A thermal vacuum test process environment stress self-adaptive regulation and control method

Abstract

This invention discloses an adaptive control method for environmental stress during thermal vacuum testing, belonging to the field of adaptive control technology. It addresses the problem of increased junction temperature risk within a single unit under high-load operating conditions. By monitoring the clock cycle deviation and instantaneous ripple voltage of the test chamber, the operating status of the single-unit simulation is determined based on the instantaneous ripple voltage. The clock cycle deviation is used to determine whether to enter the thermal hysteresis analysis mechanism. The execution delay of the test chamber operator and the shell strain intensity are collected. The thermal accumulation index is calculated using the operator execution delay, and the thermal manifestation characteristics are obtained based on the shell strain intensity. A hidden junction temperature indicator is generated by combining the thermal accumulation index and thermal manifestation characteristics. Based on this, the system selects between continuous test operation and the execution of an environmental stress control strategy. When executing the environmental stress control strategy, the current temperature change rate is retrieved, the control analysis cycle is set, and the edge trigger frequency and logic flip density are statistically analyzed to correct the temperature change rate, thereby improving test safety and data reliability.

Description

Technical Field

[0001] This invention relates to the field of adaptive control technology, and more specifically, to a method for adaptive control of environmental stress during a thermal vacuum test process. Background Technology

[0002] Thermal vacuum testing is an important testing method for simulating space vacuum and extreme thermal environments for individual spacecraft, subsystems, and the entire spacecraft during the ground phase. It verifies the reliability and stability of the tested object in orbit by applying high and low temperature cycles under vacuum conditions.

[0003] The existing technology has the following shortcomings:

[0004] Currently, the existing technology for controlling the thermal vacuum test environment mainly relies on the test chamber temperature setpoint and preset temperature change curve for open-loop or weak closed-loop adjustment. It lacks an effective identification and quantitative analysis mechanism for the hidden heat accumulation and thermal hysteresis effect inside the single unit, which leads to a decrease in the timeliness and accuracy of environmental stress control response and an increase in the risk of junction temperature inside the single unit under high load operation. Therefore, an adaptive control method for environmental stress in the thermal vacuum test process is proposed.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an adaptive control method for environmental stress in a thermal vacuum test process. By employing a multi-source parameter fusion analysis mechanism based on temporal stability and computational running characteristics, a hidden junction temperature determination model is constructed and dynamic adaptive correction of the temperature change rate is achieved to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for adaptive control of environmental stress during a thermal vacuum test, comprising the following steps:

[0008] Step S1: During the thermal vacuum test, monitor the clock cycle deviation and instantaneous ripple voltage of the test chamber, evaluate the single-unit calculation operation status based on the instantaneous ripple voltage, and determine whether to enter the thermal hysteresis analysis mechanism based on the clock cycle deviation.

[0009] Step S2: In the thermal hysteresis analysis mechanism, the operator execution delay and shell strain intensity of the test chamber are collected, the thermal accumulation index of the test chamber is calculated based on the operator execution delay, and the thermal manifestation characteristics of the test chamber are analyzed based on the shell strain intensity.

[0010] Step S3: Perform stealth thermal accumulation analysis on the test chamber based on the comprehensive thermal accumulation index and thermal manifestation characteristics, and generate a stealth junction temperature indicator. Select either continuous operation test or implement environmental stress control strategy based on the stealth junction temperature indicator.

[0011] Step S4: When executing the environmental stress control strategy, retrieve the current temperature change rate of the test chamber, set the control analysis cycle, detect the edge trigger frequency and logic flip density of the test chamber within the control analysis cycle, and correct the current temperature change rate.

[0012] In a preferred embodiment, in step S1, the clock cycle deviation of the test chamber refers to the deviation information generated by the test chamber side after uniformly sensing the timing behavior of the single machine during the thermal vacuum test, which is used to characterize the timing stability.

[0013] Instantaneous ripple voltage refers to short-term voltage fluctuations in the power supply chain of the test chamber during the operational simulation.

[0014] In a preferred embodiment, in step S1, if the instantaneous ripple voltage of the test chamber is greater than or equal to a preset ripple voltage threshold, then the single-machine simulation operation state is determined to be in a high-load operation state.

[0015] If the instantaneous ripple voltage of the test chamber is less than the preset ripple voltage threshold, the single-machine simulation is determined to be in a stable operating state.

[0016] If the single-machine simulation is in a high-load operation state and the clock cycle deviation of the test chamber is greater than or equal to the preset cycle deviation threshold, then it is determined to enter the thermal hysteresis analysis mechanism.

[0017] Conversely, if the condition is not met, the analysis mechanism for thermal hysteresis will not be entered.

