A temperature data processing method and system for cell recovery

Abstract

The application provides a temperature data processing method and system for cell resuscitation. The temperature data processing method for cell resuscitation comprises the following steps: obtaining a current time heating rate according to a surface temperature sequence; judging whether the cryoprotective solution in the cell bag is in a phase transition interval of ice crystal melting according to the surface temperature sequence and the heating rate; when the judgment result is in the phase transition interval, dynamically determining a thermal hysteresis compensation coefficient of the current time according to the change degree of the heating rate relative to the starting time of the phase transition interval; and obtaining the core temperature inside the cell bag according to the thermal hysteresis compensation coefficient, the heating rate and the surface temperature sequence. The application can reduce the estimation error of the core temperature in the phase transition interval, provide more accurate feedback signals for subsequent heating control, and further optimize the temperature control accuracy in the cell resuscitation process.

Description

Technical Field

[0001] This invention relates to the field of biomedical equipment and automated control technology, and in particular to a method and system for temperature data processing for cell resuscitation. Background Technology

[0002] Cell resuscitation is the process of rapidly warming liquid nitrogen-frozen cell samples to physiological temperatures, aiming to thaw the cryopreservation solution while preserving cell viability. Existing dry-heating cell resuscitation equipment heats the container holding the cell bags via a heating tray or chamber, using temperature sensors to monitor the temperature of the heating interface or cell bag surface, which serves as feedback for controlling the heating power. Common temperature detection techniques include using contact temperature sensors (e.g., thermocouples, platinum resistance thermometers) directly attached to the cell bag surface or heating tray, and using non-contact infrared sensors to measure infrared radiation from the cell bag surface. Some devices employ multi-sensor configurations, such as simultaneously using contact and non-contact sensors, to improve the reliability of temperature measurements through data fusion. Regarding control strategies, existing equipment often uses PID control or on / off control, adjusting the output power of the heating element based on a preset target temperature.

[0003] In practical applications, the initial temperature of the cell bag when removed from liquid nitrogen is approximately -196°C. During the heating process to the target temperature, the cryopreservation solution inside the cell bag undergoes three stages: solid-state heating, ice crystal melting phase transition, and liquid-state heating. Due to the thermal resistance of the cell bag wall and the cryopreservation solution itself, there is a heat transfer lag between the surface temperature and the internal core temperature. During the solid-state heating stage, the temperature difference between the surface and core temperatures is relatively stable. However, during the ice crystal melting phase transition, the cryopreservation solution absorbs a large amount of latent heat, causing the core temperature to rise at a lower rate than the surface temperature. Therefore, if heating is controlled solely based on the surface temperature, the following situations may occur: when the surface temperature reaches the preset target temperature, the interior may not be completely melted; if the heating time is extended to ensure internal melting, the surface temperature may exceed the safe limits tolerable by the cells. Therefore, how to accurately estimate the core temperature during the phase transition process to optimize control accuracy is a problem that needs to be solved in this field. Summary of the Invention

[0004] The main objective of this invention is to provide a method and system for processing temperature data for cell resuscitation, aiming to solve the technical problems mentioned in the background art.

[0005] In a first aspect, the present invention proposes a method for processing temperature data for cell resuscitation, comprising the following steps: Acquire temperature data of the cell bag surface and generate a surface temperature sequence based on the temperature data; The heating rate at the current moment is obtained based on the surface temperature sequence; Determine whether the cryopreservation solution in the cell bag is in the phase transition range of ice crystal melting based on the surface temperature sequence and the heating rate; When the determination result is that it is in the phase transition interval, the thermal hysteresis compensation coefficient at the current moment is dynamically determined according to the degree of change of the heating rate relative to the start time of the phase transition interval, wherein the compensation coefficient increases as the heating rate decreases. The core temperature inside the cell bag is obtained based on the thermal hysteresis compensation coefficient, the heating rate, and the surface temperature sequence. The output power of the heating device is controlled according to the core temperature.

[0006] Optionally, the step of determining whether the cryopreservation solution in the cell bag is in the phase transition region of ice crystal melting based on the surface temperature sequence and the heating rate includes: Calculate its sliding average value within a preset first time window based on the heating rate; Determine whether the current heating rate is less than a preset proportion of the sliding average value, and determine whether the surface temperature at the current moment is within a preset phase transition range. If both conditions are met, the phase transition judgment condition is satisfied. When multiple consecutive preset sampling periods meet the phase transition judgment condition, it is confirmed that the current moment is in the phase transition range of ice crystal melting.

[0007] Optionally, it also includes a phase transition prediction step: Determine whether the surface temperature has entered a preset predicted temperature range. If it has, then use the least squares method to fit the historical values ​​of the heating rate of the most recent multiple sampling periods to obtain the expected rate at the current moment. Calculate the rate deviation based on the expected rate and the current heating rate; Determine whether the rate deviation exceeds a preset deviation threshold. If it does, obtain a pre-compensation coefficient based on the preset benchmark compensation coefficient for the solid-state heating range and the rate deviation, and use the pre-compensation coefficient to replace the thermal hysteresis compensation coefficient.

[0008] Optionally, the step of using the least squares method to fit the expected rate at the current time includes: Take the heating rate and its corresponding physical time from the most recent multiple sampling periods, fit a univariate linear regression model, and obtain the fitting parameters; The expected rate at the current moment is obtained based on the fitting parameters and the physical time at the current moment.

[0009] Optionally, the step of dynamically determining the thermal hysteresis compensation coefficient at the current moment based on the degree of change of the heating rate relative to the start time of the phase transition interval includes: The reference rate at the start of entering the phase transition interval is obtained based on the sliding average value when the phase transition judgment condition is met. Based on the reference rate, the current heating rate, the preset baseline compensation coefficient for the solid-state heating range, and the preset adaptive coefficient, the thermal hysteresis compensation coefficient for the current moment is obtained.

[0010] Optionally, the step of obtaining the core temperature inside the cell bag based on the thermal hysteresis compensation coefficient, the heating rate, and the surface temperature sequence includes: The instantaneous compensation temperature difference is obtained based on the thermal hysteresis compensation coefficient and the heating rate; The cumulative integral value is obtained by performing a time-based integral on the positive portion of the rate deviation. The cumulative thermal hysteresis compensation term is obtained based on the cumulative integral value, the reference rate, the preset cumulative compensation coefficient, and the saturation time constant; The core temperature inside the cell bag is obtained based on the surface temperature, the instantaneous compensated temperature difference, and the cumulative thermal hysteresis compensation term.

[0011] Optionally, the step of controlling the output power of the heating device according to the core temperature includes: Calculate the temperature difference based on the core temperature and the preset target temperature; When the core temperature is lower than the difference between the preset target temperature and the preset rapid heating threshold, the heating device is controlled to output full power. When the core temperature is greater than or equal to the difference between the preset target temperature and the preset rapid heating threshold, the system switches to PID control mode, using the core temperature as feedback, and adjusts the output power of the heating device according to the discrete PID formula.

[0012] Secondly, the present invention also provides a temperature data processing system for cell resuscitation, the system comprising: The data acquisition module is used to acquire temperature data of the cell bag surface and generate a surface temperature sequence based on the temperature data. A temperature calculation module is used to obtain the current temperature rise rate based on the surface temperature sequence. A phase transition determination module is used to determine whether the cryopreservation solution in the cell bag is in the phase transition range of ice crystal melting based on the surface temperature sequence and the heating rate. The compensation coefficient determination module is used to dynamically determine the thermal hysteresis compensation coefficient at the current moment based on the degree of change of the heating rate relative to the start time of the phase transition when the judgment result is that it is in the phase transition interval, wherein the compensation coefficient increases as the heating rate decreases. The core temperature calculation module is used to obtain the core temperature inside the cell bag based on the thermal hysteresis compensation coefficient, the heating rate, and the surface temperature sequence. The control output module is used to control the output power of the heating device according to the core temperature.

[0013] Thirdly, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in the first aspect.

[0014] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in the first aspect.

[0015] Compared with related technologies, the temperature data processing method and system for cell resuscitation provided in this application have at least the following technical advantages: This invention utilizes a dynamically determined thermal hysteresis compensation coefficient to adjust the compensation amount in real time according to the degree of change of the heating rate relative to the start time of the phase transition interval. This allows for adaptive correction of the surface temperature during the phase transition process, resulting in a core temperature estimate that is closer to the actual situation. Consequently, the estimation error of the core temperature can be reduced within the phase transition interval, providing a more accurate feedback signal for subsequent heating control and thus optimizing the accuracy of temperature control during cell resuscitation.

