on the current temperature difference, thermal response characteristics, and time constraints. Traditional PID control relies only on the current error and does not consider material thermal inertia and time limits, which can easily lead to overshoot or response lag.

[0067] Furthermore, the calculation method for the device control quantity is as follows: select M consecutive acquisition cycles, and obtain the measured temperature value output by the temperature sensing device and the device output quantity synchronously recorded by the execution feedback unit in each cycle.

[0068] Calculate the change in measured temperature and the corresponding change in equipment output within each cycle, exclude cycles in which the change in equipment output is zero, and calculate the arithmetic mean of the ratios of the temperature change and the change in equipment output for the remaining cycles to obtain the thermal response parameters.

[0069] Considering that the thermal response can change with the material state, furnace atmosphere or equipment aging, relying solely on the initial calibration value can easily lead to control lag; therefore, historical thermal response parameters, i.e. thermal response parameters recorded during the most recent steady-state period in the current stage, are introduced for dynamic correction.

[0070] Calculate the planned duration of the current processing stage based on the planned start time of the current processing stage and the planned start time of the next processing stage.

[0071] Calculate the remaining time until the planned start time of the next processing stage based on the current system time.

[0072] The ratio of the thermal response parameter to the thermal response parameter recorded during the most recent steady-state operation in the current processing stage is used as the first correction factor, and the value is 1 when the ratio is less than 1.

[0073] The ratio of the planned duration to the remaining time is used as a second correction factor, which is set to 1 when the ratio is less than 1.

[0074] It should be noted that when calculating the first or second correction factor, if the ratio is less than 1, it should be set to 1. This is to prevent excessive weakening of the control force due to decreased response capability or sufficient time: when thermal response parameters decay due to equipment aging or changes in material state, directly using a ratio less than 1 would lead to unreasonable compression of the control amount, making it difficult to effectively correct temperature deviations. Similarly, if there is still sufficient time remaining, a time ratio less than 1 would weaken the urgency of control and may delay the achievement of the target. Therefore, setting the lower limit of the ratio to 1 ensures that the control amount is maintained at least at the baseline level, avoiding control lag or failure due to conservative correction.

[0075] The formula for calculating the initial control amount is as follows: .

[0076] Where ΔT is the current temperature difference, and K is the current thermal response parameter. As the first correction factor, As the second correction factor, This represents the basic control quantity calculated based on the current thermal response parameter K, used to characterize the initial control intensity required to eliminate the current temperature deviation under the current material and equipment conditions.

[0077] The calculation formula for the initial control amount introduces a first correction factor and a second correction factor on the basis of the basic control amount to dynamically adapt to changes in the system's thermal response capability and the urgency of the timing: the first correction factor is the ratio of the current thermal response parameter to the thermal response parameter recorded during the most recent steady-state period in the current stage. It is used to compensate for the attenuation of response capability caused by material state evolution, equipment aging or environmental disturbances, to ensure that the control amount is not lower than the historical steady-state level and to avoid correction lag.

[0078] The second correction factor is the ratio of the planned duration of the current stage to the remaining time. It is used to amplify the control intensity when the stage is about to switch, so as to eliminate temperature deviation within a limited time, while preventing overshoot caused by premature strong control when there is sufficient time. The two work together to ensure that the control amount is adapted to the current thermodynamic characteristics and matches the process timing constraints.

[0079] It dynamically compensates for changes in the current system's thermal response capability and adaptively enhances the control intensity based on the urgency of the remaining time.

[0080] The initial control amount is subjected to a limit process, and the result is used as the final equipment control amount.

[0081] The method for limiting the initial control amount is as follows: obtain the lower and upper limits of the actuator's output, and limit the initial control amount to be no less than the lower limit and no greater than the upper limit.

[0082] It should be explained that this method is designed to ensure that control commands are always within the physical executable range of the actuator, preventing control failures, equipment overloads, or process anomalies caused by algorithm outputs exceeding equipment capabilities.

[0083] It should be explained that the equipment control quantity is a key intermediate variable connecting temperature deviation sensing and actuator action. Its function is to transform the current process state, such as temperature deviation, system thermal response characteristics, and remaining time of stage, into executable control commands, directly determining the output intensity of heating, cooling, or other execution units. This control quantity not only reflects the need to correct the current deviation but also integrates the system's dynamic characteristics and timing constraints, thereby ensuring that the control is both timely and does not overshoot. At the same time, the equipment control quantity is the core input for realizing closed-loop feedback control, and its accuracy and rationality directly affect the temperature tracking accuracy, stage switching stability, and final material processing quality.

[0084] The execution feedback unit is used to convert the control quantity into control commands and send them to the actuator. After the command is executed, it continuously monitors the temperature response. If the temperature continues to deviate from the allowable deviation range of the target temperature during continuous steady-state operation, an early warning is triggered.

[0085] Furthermore, the allowable deviation range is not a fixed value, but is dynamically set. The method for obtaining it is to obtain the target temperature of the current processing stage and the temperature data sequence recorded during the most recent steady-state operation of the current processing stage.