[0018] In a preferred embodiment, in step S2, the operator status identification information periodically output by the single machine during the execution of the example is acquired by the running status acquisition device;

[0019] When the received operator status identifier is an operator execution start identifier, record the time when the operator execution start identifier is received;

[0020] When the received operator status identifier is an execution completion identifier, record the time when the operator execution completion identifier is received;

[0021] The operator execution delay is obtained by subtracting the time of receiving the operator execution completion flag from the time of receiving the operator execution start flag.

[0022] In a preferred embodiment, in step S2, a preset acquisition period is set and multiple acquisition times are divided. The strain intensity of the test chamber shell is obtained by strain sensors deployed on the surface of the test chamber shell and integrated into a strain intensity set according to the acquisition sequence.

[0023] The operator execution delay of the test chamber is standardized to obtain the thermal accumulation index of the test chamber;

[0024] The strain fluctuation intensity is obtained by subtracting the maximum and minimum values ​​from the set of strain intensities.

[0025] Select any member in the strain intensity set, subtract it from the next preceding member, and take the absolute value to obtain the strain intensity change of the selected member.

[0026] The strain intensity changes of each member are summed and divided by the preset acquisition period to obtain the strain intensity change rate.

[0027] The intensity of strain fluctuation and the rate of change of strain intensity are standardized to obtain the intensity factor and the rate factor.

[0028] The thermal characteristics of the test chamber are obtained by adding the intensity factor and the velocity factor according to a preset ratio.

[0029] In a preferred embodiment, in step S3, if the heat accumulation index is less than a preset heat accumulation threshold and the heat manifestation characteristic is less than a preset heat manifestation threshold, then the hidden junction temperature indicator is determined to be safe.

[0030] If the heat accumulation index is greater than or equal to the preset heat accumulation threshold, and the heat manifestation characteristic is less than the preset heat manifestation threshold, then the hidden junction temperature is identified as high risk.

[0031] If the heat accumulation index is less than the preset heat accumulation threshold and the heat manifestation characteristic is greater than or equal to the preset heat manifestation threshold, then the hidden junction temperature is identified as an environmental disturbance.

[0032] If the heat accumulation index is greater than or equal to the preset heat accumulation threshold, and the heat manifestation characteristic is greater than or equal to the preset heat manifestation threshold, then the hidden junction temperature is identified as high-load operation.

[0033] In a preferred embodiment, in step S3, a continuous operation test or an environmental stress control strategy is selected based on the hidden junction temperature indicator.

[0034] If the hidden junction temperature indicator is marked as safe or indicates environmental disturbance, the test should continue.

[0035] If the hidden junction temperature is identified as high-risk or high-load operation, then an environmental stress control strategy will be implemented.

[0036] In a preferred embodiment, in step S4, a fixed acquisition time is set, the temperature of the test chamber is acquired by a platinum resistance temperature sensor, and the temperature data is integrated into a set according to the acquisition sequence.

[0037] Perform point-by-point difference analysis on the temperature dataset to obtain the temperature change range of each acquisition time relative to the previous acquisition time.

[0038] The total temperature change is obtained by adding up the temperature change amplitudes at each sampling time.

[0039] Divide the total temperature change by the fixed acquisition time to obtain the current temperature change rate of the test chamber;

[0040] The control and analysis cycle is set, and the level change signal of the logic node of the test chamber is obtained by a high-speed digital signal acquisition device deployed at the output end of the single machine.

[0041] In a preferred embodiment, in step S4, edge detection is performed on the level change signal of the test chamber logic node to identify each event of transitioning from low level to high level or from high level to low level.

[0042] Count the total number of events that transition from low to high or from high to low.

[0043] The edge trigger frequency of the test chamber is obtained by dividing the total number of events that transition from low level to high level or from high level to low level by the control analysis period.

[0044] The number of logic flips in the test chamber is obtained through the on-chip system performance monitoring unit;

[0045] Divide the number of logic flips in the test chamber by the control analysis cycle to obtain the logic flip density of the test chamber.

[0046] The edge triggering frequency and logic flip density of the test chamber are comprehensively analyzed by a pre-trained online state estimation model to obtain dynamic correction coefficients.

[0047] Multiply the dynamic correction factor by the current rate of temperature change to obtain the corrected rate of temperature change.