[0016] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating a temperature data processing method for cell resuscitation according to an exemplary embodiment.

[0018] Figure 2 This is a flowchart illustrating step S3 according to an exemplary embodiment.

[0019] Figure 3 This is a flowchart illustrating step S4 according to an exemplary embodiment.

[0020] Figure 4 This is a flowchart illustrating step S6 according to an exemplary embodiment.

[0021] Figure 5 This is a block diagram illustrating a temperature data processing system for cell resuscitation according to another exemplary embodiment. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0023] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0024] Example 1 Embodiment 1 of this application provides a method for processing temperature data for cell resuscitation. Figure 1 This is a flowchart illustrating a temperature data processing method for cell resuscitation according to an exemplary embodiment. (See attached diagram.) Figure 1 The method includes: S1, acquire temperature data of the cell bag surface, and generate a surface temperature sequence based on the temperature data; S2, Obtain the heating rate at the current moment based on the surface temperature sequence: ; In the formula, Indicates the current time The heating rate (unit: °C / s). Indicates the current time The surface temperature (obtained by collecting raw temperature values ​​from multiple sensors, followed by extreme value removal averaging filtering and multi-source weighted fusion, and then moving average filtering). Indicates the sampling period (in seconds). Indicates two sampling periods Previous surface temperature; S3, determine whether the cryopreservation solution in the cell bag is in the phase transition range of ice crystal melting based on the surface temperature sequence and the heating rate; S4, when the judgment result is that it is in the phase transition interval, the thermal hysteresis compensation coefficient at the current moment is dynamically determined according to the degree of change of the heating rate relative to the start time of the phase transition interval, wherein the compensation coefficient increases as the heating rate decreases; S5, obtain the core temperature inside the cell bag based on the thermal hysteresis compensation coefficient, the heating rate, and the surface temperature sequence: ; In the formula, Indicates the core temperature. Indicates the current time Surface temperature, This represents the thermal hysteresis compensation coefficient. Indicates the current time The rate of heating; S6, control the output power of the heating device according to the core temperature.

[0025] As described in steps S1-S6 above, during cell resuscitation, there is a heat transfer lag between the core temperature and the measured surface temperature inside the cell bag, especially during the ice crystal melting stage. Due to the absorption of latent heat of phase change, the core temperature rise rate is significantly lower than the surface temperature rise rate, causing the surface temperature-based control strategy to fail to accurately reflect the true internal state. The fixed-coefficient linear compensation method used in existing technologies has a large error within the phase change range, making it difficult to meet the temperature control accuracy requirements of cell resuscitation. Therefore, this invention solves the above-mentioned technical problem by using a temperature data processing method that can dynamically adjust the compensation coefficient according to the heating rate to improve the accuracy of core temperature estimation. Specifically, this invention acquires temperature data of the cell bag surface and generates a surface temperature sequence based on this data. This surface temperature sequence is obtained by performing extreme value removal averaging filtering and multi-source weighted fusion on the raw data from multiple sensors, followed by moving average filtering. Its function is to provide a smooth and reliable surface temperature signal as the basis for subsequent calculations. Next, the heating rate at the current moment is calculated based on this surface temperature sequence, specifically using the central difference method, obtained by dividing the difference between the current moment and the surface temperature two sampling periods ago by twice the sampling period. Next, based on the surface temperature sequence and heating rate, it is determined whether the cryopreservation solution inside the cell bag is in the phase transition zone of ice crystal melting. This determination step is a prerequisite for subsequent dynamic adjustment of the compensation coefficient. When the determination result indicates that it is in the phase transition zone, the thermal hysteresis compensation coefficient at the current moment is dynamically determined based on the degree of change of the heating rate relative to the start time of the phase transition zone. This compensation coefficient increases as the heating rate decreases. The core of this step is to enable the compensation coefficient to automatically adjust with the changes in the phase transition process. Then, the core temperature inside the cell bag is obtained based on the thermal hysteresis compensation coefficient, heating rate, and surface temperature sequence. The hysteresis temperature difference between the surface temperature and the core temperature is corrected by multiplying the compensation coefficient by the heating rate. Finally, the output power of the heating device is controlled according to the core temperature to heat the cell bag according to the preset target temperature curve.

[0026] Through the above steps, this invention utilizes a dynamically determined thermal hysteresis compensation coefficient to adjust the compensation amount in real time according to the degree of change in the heating rate relative to the start time of the phase transition interval. This allows for adaptive correction of the surface temperature during the phase transition process, resulting in a core temperature estimate that more closely approximates the actual situation. Compared to existing technologies using a fixed compensation coefficient, this method can reduce the estimation error of the core temperature within the phase transition interval, providing a more accurate feedback signal for subsequent heating control and thus improving the temperature control effect during cell resuscitation.

[0027] In one embodiment of the present invention, Figure 2 This is a flowchart illustrating step S3 according to an exemplary embodiment. (Refer to the attached diagram.) Figure 2The step of determining whether the cryopreservation solution in the cell bag is in the phase transition region of ice crystal melting based on the surface temperature sequence and the heating rate includes: S31, calculate the sliding average value within the first time window based on the heating rate: ; In the formula, Indicates the current time The moving average of the heating rate (in °C / s, used to determine whether the rate has significantly decreased). This indicates the number of sampling points included in the first time window (used to determine the smoothness of the moving average and the response sensitivity). Indicates the first in the window Historical sampling points, ranging from 0 to... , Indicates the sampling period. Indicates the past number The heating rate at each sampling time; S32, determine whether the current heating rate is less than the product of the sliding average value and the preset proportional threshold: ; In the formula, Indicates the current time The rate of heating This indicates the preset ratio threshold. Indicates the current time The moving average of the heating rate; And determine whether the surface temperature at the current moment is within the preset phase transition range. If the above two conditions are met, then the phase transition judgment condition is met. S33, when the phase transition judgment condition is met for multiple consecutive sampling cycles, it is confirmed that the current moment is in the phase transition interval of ice crystal melting.

[0028] As described in steps S31-S33 above, this invention employs a judgment strategy based on a combination of relative decay of the heating rate and temperature range constraints to determine whether the cryopreservation solution is in the ice crystal melting phase transition range during cell resuscitation. In actual cell resuscitation operations, there is a heat transfer lag between the core temperature inside the cell bag and the measured surface temperature, especially during the ice crystal melting stage. Due to the absorption of latent heat of phase transition, the core temperature rise rate is significantly lower than the surface temperature rise rate. If the start and end times of the phase transition range cannot be accurately identified, subsequent adjustments to the dynamic compensation coefficient lack a reliable trigger, leading to core temperature estimation errors and consequently affecting resuscitation quality. Therefore, to solve the above problem, this invention calculates the moving average of the heating rate as a dynamic benchmark, compares the current heating rate with this moving average to detect whether the heating rate has decreased, and requires the surface temperature to be within a preset phase transition temperature range. The phase transition is confirmed to have begun when the conditions are met for multiple consecutive sampling cycles, achieving online, real-time, and accurate determination of the phase transition range.

[0029] Specifically, the moving average value of the heating rate within a first time window is first calculated based on the heating rate. This step, calculating the moving average of the heating rate, is a conventional filtering technique in signal processing. Its function is to filter out high-frequency noise in the heating rate signal and extract low-frequency components reflecting the heat transfer trend. This moving average value serves as a dynamic benchmark for subsequent comparisons, making the judgment independent of a fixed absolute value of the heating rate, thus providing adaptability to different heating rate levels. For example, the moving average value is higher when the heating rate is faster in the solid-state heating region; and lower when the heating rate slows down in the phase transition region. This moving average value provides a reference line that varies with actual operating conditions, avoiding misjudgments that might occur when using a fixed threshold.