[0086] Calculate the absolute difference between the measured temperature and the target temperature for each acquisition cycle during the steady-state operation period, and take the maximum value as the allowable deviation.

[0087] Calculate the upper and lower limits of the allowable deviation range: add the allowable deviation amount to the target temperature as the upper limit, and subtract the allowable deviation amount from the target temperature as the lower limit.

[0088] It should be explained that using the maximum absolute difference as the allowable deviation avoids frequent false alarms due to overly strict settings, or missed detection of real anomalies due to overly lenient settings. By allowing the target temperature to fluctuate around this deviation, a dynamic allowable deviation range is formed, making subsequent deviation judgments more closely aligned with the current operating conditions and improving the accuracy and adaptability of early warnings.

[0089] Furthermore, if the temperature continues to deviate from the allowable deviation range of the target temperature within multiple consecutive acquisition cycles, an early warning will be triggered. Specifically, starting from the first acquisition cycle after the control command is issued, monitoring will begin to determine whether the measured temperature is within the allowable deviation range.

[0090] Record the number of consecutive sampling cycles that do not meet the allowable deviation range; when this number reaches the minimum number of cycles M required during steady-state operation, it is determined that the temperature continues to deviate and an early warning is triggered.

[0091] It should be added that the determination of steady-state operation itself requires that the state and temperature changes do not exceed the normal fluctuation range within M consecutive cycles. Therefore, only when the deviation continues to reach the same time scale can it be reasonably determined that the system has lost its steady-state control capability, rather than being affected by instantaneous disturbances.

[0092] If an alarm is triggered based on a single data collection cycle exceeding the limit, it is highly susceptible to false alarms due to occasional fluctuations, reducing system reliability and potentially causing unnecessary process interruptions or manual intervention. However, by requiring continuous deviations for M consecutive cycles, it not only maintains consistency with steady-state identification logic but also effectively distinguishes between transient disturbances and genuine control failures.

[0093] In summary, this invention, during the hot processing of alloy materials, simultaneously collects state data and temperature data, and dynamically adjusts the sampling frequency based on the magnitude of their changes; it combines processing time and material state conditions to determine the timing of stage switching; it calculates the control amount based on current and historical thermal response parameters and the remaining time of each stage, and performs amplitude limiting processing; at the same time, it dynamically sets the allowable deviation range using the actual temperature fluctuations during steady-state operation, and triggers an early warning when the temperature continues to deviate.

[0094] The above-mentioned operation steps are interconnected to form a complete closed-loop control process, which effectively improves the accuracy of temperature control, the reliability of stage identification, and the timeliness of abnormal response during alloy hot working, thereby ensuring the consistency of material processing quality and process stability.

[0095] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0096] Those skilled in the art will recognize that the algorithmic steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0097] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0098] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0099] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A data acquisition and feedback system for alloy material processing, characterized in that, include: The data acquisition unit is used to synchronously acquire the state data and temperature data of the alloy material at a reference frequency during the current processing procedure. When the change in state data or temperature data between adjacent acquisition cycles exceeds the normal fluctuation range, it automatically switches to the diagnostic-level frequency. The stage judgment unit is used to identify whether the current processing stage has been entered based on the currently collected status data and processing time. If the current processing stage has not been entered, the current temperature difference is determined by combining the current measured temperature with the target temperature corresponding to the current stage. The control generation unit is used to calculate the equipment control amount based on the current temperature difference, current thermal response parameters, historical thermal response parameters of the current processing stage, planned duration, and remaining time until the next processing stage; The current processing stage contains a sequence of M consecutive acquisition cycles, where M≥3 and is an integer. The consecutive acquisition cycle refers to the cycle that is sequentially adjacent in time and has no missing data at the same sampling frequency. The method for calculating the equipment control quantity is as follows: Select M consecutive acquisition cycles, and obtain the measured temperature value output by the temperature sensing device and the device output quantity synchronously recorded by the execution feedback unit in each cycle; Calculate the change in measured temperature and the corresponding change in equipment output in each cycle, and exclude cycles in which the change in equipment output is zero. Calculate the arithmetic mean of the ratio of the temperature change to the change in equipment output for the remaining cycles to obtain the thermal response parameters. Calculate the planned duration of this stage based on the planned start time of the current processing stage and the planned start time of the next processing stage; Calculate the remaining time until the planned start time of the next processing stage based on the current system time; The ratio of the thermal response parameter to the thermal response parameter recorded during the most recent steady-state operation in the current processing stage is used as the first correction factor, and when the ratio is less than 1, it is set to 1; The ratio of the planned duration to the remaining time is used as a second correction factor, which is set to 1 when the ratio is less than 1. The formula for calculating the initial control amount is as follows: ； Where ΔT is the current temperature difference, and K is the current thermal response parameter. As the first correction factor, As the second correction factor, This represents the basic control quantity calculated based on the current thermal response parameter K; The initial control amount is subjected to amplitude limiting, and the result is used as the final equipment control amount. The method for limiting the initial control amount is as follows: Obtain the lower and upper limits of the actuator's output: The initial adjustment amount is limited to no less than the lower limit of output and no more than the upper limit of output; The execution feedback unit is used to convert the control quantity into control commands and send them to the actuator. After the command is executed, it continuously monitors the temperature response. If the temperature continues to deviate from the allowable deviation range of the target temperature during continuous steady-state operation, an early warning is triggered.