[0048] The technical effects and advantages of this invention are as follows:

[0049] This invention monitors the clock cycle deviation and instantaneous ripple voltage of the test chamber. Based on the instantaneous ripple voltage, it determines the operating status of the single-machine simulation. Combined with the clock cycle deviation, it determines whether to enter the thermal hysteresis analysis mechanism. In the thermal hysteresis analysis mechanism, it collects the operator execution delay and shell strain intensity of the test chamber. It calculates the heat accumulation index based on the operator execution delay and obtains the thermal manifestation characteristics based on the shell strain intensity. It then generates a hidden junction temperature indicator by combining the heat accumulation index and thermal manifestation characteristics, and selects between continuous operation and the execution of an environmental stress control strategy. When executing the environmental stress control strategy, it retrieves the current temperature change rate, sets the control analysis cycle, and statistically analyzes the edge trigger frequency and logic flip density to correct the temperature change rate. This achieves full-process dynamic monitoring and intelligent control of the test chamber's thermal state, reflecting the single-machine operating load and heat accumulation status in real time, effectively preventing thermal hysteresis and high-load risks, and improving test safety and data reliability. Attached Figure Description

[0050] Figure 1 This is a flowchart illustrating the implementation of an adaptive control method for environmental stress during a thermal vacuum test process according to the present invention.

[0051] Figure 2 This is a schematic diagram illustrating the steps of an adaptive control method for environmental stress during a thermal vacuum test process according to the present invention. Detailed Implementation

[0052] 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.

[0053] This invention monitors the clock cycle deviation and instantaneous ripple voltage of the test chamber. Based on the instantaneous ripple voltage, it determines the operating status of the single-machine simulation. Combined with the clock cycle deviation, it determines whether to enter the thermal hysteresis analysis mechanism. In the thermal hysteresis analysis mechanism, it collects the operator execution delay and shell strain intensity of the test chamber. It calculates the heat accumulation index based on the operator execution delay and obtains the thermal manifestation characteristics based on the shell strain intensity. It then generates a hidden junction temperature indicator by combining the heat accumulation index and thermal manifestation characteristics, and selects between continuous test operation and execution of an environmental stress control strategy. When executing the environmental stress control strategy, it retrieves the current temperature change rate, sets the control analysis cycle, and statistically analyzes the edge trigger frequency and logic flip density to correct the temperature change rate. This achieves full-process dynamic monitoring and intelligent control of the thermal state of the test chamber.

[0054] Example 1: An adaptive control method for environmental stress during a thermal vacuum test, such as... Figures 1 to 2 As shown, it includes the following steps:

[0055] Step S1: During the thermal vacuum test, monitor the clock cycle deviation and instantaneous ripple voltage of the test chamber, evaluate the single-unit calculation operation status based on the instantaneous ripple voltage, and determine whether to enter the thermal hysteresis analysis mechanism based on the clock cycle deviation.

[0056] Step S2: In the thermal hysteresis analysis mechanism, the operator execution delay and shell strain intensity of the test chamber are collected, the thermal accumulation index of the test chamber is calculated based on the operator execution delay, and the thermal manifestation characteristics of the test chamber are analyzed based on the shell strain intensity.

[0057] Step S3: Perform stealth thermal accumulation analysis on the test chamber based on the comprehensive thermal accumulation index and thermal manifestation characteristics, and generate a stealth junction temperature indicator. Select either continuous operation test or implement environmental stress control strategy based on the stealth junction temperature indicator.

[0058] Step S4: When executing the environmental stress control strategy, retrieve the current temperature change rate of the test chamber, set the control analysis cycle, detect the edge trigger frequency and logic flip density of the test chamber within the control analysis cycle, and correct the current temperature change rate.

[0059] The specific implementation is as follows:

[0060] In step S1, the thermal vacuum test continuously monitors the operating characteristics of the single unit under extreme environment through the test chamber. The single unit outputs status signals periodically according to the preset calculation. The power supply may experience instantaneous voltage fluctuations. Due to different levels of activity of internal logic operations, clock cycle deviation or ripple voltage increase may occur, affecting the calculation rhythm and thermal state. During the test, it is necessary to identify the periodic status signals and receive the time sequence, collect the power supply voltage, and calculate the clock cycle deviation and instantaneous ripple voltage to determine the operating state of the single unit and decide whether to enter the thermal hysteresis analysis mechanism.

[0061] The clock cycle deviation of the test chamber refers to the deviation information generated by the test chamber side after uniformly sensing the timing behavior of a single machine during the thermal vacuum test, which is used to characterize the timing stability.

[0062] The reception time of the periodic status signals of the test chamber is obtained by the time synchronization acquisition device inside the test chamber.

[0063] The receiving time interval of adjacent state signals is calculated for the receiving time set. That is, the receiving time of the periodic state signal of a certain test chamber is subtracted from the receiving time of the periodic state signal of the adjacent previous test chamber to obtain the time interval between the receiving time of the periodic state signal of the test chamber and the receiving time of the periodic state signal of the adjacent previous test chamber.

[0064] Repeat the above steps to obtain the time interval between the reception time of the periodic status signal of each test chamber and the reception time of the periodic status signal of the adjacent previous test chamber, and integrate them into a time interval set.