[0030] Secondly, it is simultaneously determined whether the current heating rate is less than the product of the sliding average and a preset proportional threshold, and whether the current surface temperature is within a preset phase transition temperature range. The phase transition judgment condition is only satisfied when both conditions are met. The preset proportional threshold can be obtained by conducting multiple recovery experiments using a standard test bag with embedded thermocouples. During the normal heating phase, the fluctuation range of the heating rate is recorded, and during the phase transition phase, the decrease in the heating rate is recorded. The value that can distinguish between the two states is taken as the threshold. For example, experiments have shown that a threshold between 0.4 and 0.6 has a good distinguishing effect; in this embodiment, 0.5 is used. This condition detects the degree of decrease in the current heating rate relative to the recent sliding average level. The basis for this is that when ice crystals begin to melt, latent heat absorption causes a continuous decrease in the heating rate, and this decrease usually exceeds the fluctuation range during the normal heating process. This condition does not depend on the absolute value of the heating rate. Therefore, regardless of changes in cell bag thickness, cryopreservation solution formulation, or heating power, as long as a phase transition occurs, the relative decrease in the heating rate remains stable within a certain range, thus ensuring the universality of the judgment method. Simultaneously, the temperature range condition requires the current surface temperature to be within a preset phase transition temperature range. This preset phase transition temperature range can be determined based on the physical properties of the cell cryopreservation solution. Specifically, the phase transition onset and end temperatures of the cryopreservation solution are determined by differential scanning calorimetry. For example, for a culture medium containing 10% dimethyl sulfoxide, its freezing point is approximately -20°C, and its complete thawing temperature is approximately 0°C. Therefore, the preset phase transition temperature range can be set to -20°C to 0°C. This condition ensures that phase transition recognition is only initiated within the temperature range where the cryopreservation solution may actually undergo a phase transition, thereby eliminating the possibility of falsely triggering phase transition recognition due to accidental fluctuations in the heating rate in the low-temperature solid region or high-temperature liquid region. These two conditions give phase transition recognition both physical necessity (temperature range) and dynamic characteristics (heating rate decay). Through this mechanism, even if the heating rate decay condition is accidentally met, the system will not trigger phase transition recognition as long as the surface temperature is not within the preset phase transition temperature range; conversely, even if the surface temperature enters the preset phase transition temperature range, if the heating rate does not decay, it indicates that the phase transition has not yet started or has already ended, and recognition will also not be triggered. This double verification helps improve the accuracy of the judgment.

[0031] Secondly, the phase transition judgment condition mentioned above must be met for multiple consecutive sampling periods to confirm that the current moment is within the phase transition range of ice crystal melting. This step utilizes the continuous characteristic of the phase transition process, that is, ice crystal melting is a process lasting several seconds to tens of seconds, rather than an instantaneous event. The number of consecutive sampling periods can be set according to the sampling period and the desired confirmation time. For example, if the sampling period is 0.1 seconds, setting the condition to be met for 3 consecutive sampling periods is equivalent to requiring the condition to be met continuously for 0.3 seconds. This value can be determined as follows: during normal heating without phase transition, measure the longest duration of random fluctuations in the heating rate caused by noise or heating power adjustment, and set the number of consecutive confirmations to be greater than the number of sampling periods corresponding to this longest duration. For example, experiments show that random fluctuations usually do not exceed 0.2 seconds, so taking 3 consecutive sampling periods (0.3 seconds) can effectively filter out such fluctuations. By using a confirmation window in the time dimension, the probability of false triggers caused by single noise or instantaneous disturbances is reduced. At the same time, since the duration of this confirmation window is much shorter than the total duration of the phase transition process, it will not have a substantial impact on the real-time performance of the identification.

[0032] It should be noted that when it is confirmed that the current moment is within the phase transition range of ice crystal melting, the current heating rate is recorded as a reference rate. This reference rate characterizes the heat transfer state at the onset of the phase transition, i.e., the heating rate before it is significantly affected by latent heat absorption. Recording this reference rate is itself a conventional data storage operation, but its function in this invention is to provide a benchmark parameter for the subsequent calculation of the dynamic compensation coefficient. By subsequently comparing the ratio of the current heating rate to this reference rate, the proportion of remaining ice crystals can be quantitatively estimated. This technical feature allows the adjustment of the compensation coefficient to be based on the actual heating characteristics of the current recovery batch, rather than relying on fixed empirical parameters, thereby improving the adaptability of subsequent core temperature estimation.

[0033] In one embodiment of the present invention, a phase transition prediction step is further included: S301, determine whether the surface temperature has entered the preset predicted temperature range. If it has, then use the least squares method to fit the historical values ​​of the heating rate of the most recent multiple sampling cycles to obtain the expected rate at the current moment. S302, calculate the rate deviation based on the expected rate and the current heating rate: ; In the formula, Indicates the rate deviation (reflecting the percentage decrease in rate caused by ice crystal melting). Indicates the expected rate. Indicates the current time The rate of heating This represents a preset small positive number, and its unit is ℃ / s; S303, determine whether the rate deviation exceeds a preset deviation threshold. If it does, obtain a pre-compensation coefficient based on the preset benchmark compensation coefficient for the solid-state heating range and the rate deviation, and use the pre-compensation coefficient to replace the thermal hysteresis compensation coefficient. The pre-compensation coefficient is calculated using the following formula: ; In the formula, This represents the pre-compensation coefficient (in seconds, used to increase the compensation amount in advance). This represents the preset reference compensation coefficient for the solid-state heating range (in seconds, obtained through factory calibration, acquired via linear regression using a standard test bag with pre-embedded thermocouples, representing the reference thermal hysteresis time constant of the solid (unmelted) cell bag, reflecting the temperature difference ratio between the surface and the core during normal heating). This represents the pre-compensation gain coefficient (in seconds, calibrated by pre-shipment testing, used to control the degree of influence of rate deviation on the pre-compensation coefficient). Indicates the rate deviation.

[0034] As described in steps S301-S303 above, during cell resuscitation, there is a brief time window between the start of ice crystal melting and the detection of a significant decrease in the heating rate. Within this window, latent heat absorption has begun, but the rate decline has not yet reached the level required by the aforementioned phase transition judgment condition (i.e., the current heating rate is less than the product of the moving average and a preset proportional threshold). Therefore, this invention adds a phase transition prediction step before determining the phase transition range. Its core is: when the surface temperature enters a relatively wide prediction temperature range, the expected rate at the current moment is extrapolated using the historical trend of the heating rate, and the deviation between the actual rate and the expected rate is calculated. If the deviation exceeds a preset threshold, a pre-compensation state is triggered in advance, and a pre-compensation coefficient is used instead of the conventional thermal hysteresis compensation coefficient.

[0035] First, it is determined whether the surface temperature has entered a preset predictive temperature range. This predictive temperature range differs from the preset phase change temperature range used for phase change confirmation in the previous steps. The predictive temperature range is wider, for example, it can be set to -25℃ to 5℃, while the latter's phase change temperature range is -20℃ to 0℃. The width of the predictive temperature range is based on the following considerations: since the phase change initiation temperature of different batches of cryopreservation solution may vary, and temperature sensor measurements may have errors, setting a wider temperature range ensures that the predictive mechanism is activated before the actual phase change occurs, thus initiating monitoring in advance. The endpoints of this preset predictive temperature range can be obtained by performing differential scanning calorimetry (DSC) tests on the cryopreservation solution used, extending a certain margin (e.g., 5℃ above and below the phase change initiation temperature) as the predictive temperature range. The purpose of this technical feature is to provide a trigger condition for the predictive mechanism, avoiding unnecessary calculations in regions far below the phase change temperature.

[0036] Once the surface temperature enters the preset predicted temperature range, the expected rate for the current moment is obtained by fitting historical heating rate values ​​from multiple recent sampling periods using the least squares method. The core of this step lies in using a univariate linear regression model to extract the trend of change from historical heating rate data and extrapolating it to the current moment, thereby obtaining an expected heating rate under the assumption of no phase transition interference. This expected rate reflects the value that the heating rate should reach if it continues to change according to the existing trend. The least squares fitting method is a conventional method in statistics, and its specific application in this invention is to provide a benchmark for subsequent deviation calculations by quantifying the trend of rate change. The beneficial effect of this technical feature is that the calculation of the expected rate does not rely on fixed empirical values, but is based on the actual rate change history of the current recovery process, thus exhibiting adaptability to different heating conditions.