2. The data acquisition and feedback system for alloy material processing as described in claim 1, characterized in that, The method for obtaining the state data and temperature data of the alloy material is as follows: The state data and temperature data of the alloy material are collected simultaneously by a first non-contact sensor and a second non-contact sensor respectively installed on the processing equipment. In each sampling period, the same hardware trigger signal simultaneously initiates the data acquisition operation of the first non-contact sensing device and the second non-contact sensing device. The first non-contact sensing device and the second non-contact sensing device each output valid data once within a preset response window after receiving the hardware trigger signal, and mark the same time. The time difference between the acquisition time of state data and temperature data is equal to the response time difference required for the two sensing devices to output valid data from receiving the hardware trigger signal. The state data is at least one process response signal that can characterize the current physical state or phase transition process of the material, and the temperature data is the thermal state signal of the material surface or near-surface region.

3. The data acquisition and feedback system for alloy material processing as described in claim 1, characterized in that, When the change in status data or temperature data between adjacent acquisition cycles exceeds the normal fluctuation range, the system automatically switches to a diagnostic-level frequency, including: In the current processing procedure, this procedure is divided into multiple processing stages according to the preset time progress and material state; Acquire the state data sequence and temperature data sequence recorded during the most recent continuous steady-state operation within the current stage; The standard deviation of the state data sequence is calculated, and the standard deviation is multiplied by a preset factor to obtain the upper limit of the fluctuation of the state data. The standard deviation of the temperature data series is calculated, and the standard deviation is multiplied by the same preset factor to obtain the upper limit of the temperature data fluctuation. In the current acquisition cycle, calculate the absolute difference between the status data and the status data of the previous acquisition cycle, and the absolute difference between the temperature data and the temperature data of the previous acquisition cycle. If the absolute difference of the status data is greater than the upper limit of the status data fluctuation, or the absolute difference of the temperature data is greater than the upper limit of the temperature data fluctuation, then the current sampling frequency will be switched from the reference frequency to the diagnostic frequency. When a data sequence consistent with steady-state operation is identified at the diagnostic-level frequency, the acquisition frequency is restored to the reference frequency.

4. The data acquisition and feedback system for alloy material processing as described in claim 3, characterized in that, The method for setting the steady-state operation period is as follows: For each period in the sequence except the first period, the absolute difference between the state data and the state data of the previous period is less than or equal to the upper limit of state fluctuation, and the absolute difference between the temperature data and the temperature data of the previous period is less than or equal to the upper limit of temperature fluctuation.

5. The data acquisition and feedback system for alloy material processing as described in claim 1, characterized in that, The step of identifying whether the current processing stage has begun based on the currently collected status data and processing time includes: Get the running time of the current processing process and read the planned start time of the next processing stage. At the same time, get the currently collected status data and read the status judgment benchmark value corresponding to the next processing stage. The process is considered to have entered the next processing stage only when the running time is not less than the planned start time and the status data is not less than the status judgment benchmark value.

6. The data acquisition and feedback system for alloy material processing as described in claim 5, characterized in that, The method for identifying the current temperature difference is as follows: Based on the results of the phase assessment, it is confirmed that any of the following situations are true: (a) The current processing time is less than the planned start time of the next processing stage; (b) The currently collected material condition data is less than the condition judgment benchmark value corresponding to the next processing stage; When condition (a) or condition (b) is met, read the target temperature value pre-configured for the current processing stage; Obtain the measured temperature value output by the temperature sensor during the current sampling period; The current temperature difference is obtained by subtracting the measured temperature value from the target temperature value.

7. The data acquisition and feedback system for alloy material processing as described in claim 1, characterized in that, The method for obtaining the allowable deviation range is as follows: Obtain the target temperature for the current processing stage and the temperature data sequence recorded during the most recent steady-state operation of the current processing stage; Calculate the absolute difference between the measured temperature and the target temperature in each acquisition cycle during the steady-state operation period, and take the maximum value as the allowable deviation. Calculate the upper and lower limits of the allowable deviation range: add the allowable deviation amount to the target temperature as the upper limit, and subtract the allowable deviation amount from the target temperature as the lower limit.

8. The data acquisition and feedback system for alloy material processing as described in claim 1, characterized in that, If the temperature continues to deviate from the allowable deviation range of the target temperature within multiple consecutive sampling cycles, an early warning will be triggered, specifically: Starting from the first data acquisition cycle after the control command is issued, monitoring begins to determine whether the measured temperature is within the allowable deviation range. Record the number of consecutive acquisition cycles that do not meet the allowable deviation range; When this number reaches the minimum number of cycles M required for steady-state operation, the temperature is determined to be continuously deviating, and an early warning is triggered.

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