[0065] Divide each member in the time interval set by the preset reference time interval to obtain the degree of deviation of the reception rhythm of each period signal;

[0066] The clock cycle deviation of the test chamber is obtained by averaging the deviation of the received rhythm of each period signal.

[0067] It should be noted that the time synchronization acquisition device refers to the acquisition device deployed in the test chamber for unified time calibration and reception recording of the periodic status signals output by the tested unit; the periodic status signals of the test chamber are the operating status identification signals periodically output by the unit according to the preset operating rhythm during the thermal vacuum test; the preset reference time interval can be set according to the unit's calculation scheduling rhythm, the test chamber's time synchronization accuracy, and the sampling requirements of the periodic status signals.

[0068] Instantaneous ripple voltage refers to the short-term voltage fluctuation information that occurs in the power supply chain of the test chamber during the operation of the simulation. This fluctuation information can reflect the changes in single-machine power consumption and the activity level of internal logic switching.

[0069] The voltage at the power input terminal of the test chamber is acquired by a high-speed voltage acquisition unit and integrated into a voltage sequence according to the acquisition time.

[0070] Perform point-by-point differential analysis on the voltage sequence to obtain the voltage change amplitude at each acquisition time relative to the previous acquisition time;

[0071] The instantaneous ripple voltage of the test chamber is obtained by averaging the voltage change amplitude of each acquisition time relative to the previous acquisition time.

[0072] The instantaneous ripple voltage of the test chamber is compared with the preset ripple voltage threshold for judgment:

[0073] If the instantaneous ripple voltage of the test chamber is greater than or equal to the preset ripple voltage threshold, the single-machine simulation is determined to be in a high-load operation state.

[0074] If the instantaneous ripple voltage of the test chamber is less than the preset ripple voltage threshold, the single-machine simulation is determined to be in a stable operating state.

[0075] The clock cycle deviation of the test chamber is compared with the preset cycle deviation threshold, and the judgment is made in conjunction with the single-machine calculation example operation status:

[0076] If the single-machine simulation is in a high-load operation state and the clock cycle deviation of the test chamber is greater than or equal to the preset cycle deviation threshold, then it is determined to enter the thermal hysteresis analysis mechanism.

[0077] Conversely, if the condition is not met, the analysis mechanism for thermal hysteresis will not be entered.

[0078] It should be explained that the high-speed voltage acquisition unit refers to a voltage acquisition unit deployed in the test chamber for high-time-resolution sampling of the voltage at the power input terminal of the tested unit; point-by-point differential analysis refers to calculating the difference between the data values ​​of two adjacent sampling points in a data sequence arranged in chronological order to obtain the change amplitude of each sampling moment relative to the previous sampling moment; the preset ripple voltage threshold can be set according to the load characteristics of the single-unit simulation, the stability level of the power system, and the data sampling requirements of the high-speed voltage acquisition unit; high-load operation state refers to an operation state in which the internal logic operation, data access, or function module call is at a high level when the single unit executes the simulation during the thermal vacuum test, resulting in a significant increase in power consumption and timing disturbances; stable operation state refers to an operation state in which the internal operation activity and function module call remain at a relatively stable level when the single unit executes the simulation during the thermal vacuum test, the transient voltage fluctuation amplitude at the power input terminal is small, and the simulation execution rhythm does not show obvious disturbances; the preset period deviation threshold can be set according to the scheduling rhythm of the single-unit simulation, the time synchronization accuracy of the test chamber, and the sampling and statistical requirements of periodic status signals.

[0079] By monitoring the clock cycle deviation and instantaneous ripple voltage of the test chamber, the real-time operating status and load fluctuation of the single-machine simulation are reflected, enabling accurate determination of high load or stable operating status, thereby effectively identifying whether the thermal hysteresis analysis mechanism has been entered, and providing a reliable basis for subsequent thermal management.

[0080] In step S2, the thermal vacuum test is an experimental method that uses a test chamber to continuously monitor the operating characteristics and thermal status assessment of a single machine under extreme environments. During the operation of the simulation, the single machine periodically outputs operator status identification signals. At the same time, the shell of the test chamber undergoes slight deformation under the load of the simulation or changes in ambient temperature. It is possible that the execution delay of one operator is longer and the execution of another operator is faster, resulting in heat accumulation and abnormal external characteristics, which affects the overall thermal status assessment. During the thermal vacuum test, the operator status identification and its receiving time sequence are first identified, and the basic data of shell strain strength and operator execution delay are obtained.