[0037] The rate deviation is calculated based on the expected rate and the current heating rate. In the calculation formula, the numerator of the formula... The deviation rate represents the difference between the expected and actual rates, reflecting the degree to which the current actual heating rate lags behind the expected trend. The preset small positive value in the denominator can be set to 0.01℃ / s, which is less than the minimum typical heating rate (e.g., 0.05℃ / s), and therefore will not have a substantial impact on the calculation of the deviation. The rate deviation is a dimensionless quantity, its physical meaning being the relative lag ratio of the actual rate to the expected rate. When the actual rate equals the expected rate, it approaches zero; when the actual rate is significantly lower than the expected rate, it approaches a positive value. Quantifying the degree of deviation through this relative ratio rather than an absolute difference makes the deviation comparable across different rate levels. For example, in high-speed and low-speed heating stages, the same absolute rate difference may correspond to different degrees of phase transition severity, while the relative deviation eliminates this dimensional effect.

[0038] Next, determine whether the rate deviation exceeds a preset deviation threshold. This preset deviation threshold can be obtained by conducting multiple recovery experiments using a standard test bag with embedded thermocouples. Record the rate deviation fluctuation range during normal heating before the phase change begins (i.e., before latent heat absorption occurs), and simultaneously record the rate deviation curve at the initial stage of the phase change. Take the value that distinguishes the two states and leaves an appropriate margin as the threshold. For example, experiments show that the deviation is usually less than 0.2 under normal fluctuations, while it can rapidly rise to above 0.3 at the initial stage of the phase change. Therefore, the preset deviation threshold can be set to 0.3. When the rate deviation exceeds this preset deviation threshold, it indicates that the actual heating rate has significantly lagged behind the expected trend, meaning that the phase change may have already begun or is about to begin.

[0039] When the rate deviation exceeds a preset deviation threshold, a pre-compensation state is triggered. A pre-compensation coefficient is obtained based on the preset baseline compensation coefficient for the solid-state heating range and the rate deviation. In this pre-compensation state, this pre-compensation coefficient replaces the thermal hysteresis compensation coefficient for core temperature calculation. The preset baseline compensation coefficient for the solid-state heating range is obtained by using a standard test bag with embedded thermocouples. A recovery experiment is conducted in the solid-state heating range (e.g., surface temperature below -20℃), recording the surface temperature and the actual core temperature. The slope obtained through linear regression is the preset baseline compensation coefficient. The pre-compensation gain coefficient is obtained by linearly fitting the actual required compensation coefficient increment (i.e., the difference between the pre-compensation coefficient and the preset baseline compensation coefficient) to the corresponding rate deviation in the experimental data at the initial stage of the phase transition. The slope obtained is the pre-compensation gain coefficient, typically 0.1 seconds. This pre-compensation coefficient increases linearly with the rate deviation. Its significance lies in the fact that a larger deviation indicates a more pronounced phase transition trend, requiring a larger amount of compensation in advance. When the rate deviation exceeds the preset deviation threshold, a pre-compensation coefficient is used instead of the conventional compensation coefficient. This allows for increased compensation before the phase transition is formally confirmed, thereby reducing the error in core temperature estimation during the initial phase transition.

[0040] In one embodiment of the present invention, the step of using the least squares method to fit and obtain the expected rate at the current time includes: S3011: Take the heating rate and its corresponding physical time from the most recent multiple sampling periods, fit a univariate linear regression model, and obtain the fitting parameters. Fitting parameters include and Calculation formula: ; ; In the formula, The slope parameter represents the linear regression (unit: ℃ / s², indicating the rate of change). This indicates the number of sampling points included in the least squares fitting window (which determines the stability and response speed of the prediction). Indicates the first Physical time of each sampling point Indicates all within the window The average value, Indicates the first The heating rate at each sampling point Indicates all within the window The average value, The intercept parameter represents the linear regression (unit: °C / s, representing the expected rate at time zero (or reference time)). S3012, Obtain the expected rate at the current moment based on the fitted parameters and the physical time at the current moment: ; In the formula, This represents the expected rate (the rate that should exist at the current moment, assuming no phase transition interference). Represents the intercept parameter. Represents the slope parameter. Indicates the current time (physical time).

[0041] As described in steps S3011-S3012 above, when the surface temperature enters the preset predicted temperature range, the present invention predicts the expected rate at the current moment based on the historical values ​​of the heating rate of the most recent multiple sampling cycles. This expected rate is used for the calculation of the subsequent rate deviation.

[0042] First, the heating rate values ​​and their corresponding physical times from the most recent sampling periods are taken, and a univariate linear regression model is fitted. Specifically, the heating rate values ​​and their corresponding physical times from the most recent M sampling periods are taken, and a univariate linear regression model is used to describe the trend of the heating rate over time. The reason for choosing a univariate linear regression model is that in the solid-state heating stage before the phase transition, the heating power is usually constant (rapid heating mode) or changes slowly, and the heating rate changes approximately linearly with time. Therefore, the linear model can fit the rate trend of this stage well. This model belongs to the conventional regression analysis method, and its specific application in this invention is to provide a physically meaningful expected benchmark for the calculation of rate deviation. Second, the fitting parameters are obtained by minimizing the sum of squared residuals. The selection method of the number of sampling points M in the window is as follows: considering both the stability of the prediction and the response speed, if M is too small, it will be sensitive to noise; if it is too large, the response will be lagging. It can be determined experimentally. For example, under a typical heating rate, taking M=5 corresponds to a 0.5-second time window, which can smooth out noise without introducing significant delay. This value can be adjusted according to the sampling period. If the sampling period is 0.1 seconds, then M=5 corresponds to a historical data window of 0.5 seconds. Then, based on the above fitting parameters and the current physical time, the expected rate at the current moment is obtained. The calculation formula extrapolates the fitted linear model to the current moment, yielding the expected heating rate at the current time. The significance of the expected rate is: assuming the heating rate continues to evolve according to the trend of the past M sampling periods (i.e., no phase transition interference), the heating rate that should be observed at the current moment.

[0043] The preset parameters involved in the above steps can be obtained through calibration experiments on standard test bags. Specifically, a test bag with pre-embedded thermocouples is used to perform multiple standard recovery procedures to collect surface temperature and true core temperature data. The parameter combination that minimizes the core temperature estimation error is then selected using a parameter scanning method. Those skilled in the art, based on the description in this specification and combined with conventional experimental design and parameter optimization methods, can determine the parameter values ​​suitable for specific implementation equipment without any inventive effort.

[0044] In one embodiment of the present invention, Figure 3 This is a flowchart illustrating step S4 according to an exemplary embodiment. (Refer to the attached document.) Figure 3 The step of dynamically determining the thermal hysteresis compensation coefficient at the current moment based on the degree of change of the heating rate relative to the start time of the phase transition interval includes: S41, obtain the reference rate at the start of entering the phase transition interval based on the sliding average value when the phase transition judgment condition is met; S42, the thermal hysteresis compensation coefficient at the current moment is obtained based on the reference rate, the current heating rate, the preset benchmark compensation coefficient for the solid-state heating range, and the preset adaptive coefficient. The calculation formula is as follows: ; In the formula, Represents the dynamically determined current moment. The thermal hysteresis compensation coefficient (in seconds, reflecting the dynamic proportional relationship between surface temperature and core temperature). This represents the preset adaptive coefficient (in seconds, obtained from factory calibration, reflecting the increase in thermal hysteresis caused by ice crystal melting). This represents the preset baseline compensation coefficient for the solid-state heating range. Indicates the current time The rate of heating The reference rate (unit: °C / s) represents the initial moment of entering the phase transition region. It serves as a benchmark for determining the proportion of remaining ice crystals and is recorded as the sliding average rate "when it is confirmed that the phase transition region has been entered" as the reference rate. As described in steps S41-S42 above, after confirming that the current moment is in the phase transition range of ice crystal melting, the present invention adjusts the thermal hysteresis compensation coefficient in real time according to the degree of change of the heating rate relative to the starting moment of the phase transition range, so as to reflect the change of the degree of thermal hysteresis during the phase transition.

[0045] First, the reference rate at the start of the phase transition interval is obtained based on the moving average value when the phase transition judgment condition is met. Specifically, when the phase transition judgment condition is met for multiple consecutive sampling periods (i.e., the current heating rate is less than the product of the moving average value and a preset proportional threshold, and the current surface temperature is within a preset phase transition temperature range), the current moment is confirmed to be within the phase transition interval, and the moving average value of the heating rate at that moment is recorded as the reference rate, with the unit of the reference rate being ℃ / s. The moving average value is chosen because it has undergone wave filtering and has better stability, enabling a more reliable characterization of the heat transfer state at the start of the phase transition. The physical meaning of this reference rate is the expected heating rate level under the current heating conditions when the phase transition has just begun and latent heat absorption has not yet significantly affected the heating rate.