[0081] The operator status identification information periodically output by the single machine during the execution of the example is obtained through the operation status acquisition device;

[0082] When the received operator status identifier is an operator execution start identifier, record the time when the operator execution start identifier is received;

[0083] When the received operator status identifier is an execution completion identifier, record the time when the operator execution completion identifier is received;

[0084] Subtract the time of receiving the operator execution completion flag from the time of receiving the operator execution start flag to obtain the operator execution delay.

[0085] Repeat the above steps to obtain the operator execution delay of multiple operators, and calculate the average value of the operator execution delay of multiple operators to obtain the operator execution delay of the test chamber;

[0086] It should be noted that the operation status acquisition device refers to the device that periodically collects the operator execution status identification information inside the single machine during the operation of the single machine example. It is used to obtain the operator status identification information periodically output by the single machine during the operation of the example. The operator status identification information refers to the status signal periodically output by the single machine during the operation of the example, which is used to characterize the execution progress of the operator.

[0087] The acquisition cycle is preset and multiple acquisition times are divided. The strain intensity of the test chamber shell is obtained by strain sensors deployed on the surface of the test chamber shell and integrated into a strain intensity set according to the acquisition sequence.

[0088] The operator execution delay of the test chamber is standardized to obtain the thermal accumulation index of the test chamber;

[0089] The strain fluctuation intensity is obtained by subtracting the maximum and minimum values ​​from the set of strain intensities.

[0090] Select any member in the strain intensity set, subtract it from the next preceding member, and take the absolute value to obtain the strain intensity change of the selected member.

[0091] Repeat the above steps to obtain the strain intensity change of each member;

[0092] The strain intensity changes of each member are summed and divided by the preset acquisition period to obtain the strain intensity change rate.

[0093] The intensity of strain fluctuation and the rate of change of strain intensity are standardized to obtain the intensity factor and the rate factor.

[0094] The thermal characteristics of the test chamber are obtained by adding the intensity factor and the velocity factor according to a preset ratio.

[0095] It should be explained that the preset acquisition cycle can be set according to the single-machine simulation scheduling rhythm, the response capability of the test chamber sensors, and the time resolution of the operator execution status acquisition; the strain sensor is a sensing device that collects information on the minute deformation of the test chamber structure in real time during simulation operation or changes in ambient temperature, and is used to obtain the shell strain strength of the test chamber; the shell strain strength characterizes the numerical value of the minute deformation amplitude of the test chamber material or structure under force or heat; the standardization processing method includes, but is not limited to, standard linear transformation based on interval scaling, Z-Score standardization method based on statistics, or normalization method based on nonlinear mapping function. The application method of standardization processing will not be elaborated here; the preset ratio can be set according to the characteristics of the test chamber shell material, the characteristics of operator execution, and the sampling accuracy of the strain sensor.

[0096] By collecting the execution delay of the single-machine operator and the strain strength of the test chamber shell, a thermal accumulation index and thermal manifestation characteristics are constructed to achieve quantitative analysis of the thermal behavior of the single machine, improve the sensitivity to potential thermal accumulation and structural strain changes, and provide accurate input data for the analysis of hidden thermal accumulation.

[0097] In step S3, during the single-machine simulation, operator execution delay or shell strain may occur, leading to abnormal heat accumulation index and thermal manifestation characteristics. This may result in a hidden high temperature or high load operating state, which may affect the safety and stability of the single-machine simulation. During the thermal vacuum test, the heat accumulation index and thermal manifestation characteristics of the test chamber are first identified, and the continuous operation test or the environmental stress control strategy is selected based on the hidden junction temperature indicator to ensure that the thermal state is controllable and reduce potential risks.

[0098] The stealth thermal accumulation analysis of the test chamber was performed by combining the comprehensive thermal accumulation index and thermal manifestation characteristics, and a stealth junction temperature indicator was generated.

[0099] The specific process for analyzing hidden heat accumulation is as follows:

[0100] The heat accumulation index and thermal manifestation characteristics are compared with the preset heat accumulation threshold and preset thermal manifestation threshold, respectively, for judgment:

[0101] If the heat accumulation index is less than the preset heat accumulation threshold and the heat manifestation characteristic is less than the preset heat manifestation threshold, then the hidden junction temperature indicator is determined to be safe.

[0102] If the heat accumulation index is greater than or equal to the preset heat accumulation threshold, and the heat manifestation characteristic is less than the preset heat manifestation threshold, then the hidden junction temperature is identified as high risk.

[0103] If the heat accumulation index is less than the preset heat accumulation threshold and the heat manifestation characteristic is greater than or equal to the preset heat manifestation threshold, then the hidden junction temperature is identified as an environmental disturbance.

[0104] If the heat accumulation index is greater than or equal to the preset heat accumulation threshold, and the heat manifestation characteristic is greater than or equal to the preset heat manifestation threshold, then the hidden junction temperature is identified as high load operation.

[0105] Choose between continuous operation testing or implementing environmental stress control strategies based on the hidden junction temperature indicator;

[0106] If the hidden junction temperature indicator is marked as safe or indicates environmental disturbance, the test should continue.

[0107] If the hidden junction temperature is identified as high-risk or high-load operation, then an environmental stress control strategy will be implemented.

[0108] It should be explained that the preset thermal accumulation threshold can be set according to the execution delay characteristics of the single-machine operator, the thermal response capability of the test chamber, and the calculation requirements of the thermal accumulation index; the preset thermal manifestation threshold can be set according to the strain characteristics of the test chamber shell, the sampling accuracy of the strain sensor, and the calculation requirements of the thermal manifestation characteristics; the environmental stress control strategy refers to the control scheme that dynamically adjusts the thermal environment, power supply status, or test chamber operation rhythm of the test chamber according to the hidden junction temperature indicator and the thermal accumulation and thermal manifestation characteristics of the test chamber during the test chamber test case operation, so as to reduce the thermal stress accumulation under high-risk or high-load operation conditions and ensure the safe and stable operation of the single-machine test case.

[0109] By generating a hidden junction temperature indicator based on the comprehensive heat accumulation index and thermal manifestation characteristics, and selecting to continue operation or implement an environmental stress control strategy based on the indicator, the thermal environment and the operation rhythm of the simulation case are actively adjusted under high-risk or high-load operation conditions, effectively reducing the risk of thermal stress accumulation and ensuring the safe and stable operation of the single-machine simulation case.

[0110] In step S4, during the operation of the single machine in the simulation, the rate of temperature change may increase or the logic node may frequently flip, resulting in abnormal edge triggering frequency and logic flip density, which will affect the thermal state control and the operation rhythm of the simulation. During the thermal vacuum test, the temperature of the test chamber and the logic node level change signal are first acquired. The dynamic correction coefficient is calculated through the online state estimation model and applied to the temperature change rate correction to ensure that the thermal state of the single machine simulation is controllable and stable under high load or complex working conditions.

[0111] Set a fixed acquisition time, acquire the temperature of the test chamber through a platinum resistance temperature sensor, and integrate the acquired temperatures into a set according to the acquisition sequence;

[0112] Perform point-by-point difference analysis on the temperature dataset to obtain the temperature change range of each acquisition time relative to the previous acquisition time.

[0113] The total temperature change is obtained by adding up the temperature change amplitudes at each sampling time.

[0114] Divide the total temperature change by the fixed acquisition time to obtain the current temperature change rate of the test chamber;

[0115] It should be noted that the fixed acquisition time can be set according to the thermal response characteristics of the test chamber, the sampling accuracy of the temperature sensor, and the analysis requirements of the temperature change rate; the platinum resistance temperature sensor is a sensor that uses the resistance of platinum material to change with temperature to measure temperature, and is used to obtain the temperature of the test chamber.

[0116] Set the control and analysis cycle, and obtain the level change signal of the logic node of the test chamber through the high-speed digital signal acquisition device deployed at the output end of the single machine;

[0117] Edge detection is performed on the level change signals of the logic nodes in the test chamber to identify each event that transitions from a low level to a high level or from a high level to a low level.

[0118] Count the total number of events that transition from low to high or from high to low.

[0119] The edge trigger frequency of the test chamber is obtained by dividing the total number of events that transition from low level to high level or from high level to low level by the control analysis period.

[0120] The number of logic flips in the test chamber is obtained through the on-chip system performance monitoring unit;

[0121] The logic flip density of the test chamber is obtained by dividing the number of logic flips in the test chamber by the control analysis cycle.

[0122] It should be noted that the control and analysis cycle can be set according to the switching characteristics of the test chamber's logic nodes, the high-speed digital signal acquisition capability, and the calculation requirements of the dynamic correction coefficient. The high-speed digital signal acquisition device refers to the electronic acquisition unit deployed at the output end of the test chamber's logic nodes, used to acquire the logic node level change signals in real time during the thermal vacuum test. Edge detection refers to analyzing the logic node level change sequence obtained by the high-speed digital signal acquisition device, identifying each event of transitioning from low level to high level or from high level to low level, in order to statistically analyze the logic node switching frequency and calculate the edge trigger frequency. The on-chip system performance monitoring unit refers to the monitoring module deployed in the control chip inside the test chamber's single unit, used to collect and statistically analyze the operating performance data of the test chamber's logic nodes in real time, including the number of logic flips, operator execution status, operating frequency, and other indicators related to logic load.

[0123] The edge triggering frequency and logic flip density of the test chamber are comprehensively analyzed by a pre-trained online state estimation model to obtain dynamic correction coefficients. The model adopts a temporal feature extraction architecture that integrates gated recurrent units and one-dimensional convolutional neural networks.