[0046] Then, based on the aforementioned reference rate, the current heating rate, the preset baseline compensation coefficient for the solid-state heating range, and the preset adaptive coefficient, the thermal hysteresis compensation coefficient for the current moment is calculated. The calculation formula is as follows: This term reflects the percentage decrease in the current heating rate relative to the reference rate, and its value ranges from 0 to 1 (when...). When it drops to zero, it takes the value 1. equal (Take 0 at this time). This term represents an estimated value of the remaining ice crystal proportion: when the phase transition has just begun. near When this term approaches 0, the compensation coefficient is close to the preset baseline compensation coefficient for the solid-state heating range. As the phase transition proceeds, the ice crystals gradually melt, the heating rate decreases, this term increases, and the compensation coefficient increases linearly. When the phase transition is nearing its end, the heating rate drops to its minimum, and the compensation coefficient approaches [the value of the original term]. This linear relationship is an engineering approximation of the actual nonlinear thermal hysteresis characteristics. By calibrating the adaptive coefficients, it can achieve a good fit within the actual working range. The preset benchmark compensation coefficient for the solid-state heating range is obtained as follows: using a standard test bag with a pre-embedded thermocouple, a recovery experiment is conducted in the solid-state heating range (e.g., surface temperature below -20℃, where the cryopreservation liquid is completely solid and there is no latent heat absorption from phase change). Simultaneously, the surface temperature and the true core temperature are recorded. The difference between the true core temperature and the surface temperature at each moment is calculated, and this difference, along with the corresponding heating rate, is used as a set of data points. A univariate linear regression is performed on these data points, and the slope obtained from the regression is the benchmark compensation coefficient. This regression process is repeated on multiple standard test bags, and the average value is taken as the factory calibration value. The typical value is approximately 0.08 seconds. The preset adaptive coefficient is obtained as follows: Within the phase transition range (e.g., surface temperature between -20℃ and 0℃), a recovery experiment is conducted using a standard test bag with embedded thermocouples. Within the phase transition range, the first calibration method is as follows: Surface temperature, heating rate, reference rate, and the actual core temperature measured by the embedded thermocouples are collected at multiple time points. For each time point, the theoretical compensation value is first calculated using a linear compensation model based on the difference between the actual core temperature and the surface temperature, and the heating rate. The residual between the actual measured value and the theoretical value is then obtained. Next, the ratio of the heating rate to the reference rate at that time is calculated, and a value is obtained by subtracting this ratio. This value is then multiplied by the current heating rate to form a feature variable. A linear regression is performed between this residual and the feature variable, and the slope of the fitted line is the adaptive coefficient. The second simplified calibration method is as follows: Multiple time points are selected within the phase transition range. For each time point, the difference between the actual core temperature and the surface temperature is calculated and divided by the current heating rate to obtain the total compensation coefficient actually required at that time. Subtract the preset baseline compensation coefficient for the solid-state heating range from the total compensation coefficient to obtain a difference. Simultaneously, calculate and subtract the ratio of the current heating rate to the reference rate to obtain a dimensionless quantity. Perform a linear regression between this difference and the dimensionless quantity; the slope of the fitted line is the adaptive coefficient. A typical value for this adaptive coefficient is approximately 0.2 seconds.

[0047] The aforementioned thermal hysteresis compensation coefficient increases with decreasing heating rate. This is significant because, as the phase transition proceeds, the remaining ice crystals decrease, but latent heat absorption continues, resulting in a large equivalent heat capacity. Therefore, the temperature difference between the surface and core temperatures remains significant, requiring a larger compensation coefficient. Through this scheme, the thermal hysteresis compensation coefficient of this invention can be adjusted in real time according to the phase transition process, allowing the core temperature estimation to follow the changes in the degree of thermal hysteresis during the phase transition. Compared with existing technologies using a fixed compensation coefficient, this method can reduce the estimation error of the core temperature within the phase transition range. Furthermore, the formula uses a reference rate as a normalization factor, making the adjustment of the compensation coefficient adaptive to different heating rate levels: even if the heating rates of the two recovery cycles are different, as long as the relative decrease ratio is the same, the increment of the compensation coefficient is also the same, thus ensuring a consistent compensation effect.

[0048] In one embodiment of the present invention, the step of obtaining the core temperature inside the cell bag based on the thermal hysteresis compensation coefficient, the heating rate, and the surface temperature sequence includes: S51, Obtain the instantaneous compensation temperature difference based on the thermal hysteresis compensation coefficient and the heating rate: ; In the formula, This indicates instantaneous compensation for temperature difference (caused by the current heat flow, i.e., the temperature difference between the surface and the core due to thermal resistance). Indicates the current time The thermal hysteresis compensation coefficient, Indicates the current time The rate of heating; S52, perform time-based integration based on the positive portion of the rate deviation to obtain the cumulative integral value: ; In the formula, The cumulative integral value representing the positive deviation (in seconds, representing the total latent heat (relative amount) absorbed by the melting of ice crystals) Indicates the integral variable Rate deviation at time (corresponding) This is to distinguish the maximum points. (Current moment) This indicates the starting time of entering the phase transition region. Indicates the current moment. Indicates time The differential, This means that only the positive deviation is taken, and the negative deviation (the case where the rate is higher than the prediction) is ignored, because only when the rate slows down does it correspond to the absorption of latent heat. S53, the cumulative thermal hysteresis compensation term is obtained based on the cumulative integral value, the reference rate, the preset cumulative compensation coefficient, and the saturation time constant. The calculation formula is as follows: ; In the formula, This represents the cumulative thermal hysteresis compensation term (in °C, the additional temperature difference caused by the absorption of cumulative latent heat, used to compensate for the insufficiency of instantaneous compensation during the phase transition plateau period). This represents the preset cumulative compensation coefficient (dimensionless). This represents the cumulative integral value. Indicates the reference rate. Represents the natural constant. This represents the saturation time constant (in seconds, preset by the system). The exponential part is dimensionless; S54, based on the surface temperature, the instantaneous compensated temperature difference, and the cumulative thermal hysteresis compensation term, obtain the core temperature inside the cell bag: ; In the formula, This indicates the core temperature (the actual temperature of the liquid inside the cell bag, which serves as the basis for control decisions). Indicates the previous time. Surface temperature, Indicates instantaneous compensation for temperature difference. This represents the cumulative thermal hysteresis compensation term; S55, when exiting the phase transition interval, the cumulative integral value is reset to zero, and the cumulative thermal hysteresis compensation term is linearly decayed to zero.

[0049] As described in steps S51-S55 above, in this embodiment, based on the core temperature in step S5, a cumulative thermal hysteresis compensation term is further used to address the problem of insufficient instantaneous compensation during the phase transition plateau. During cell resuscitation, when a large amount of ice crystals melt, the surface temperature may experience a brief plateau, i.e., the heating rate approaches zero. However, during the phase transition plateau, the actual temperature difference between the surface and the core still exists. Therefore, this invention introduces a compensation term reflecting the cumulative latent heat absorption effect, which works in conjunction with the instantaneous compensation term to compensate for the estimation bias during this stage.

[0050] First, the instantaneous compensated temperature difference is obtained based on the thermal hysteresis compensation coefficient and the heating rate. This instantaneous compensated temperature difference reflects the temperature difference between the surface and the core caused by the current heat flux, based on the fact that during heat conduction, the temperature gradient is proportional to the heat flux density, and the heat flux density is related to the heating rate.

[0051] Secondly, the positive portion of the rate deviation is integrated over time to obtain the cumulative integral value. This cumulative integral value represents the cumulative lag between the actual heating rate and the expected rate from the start of the phase transition to the current moment. Since only positive deviations are accumulated, this integral value increases only when the actual rate is lower than the expected rate, and remains unchanged when the actual rate is higher than the expected rate. This aligns with the physical fact that latent heat absorption during the phase transition causes a unidirectional rate lag. The rate deviation itself reflects the instantaneous relative lag ratio; after integration, it reflects the cumulative effect of the lag over its duration, equivalent to a relative estimate of the total latent heat absorption. It should be noted that since the phase transition interval is finite in time (typically lasting from several seconds to tens of seconds), and the cumulative integral value is reset when the surface temperature exceeds the phase transition temperature range (e.g., above 0°C), the cumulative integral value will not grow indefinitely; its maximum value is limited by the duration of the phase transition interval. The calculation of this cumulative integral value can be implemented discretely: within each sampling period, the rate deviation at the current moment is calculated; if the rate deviation is greater than 0, cumulative integration is performed; if the rate deviation is less than or equal to 0, the cumulative integral value remains unchanged. This method is a standard implementation of integration in digital systems and requires no further explanation.