[0124] The model training process includes the following steps:

[0125] Data preparation: Collect historical test data to construct a training set, including edge triggering frequency, logic flip density, and corresponding optimal correction coefficient labels calculated based on the ideal heat conduction model;

[0126] Data preprocessing: Normalize the edge trigger frequency and logic flip density of the input, and standardize the correction coefficient labels of continuous values;

[0127] Training strategy: The Huber loss function is adopted. This function is not sensitive to outliers in the data, which can enhance the robustness of the model in engineering noise environment and ensure that the trained model output is stable and reliable.

[0128] Optimization method: The AdamW optimizer is used in conjunction with a cosine annealing learning rate scheduling strategy with hot restart. The AdamW optimizer can effectively prevent overfitting, and the hot restart strategy can revitalize the optimization when training is stuck in a local stagnation state, which helps to find better solutions in complex regression problems.

[0129] Model validation: On the independent validation set, not only is the mean absolute error between the dynamic correction coefficients output by the model and the target coefficients evaluated, but error distribution statistics and error analysis at key working points are also added to ensure that the model performs reliably in various typical scenarios without systematic bias.

[0130] Multiply the dynamic correction factor by the current rate of temperature change to obtain the corrected rate of temperature change.

[0131] It needs to be explained that the temporal feature extraction architecture integrating a gated recurrent unit and a one-dimensional convolutional neural network refers to a deep neural network model. This model first extracts local temporal features from temporal signals such as edge trigger frequency and logic flip density collected at high speed from the test chamber using a one-dimensional convolutional neural network. Then, a gated recurrent unit is used to model the long-term dependencies of the sequence, achieving accurate prediction of the dynamic correction coefficient. The Huber loss function is a loss function used to measure the error between the predicted and true values, suitable for processing engineering data containing outliers. The AdamW optimizer is a gradient descent optimization algorithm based on adaptive moment estimation. It introduces a weight decay strategy on top of the standard Adam optimizer for updating deep neural network parameters to prevent overfitting and improve the model's robustness in noisy environments. The cosine annealing learning rate scheduling strategy with hot restart refers to dynamically reducing the learning rate according to the cosine function during deep neural network training and restarting the learning rate to its initial value after a preset training period. This helps the model escape local optima and enhances convergence and prediction robustness.

[0132] By acquiring the temperature change rate of the test chamber and the level change information of the logic nodes, and combining the temperature change rate with a dynamic correction coefficient, real-time control of the thermal state of the single machine is achieved, improving the operational reliability and thermal management accuracy in extreme environments, and ensuring that the simulation is executed stably under high load or complex conditions.

[0133] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0134] 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 a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0135] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0136] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0137] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for adaptive control of environmental stress during a thermal vacuum test, characterized in that: Includes the following steps: Step S1: During the thermal vacuum test, monitor the clock cycle deviation and instantaneous ripple voltage of the test chamber, evaluate the single-unit calculation operation status based on the instantaneous ripple voltage, and determine whether to enter the thermal hysteresis analysis mechanism based on the clock cycle deviation. Step S2: In the thermal hysteresis analysis mechanism, the operator execution delay and shell strain intensity of the test chamber are collected, the thermal accumulation index of the test chamber is calculated based on the operator execution delay, and the thermal manifestation characteristics of the test chamber are analyzed based on the shell strain intensity. Step S3: Perform stealth thermal accumulation analysis on the test chamber based on the comprehensive thermal accumulation index and thermal manifestation characteristics, and generate a stealth junction temperature indicator. Select either continuous operation test or implement environmental stress control strategy based on the stealth junction temperature indicator. Step S4: When executing the environmental stress control strategy, retrieve the current temperature change rate of the test chamber, set the control analysis cycle, detect the edge trigger frequency and logic flip density of the test chamber within the control analysis cycle, and correct the current temperature change rate.

2. The adaptive control method for environmental stress during a thermal vacuum test process according to claim 1, characterized in that: In step S1, the clock cycle deviation of the test chamber refers to the deviation information generated by the test chamber side after uniformly sensing the timing behavior of the single machine during the thermal vacuum test, which is used to characterize the timing stability. Instantaneous ripple voltage refers to short-term voltage fluctuations in the power supply chain of the test chamber during the operational simulation.

3. The adaptive control method for environmental stress during a thermal vacuum test process according to claim 2, characterized in that: In step S1, if the instantaneous ripple voltage of the test chamber is greater than or equal to the preset ripple voltage threshold, it is determined that the single-machine simulation operation is in a high-load operation state. If the instantaneous ripple voltage of the test chamber is less than the preset ripple voltage threshold, the single-machine simulation is determined to be in a stable operating state. If the single-machine simulation is in a high-load operation state and the clock cycle deviation of the test chamber is greater than or equal to the preset cycle deviation threshold, then it is determined to enter the thermal hysteresis analysis mechanism. Conversely, if the condition is not met, the analysis mechanism for thermal hysteresis will not be entered.

4. The adaptive control method for environmental stress during a thermal vacuum test process according to claim 1, characterized in that: In step S2, the operator status identification information periodically output by the single machine during the calculation process is obtained through the running status acquisition device; When the received operator status identifier is an operator execution start identifier, record the time when the operator execution start identifier is received; When the received operator status identifier is an execution completion identifier, record the time when the operator execution completion identifier is received; The operator execution delay is obtained by subtracting the time of receiving the operator execution completion flag from the time of receiving the operator execution start flag.

5. The adaptive control method for environmental stress during a thermal vacuum test process according to claim 4, characterized in that: In step S2, a preset acquisition period is set and multiple acquisition times are divided. The strain intensity of the test chamber shell is obtained by strain sensors deployed on the surface of the test chamber shell and integrated into a strain intensity set according to the acquisition sequence. The operator execution delay of the test chamber is standardized to obtain the thermal accumulation index of the test chamber; The strain fluctuation intensity is obtained by subtracting the maximum and minimum values ​​from the set of strain intensities. Select any member in the strain intensity set, subtract it from the next preceding member, and take the absolute value to obtain the strain intensity change of the selected member. The strain intensity changes of each member are summed and divided by the preset acquisition period to obtain the strain intensity change rate. The intensity of strain fluctuation and the rate of change of strain intensity are standardized to obtain the intensity factor and the rate factor. The thermal characteristics of the test chamber are obtained by adding the intensity factor and the velocity factor according to a preset ratio.

6. The adaptive control method for environmental stress during a thermal vacuum test process according to claim 1, characterized in that: In step S3, if the heat accumulation index is less than the preset heat accumulation threshold and the heat manifestation characteristic is less than the preset heat manifestation threshold, then the hidden junction temperature indicator is determined to be safe. If the heat accumulation index is greater than or equal to the preset heat accumulation threshold, and the heat manifestation characteristic is less than the preset heat manifestation threshold, then the hidden junction temperature is identified as high risk. If the heat accumulation index is less than the preset heat accumulation threshold and the heat manifestation characteristic is greater than or equal to the preset heat manifestation threshold, then the hidden junction temperature is identified as an environmental disturbance. If the heat accumulation index is greater than or equal to the preset heat accumulation threshold, and the heat manifestation characteristic is greater than or equal to the preset heat manifestation threshold, then the hidden junction temperature is identified as high-load operation.

7. The adaptive control method for environmental stress during a thermal vacuum test process according to claim 6, characterized in that: In step S3, based on the hidden junction temperature indicator, either a continuous operation test or an environmental stress control strategy is selected; If the hidden junction temperature indicator is marked as safe or indicates environmental disturbance, the test should continue. If the hidden junction temperature is identified as high-risk or high-load operation, then an environmental stress control strategy will be implemented.

8. The adaptive control method for environmental stress during a thermal vacuum test process according to claim 1, characterized in that: In step S4, a fixed acquisition time is set, the temperature of the test chamber is acquired through a platinum resistance temperature sensor, and the temperature data is integrated into a set according to the acquisition sequence. Perform point-by-point difference analysis on the temperature dataset to obtain the temperature change range of each acquisition time relative to the previous acquisition time. The temperature change amplitude at each sampling time is added together to obtain the total temperature change. Divide the total temperature change by the fixed acquisition time to obtain the current temperature change rate of the test chamber; The control and analysis cycle is set, and the level change signal of the logic node of the test chamber is obtained by a high-speed digital signal acquisition device deployed at the output end of the single machine.

9. The adaptive control method for environmental stress during a thermal vacuum test process according to claim 8, characterized in that: In step S4, edge detection is performed on the level change signal of the logic node of the test chamber to identify each event of transitioning from low level to high level or from high level to low level. Count the total number of events that transition from low to high or from high to low. The edge trigger frequency of the test chamber is obtained by dividing the total number of events that transition from low level to high level or from high level to low level by the control analysis period. The number of logic flips in the test chamber is obtained through the on-chip system performance monitoring unit; Divide the number of logic flips in the test chamber by the control analysis cycle to obtain the logic flip density of the test chamber. The edge triggering frequency and logic flip density of the test chamber are comprehensively analyzed by a pre-trained online state estimation model to obtain dynamic correction coefficients. Multiply the dynamic correction factor by the current rate of temperature change to obtain the corrected rate of temperature change.

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