[0052] Next, the cumulative thermal hysteresis compensation term is obtained based on the aforementioned cumulative integral value, reference rate, preset cumulative compensation coefficient, and saturation time constant. It should be noted that, due to the finite duration of the phase transition interval, the cumulative thermal hysteresis compensation term has an upper limit; it will not grow indefinitely in practical applications, and its maximum value occurs at the end of the phase transition. The preset cumulative compensation coefficient and saturation time constant are obtained as follows: a recovery experiment is conducted using a standard test bag with pre-embedded thermocouples. Within the phase transition interval, surface temperature, true core temperature, instantaneous compensation temperature difference, cumulative integral value, and reference rate are collected at multiple moments. For each moment, the difference between the true core temperature and the surface temperature is first calculated, and then the instantaneous compensation temperature difference at that moment is subtracted to obtain a residual value. Simultaneously, based on the cumulative integral value and the preset saturation time constant at that moment, a characteristic quantity is calculated. This characteristic quantity is equal to the product of the cumulative integral value and the reference rate, multiplied by an exponential function value minus the base of the natural constant and the exponent of the negative of the ratio of the cumulative integral value to the saturation time constant. The residual values ​​and characteristic quantities are fitted using the least squares method. The resulting parameters are the cumulative compensation coefficient and the saturation time constant. A typical value for the cumulative compensation coefficient is 0.05, dimensionless; a typical value for the saturation time constant is 3 seconds. This saturation time constant reflects the characteristic time for the cumulative compensation term to transition from quadratic growth to linear growth. Its value can be determined experimentally and is usually related to the rate of change of the rate deviation during the phase transition. The significance of this cumulative thermal hysteresis compensation term is that as the phase transition continues, latent heat absorption accumulates, leading to a gradual increase in the temperature difference between the surface and the core. Since the cumulative integral value increases with the duration of the phase transition, the cumulative thermal hysteresis compensation term also increases, thus providing additional compensation during the phase transition plateau period when instantaneous compensation is insufficient. The exponential factor makes the growth rate of the compensation term faster in the early stages of the phase transition and gradually tends to be linear in the middle and later stages. This is consistent with the actual process of latent heat absorption: initially, a large amount of ice crystals melt, and latent heat absorption increases rapidly; later, the remaining ice crystals decrease, and the latent heat absorption rate gradually stabilizes.

[0053] Then, the core temperature inside the cell bag is obtained based on the surface temperature, the instantaneous compensated temperature difference, and the cumulative thermal hysteresis compensation term. The calculation formula expresses the core temperature as the sum of the surface temperature and the two compensation terms: the instantaneous compensated temperature difference reflects the temperature difference caused by the current heat flow, and the cumulative thermal hysteresis compensation term reflects the additional temperature difference caused by the absorption of latent heat during the phase transition. During the phase transition plateau, when the heating rate approaches zero, the instantaneous compensated temperature difference approaches zero, but the cumulative thermal hysteresis compensation term still exists and increases as the phase transition continues, thus maintaining the accuracy of the core temperature estimation.

[0054] Finally, upon exiting the phase transition interval, the accumulated integral value is reset to zero, and the accumulated thermal hysteresis compensation term is linearly decayed to zero. The criteria for exiting the phase transition interval can be set as follows: the surface temperature exceeds the upper limit of a preset phase transition temperature range (e.g., 0°C) for a sustained period, or the phase transition ends based on the rate deviation consistently falling below a certain threshold. When the exit condition is met, the following operations are performed: the accumulated integral value is reset to zero, and the accumulated thermal hysteresis compensation term is linearly decayed to zero according to a preset decay time constant. For example, within each sampling period, the accumulated thermal hysteresis compensation term at the current moment is multiplied by the ratio of the sampling period to the preset decay time constant, and the resulting product is subtracted from the accumulated thermal hysteresis compensation term, thus achieving linear decay of the compensation term. A typical value for the preset decay time constant is 1 to 2 seconds. It is obtained by measuring the actual decay time required for the accumulated compensation term during the liquid heating phase after the phase transition ends, selecting a value that allows for a smooth transition without causing a sudden temperature change. The purpose of this reset and decay mechanism is that after the phase change ends, the cumulative latent heat absorption effect no longer exists, so the cumulative integral value should be cleared to zero and the cumulative compensation term should gradually disappear in order to avoid introducing unnecessary compensation during the liquid heating stage.

[0055] In one embodiment of the present invention, steps S3 and S4 are executed according to the following state machine: State 1: Solid-state heating state. When the surface temperature is below the first threshold or above the second threshold and the phase transition interval is not triggered, the thermal hysteresis compensation coefficient is taken as the preset benchmark compensation coefficient of the solid-state heating interval. State 2: Pre-compensation state, when the surface temperature is within the predicted temperature range and the rate deviation exceeds the preset threshold, the thermal hysteresis compensation coefficient is taken as the pre-compensation coefficient; State 3: Main phase transition. When the heating rate is lower than the preset ratio of the sliding average for multiple consecutive sampling cycles, and the surface temperature is in the phase transition range, the thermal hysteresis compensation coefficient is the thermal hysteresis compensation coefficient dynamically determined in step S4. State 4: Liquid heating state. When the surface temperature is higher than the second threshold or the phase transition interval is predicted to be about to end, the thermal hysteresis compensation coefficient is taken as the liquid compensation coefficient (obtained by factory calibration, existing technology). The states are smoothly switched, and linear interpolation is used at the switching boundaries.

[0056] As described above, this invention provides a state machine control method that selects the appropriate thermal hysteresis compensation coefficient based on different heating stages. During cell resuscitation, the cryopreservation solution undergoes multiple stages, including solid-state heating, ice crystal melting phase transition, and liquid-state heating, each with different heat transfer characteristics. In the solid-state heating stage, the cryopreservation solution is homogeneous, and the thermal hysteresis mainly stems from the thermal resistance of the cell bag wall, resulting in a relatively stable compensation coefficient. During the phase transition stage, due to latent heat absorption, the thermal hysteresis increases significantly and changes with the phase transition process. In the liquid-state heating stage, accelerated liquid convection leads to thermal equilibrium, reducing the thermal hysteresis. Therefore, this invention provides a state machine control method that automatically switches the compensation coefficient calculation mode based on the current heating state.

[0057] The first state is the solid-state heating state. The triggering condition for this state is: the surface temperature is below a first preset temperature threshold, or the surface temperature is above a second preset temperature threshold but the phase transition interval is not triggered. The first preset temperature threshold can be set to -20℃, and the second preset temperature threshold can be set to 0℃. The first preset temperature threshold is obtained by determining the phase transition onset temperature of the cryogenic solution using differential scanning calorimetry (DSC), and taking this temperature value as the first preset temperature threshold. For example, the phase transition onset temperature of a typical cryogenic solution is approximately -20℃. The second preset temperature threshold is obtained by determining the phase transition end temperature of the cryogenic solution using DSC, and taking this temperature value as the second preset temperature threshold. For example, the phase transition end temperature of a typical cryogenic solution is approximately 0℃. In the solid-state heating state, the thermal hysteresis compensation coefficient is taken as the preset baseline compensation coefficient for the solid-state heating interval. This state covers the entire solid-state heating stage from the start of recovery to before entering the phase transition zone, as well as the liquid-state heating stage where the surface temperature is above 0°C after the phase transition (but the liquid-state heating stage is actually handled by the fourth state; here, "above the second preset temperature threshold and without triggering phase transition zone identification" refers to the case where the solid-state heating directly skips the phase transition zone, or serves as a transitional condition for state switching). The function of this technical feature is to avoid unnecessary dynamic adjustments by using a calibrated and verified fixed compensation coefficient during the solid-state heating stage without phase transition interference.

[0058] The second state is the pre-compensation state. This state is triggered when the surface temperature is within the predicted temperature range and the rate deviation exceeds a preset deviation threshold. The predicted temperature range can be set from -25℃ to 5℃, a wider range than the phase transition temperature range, used to initiate predictive monitoring in advance. In the pre-compensation state, the thermal hysteresis compensation coefficient is the pre-compensation coefficient. The purpose of this state is to increase the compensation coefficient in advance, before the phase transition is formally confirmed, when the rate deviation shows that the actual heating rate has significantly lagged behind the expected trend, in order to reduce the core temperature estimation error in the early stages of the phase transition.

[0059] The third state is the main phase transition state. The triggering condition for this state is that for multiple consecutive sampling periods, the heating rate is lower than the product of the moving average and a preset proportional threshold, and the surface temperature is within the phase transition temperature range. This condition is consistent with the condition for confirming the phase transition range in the previous steps; therefore, the triggering time of the main phase transition state is synchronized with the confirmation time of the phase transition range. In the main phase transition state, the thermal hysteresis compensation coefficient is the dynamically determined thermal hysteresis compensation coefficient in the previous steps. This state covers the entire main phase transition stage from phase transition confirmation to the end of the phase transition and is the main stage for the dynamic adjustment of the compensation coefficient in core temperature estimation. The function of this state is to continuously adjust the compensation coefficient according to the decrease ratio of the current heating rate relative to the reference rate during the phase transition process, so that the core temperature estimation can follow the changes in the phase transition process.

[0060] The fourth state is the liquid-state heating state. This state is triggered when the surface temperature exceeds a second preset temperature threshold (e.g., 0°C), or when the phase transition interval is predicted to end. The prediction of the impending end of the phase transition interval can be achieved as follows: when the surface temperature approaches the second preset temperature threshold (e.g., above -5°C) and the heating rate begins to recover, or when the rate deviation remains below a certain small threshold (e.g., 0.1), the phase transition is considered to be nearing its end. In the liquid-state heating state, the thermal hysteresis compensation coefficient is taken as the liquid-state compensation coefficient. The liquid-state compensation coefficient is obtained by using a standard test bag with a pre-embedded thermocouple. A revival experiment is conducted in the liquid-state heating interval (e.g., surface temperature above 2°C, at which point the cryopreservation liquid has completely thawed). The surface temperature, heating rate, and the true core temperature measured by the pre-embedded thermocouple are collected at multiple moments. The difference between the true core temperature and the surface temperature at each moment is calculated. This difference, along with the corresponding heating rate, forms a set of data points. A univariate linear regression is performed on these data points, and the slope of the fitted line is the liquid-state compensation coefficient. A typical value is approximately 0.05 seconds. The purpose of this state is that after the phase change is completed, the cryopreservation solution is in a liquid state, and the thermal convection accelerates the internal thermal equilibrium, reducing thermal hysteresis. A smaller fixed compensation coefficient can meet the estimation accuracy requirements, while avoiding unnecessary dynamic calculations.

[0061] The transitions between the four states mentioned above require a smooth transition to avoid abrupt changes in the core temperature estimation caused by sudden changes in the compensation coefficient. In this embodiment of the invention, linear interpolation is used at the transition boundaries. Specifically, when the state transition condition is met, the compensation coefficient is not immediately switched to the value of the target state. Instead, within a preset transition time window (e.g., 0.5 seconds), the compensation coefficient is linearly changed from the value of the original state to the value of the target state. The transition time is selected to be short enough to avoid introducing significant delays, and long enough to avoid abrupt changes in temperature estimation; a typical value is 0.2 to 0.5 seconds. The function of this smooth transition mechanism is that when the state changes, the compensation coefficient changes continuously, resulting in a smooth transition of the core temperature estimation value and avoiding jitter in the control output caused by sudden changes in the coefficient.

[0062] In one embodiment of the present invention, Figure 4 This is a flowchart illustrating step S6 according to an exemplary embodiment. (Refer to the attached document.) Figure 4 The step of controlling the output power of the heating device according to the core temperature includes: S61, calculate the temperature difference based on the core temperature and the preset target temperature; S62, when the core temperature is lower than the difference between the preset target temperature and the preset rapid heating threshold, the heating device is controlled to output full power; S63, when the core temperature is greater than or equal to the difference between the preset target temperature and the preset rapid heating threshold, switch to PID control mode, using the core temperature as feedback, and adjust the output power of the heating device according to the discrete PID formula: ; In the formula, This indicates the output power (the control output of the heating device; in this embodiment, it is the PWM duty cycle percentage, which determines the heating power). Indicates the current sampling period The temperature difference (representing the difference between the preset target temperature and the core temperature of the current sampling period; the typical value of the preset target temperature is 37℃). This represents the temperature difference in the previous sampling period. Indicates the first Temperature difference per sampling period Indicates the sampling period. Represents the proportionality coefficient. Represents the integral coefficient. Represents the differential coefficient. Indicates the current sampling period. It represents the accumulation of error over time and is used to eliminate long-term deviations; S64 independently monitors the average temperature of the contact probe and the maximum temperature of the thermal imager. When either temperature reaches the preset target temperature limit, it triggers hardware-level heating cut-off. The heating cut-off logic is independent of and takes precedence over the PID control logic.

[0063] As described in steps S61-S64 above, this embodiment of the invention discloses a specific method for controlling the output power of a heating device based on the core temperature. After obtaining an estimated value of the core temperature inside the cell bag, the output power of the heating device needs to be adjusted in real time according to the relationship between the core temperature and the preset target temperature to achieve a rapid, stable, and safe heating process. If only a single PID control is used, the heating may be slow in the initial stage due to insufficient power, prolonging the residence time of cells in the ice crystal danger zone; if only full-power heating is used, overshoot is likely to occur when approaching the target temperature, which may cause thermal damage to the cells. Therefore, the heating control method of this invention automatically switches the control mode according to the difference between the core temperature and the target temperature, and at the same time sets a safety cut-off mechanism independent of software control to prevent the risk of overheating caused by sensor failure or algorithm abnormality.

[0064] First, the temperature difference is calculated based on the core temperature and the preset target temperature. The preset target temperature can be set according to the cell type, with a typical value of 37°C. Second, when the core temperature is lower than the difference between the preset target temperature and the preset rapid heating threshold, the heating device is controlled to output full power. The preset rapid heating threshold is in °C, with a typical value of 3°C. This threshold is obtained by setting it based on the ice crystal danger zone of the cell cryopreservation solution (usually -50°C to 0°C) and the time required to heat from this temperature range to the target temperature, selecting a value that minimizes the heating time while ensuring safety, such as 3°C. When the core temperature is lower than the difference between the preset target temperature and the preset rapid heating threshold, this trigger condition is met. At this time, the heating device outputs 100% PWM duty cycle, i.e., full power heating. The purpose of this mode is to rapidly heat at maximum power when the core temperature is far from the target temperature, reducing the cell's exposure time in the ice crystal danger zone (approximately -50°C to 0°C), thereby reducing mechanical damage to the cells from ice crystals. This mode is a conventional application of switch control, and its specific role in this invention is to complement the subsequent PID mode.

[0065] When the core temperature is greater than or equal to the difference between the preset target temperature and the preset rapid heating threshold, the system switches to PID control mode. The core temperature is used as feedback, and the output power of the heating device is adjusted according to the discrete PID formula. PID control is a classic closed-loop control method. The PID formula is a standard form in control engineering. Its proportional term responds to the current error, the integral term eliminates long-term deviations, and the derivative term predicts the error trend. The PID control mode switches when the core temperature is greater than or equal to the difference between the preset target temperature and the preset rapid heating threshold. At this point, the core temperature is close to the target temperature, and fine-tuning of the power is required to avoid overshoot and ensure steady-state accuracy. The proportional, integral, and derivative coefficients in the PID parameters are obtained by: obtaining the transfer function model of the controlled object through system identification, and then tuning the parameters using the Ziegler-Nichols method or the critical proportionality method. Alternatively, they can be optimized through repeated experiments on actual equipment. Those skilled in the art can determine the PID parameters suitable for specific implementation equipment through experiments based on conventional control engineering practices, without requiring creative effort. The core of the aforementioned dual-mode control strategy lies in automatically switching the control mode based on the distance between the core temperature and the target temperature. This strategy has been applied in industrial temperature control, but its application in a cell resuscitation scenario, using the aforementioned core temperature estimate for switching, yields specific technical benefits. The rapid heating mode shortens the cell's residence time in the ice crystal danger zone, while the PID mode ensures the steady-state accuracy of the target temperature. The combination of the two avoids the problems of slow heating or temperature overshoot that may occur with a single mode.

[0066] Finally, the average temperature of the contact probes and the maximum temperature of the thermal imager are independently monitored. When either temperature reaches the preset target temperature limit, a hardware-level heating cutoff is triggered. This cutoff logic is independent of and takes precedence over the PID control logic. Specifically, the preset target temperature limit can be set as the target temperature plus an allowable deviation upper limit of 0.5℃. The average temperature of the contact probes is obtained by taking the average value after removing the extreme values ​​from the current readings of the five contact infrared probes. The maximum temperature of the thermal imager is obtained by extracting the maximum value from the temperature matrix output by the infrared thermal imager. When the average temperature of the contact probes reaches the sum of the preset target temperature and 0.5℃, or when the maximum temperature of the infrared thermal imager reaches the sum of the preset target temperature and 0.5℃, a hardware-level cutoff is triggered. The hardware-level cutoff can be implemented by setting up a comparator circuit independent of the main controller MCU, comparing the two temperature signals (after signal conditioning) with a preset voltage threshold (corresponding to the target temperature limit). When either comparator outputs a high level, the power relay of the heating device is directly cut off. This hardware cutoff circuit is independent of the MCU's software operating state, so the cutoff function remains effective even if the software crashes or the program malfunctions. The beneficial effect of this feature is that it provides a layer of hardware safety protection independent of software control. When the software-controlled PID regulation fails to effectively limit the temperature due to sensor failure, algorithm anomalies, or external interference, the hardware cutoff can serve as a final safeguard, preventing cell damage due to overheating.

[0067] Example 2 Embodiment 2 of this application also provides a temperature data processing system for cell resuscitation. Figure 5 This is a block diagram illustrating a temperature data processing system for cell resuscitation according to another exemplary embodiment. Figure 5 As shown, the system includes: A heating device is used to hold and heat the cell bags; The temperature detection module includes at least one contact temperature sensor and one non-contact temperature sensor for collecting temperature data on the surface of the cell bag. The controller, electrically connected to the heating device and the temperature detection module, is configured to perform the following functional modules: The data acquisition module is used to acquire temperature data of the cell bag surface and generate a surface temperature sequence based on the temperature data. A temperature calculation module is used to obtain the current temperature rise rate based on the surface temperature sequence. A phase transition determination module is used to determine whether the cryopreservation solution in the cell bag is in the phase transition range of ice crystal melting based on the surface temperature sequence and the heating rate. The compensation coefficient determination module is used to dynamically determine the thermal hysteresis compensation coefficient at the current moment based on the degree of change of the heating rate relative to the start time of the phase transition when the judgment result is that it is in the phase transition interval, wherein the compensation coefficient increases as the heating rate decreases. The core temperature calculation module is used to obtain the core temperature inside the cell bag based on the thermal hysteresis compensation coefficient, the heating rate, and the surface temperature sequence. The control output module is used to control the output power of the heating device according to the core temperature.

[0068] This invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method provided in Embodiment 1.

[0069] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method provided in Embodiment 1.

[0070] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0071] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for processing temperature data for cell resuscitation, characterized in that, Includes the following steps: Acquire temperature data of the cell bag surface and generate a surface temperature sequence based on the temperature data; The heating rate at the current moment is obtained based on the surface temperature sequence; Determine whether the cryopreservation solution in the cell bag is in the phase transition range of ice crystal melting based on the surface temperature sequence and the heating rate; When the determination result is that it is in the phase transition interval, the thermal hysteresis compensation coefficient at the current moment is dynamically determined according to the degree of change of the heating rate relative to the start time of the phase transition interval, wherein the compensation coefficient increases as the heating rate decreases. The core temperature inside the cell bag is obtained based on the thermal hysteresis compensation coefficient, the heating rate, and the surface temperature sequence. The output power of the heating device is controlled according to the core temperature.

2. The method according to claim 1, characterized in that, The step of determining whether the cryopreservation solution in the cell bag is in the phase transition region of ice crystal melting based on the surface temperature sequence and the heating rate includes: Calculate its sliding average value within a preset first time window based on the heating rate; Determine whether the current heating rate is less than a preset proportion of the sliding average value, and determine whether the surface temperature at the current moment in the surface temperature sequence is within a preset phase transition range. If the above two conditions are met, the phase transition judgment condition is satisfied. When multiple consecutive preset sampling periods meet the phase transition judgment condition, it is confirmed that the current moment is in the phase transition range of ice crystal melting.

3. The method according to claim 1, characterized in that, It also includes a phase transition prediction step: Determine whether the surface temperature at the current moment in the surface temperature sequence has entered the preset predicted temperature range. If it has, obtain the historical values ​​of the heating rate of the most recent multiple sampling periods, and combine them with the least squares method to fit and obtain the expected rate at the current moment. Calculate the rate deviation based on the expected rate and the current heating rate; Determine whether the rate deviation exceeds a preset deviation threshold. If it does, obtain a pre-compensation coefficient based on the preset benchmark compensation coefficient for the solid-state heating range and the rate deviation, and use the pre-compensation coefficient to replace the thermal hysteresis compensation coefficient.

4. The method according to claim 3, characterized in that, The step of using the least squares method to fit and obtain the expected rate at the current time includes: Take the heating rate and its corresponding physical time from the most recent multiple sampling periods, fit a univariate linear regression model, and obtain the fitting parameters; The expected rate at the current moment is obtained based on the fitting parameters and the physical time at the current moment.

5. The method according to claim 3, characterized in that, The step of dynamically determining the thermal hysteresis compensation coefficient at the current moment based on the degree of change of the heating rate relative to the start time of the phase transition interval includes: The reference rate at the start of entering the phase transition interval is obtained based on the sliding average value when the phase transition judgment condition is met. The thermal hysteresis compensation coefficient at the current moment is obtained based on the reference rate, the current heating rate, the preset benchmark compensation coefficient for the solid-state heating range, and the preset adaptive coefficient.

6. The method according to claim 5, characterized in that, The step of obtaining the core temperature inside the cell bag based on the thermal hysteresis compensation coefficient, the heating rate, and the surface temperature sequence includes: The instantaneous compensation temperature difference is obtained based on the thermal hysteresis compensation coefficient and the heating rate; The cumulative integral value is obtained by performing a time-based integral on the positive portion of the rate deviation. The cumulative thermal hysteresis compensation term is obtained based on the cumulative integral value, the reference rate, the preset cumulative compensation coefficient, and the saturation time constant; The core temperature inside the cell bag is obtained based on the surface temperature sequence, the instantaneous compensated temperature difference, and the cumulative thermal hysteresis compensation term.

7. The method according to claim 1, characterized in that, The step of controlling the output power of the heating device according to the core temperature includes: Calculate the temperature difference based on the core temperature and the preset target temperature; When the core temperature is lower than the difference between the preset target temperature and the preset rapid heating threshold, the heating device is controlled to output full power. When the core temperature is greater than or equal to the difference between the preset target temperature and the preset rapid heating threshold, the system switches to PID control mode, using the core temperature as feedback, and adjusts the output power of the heating device according to the discrete PID formula.

8. A temperature data processing system for cell resuscitation, characterized in that, The system includes: The data acquisition module is used to acquire temperature data of the cell bag surface and generate a surface temperature sequence based on the temperature data. A temperature calculation module is used to obtain the current temperature rise rate based on the surface temperature sequence. A phase transition determination module is used to determine whether the cryopreservation solution in the cell bag is in the phase transition range of ice crystal melting based on the surface temperature sequence and the heating rate. The compensation coefficient determination module is used to dynamically determine the thermal hysteresis compensation coefficient at the current moment based on the degree of change of the heating rate relative to the start time of the phase transition when the judgment result is that it is in the phase transition interval, wherein the compensation coefficient increases as the heating rate decreases. The core temperature calculation module is used to obtain the core temperature inside the cell bag based on the thermal hysteresis compensation coefficient, the heating rate, and the surface temperature sequence. The control output module is used to control the output power of the heating device according to the core temperature.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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