A centrifuge temperature control method and a centrifuge

Abstract

This application relates to the technical field of medical equipment, and specifically to a centrifuge temperature control method and a centrifuge. By obtaining the temperature value of the centrifuge at the current time node and predicting the temperature value of the next time node according to the deviation state of the current node temperature value, and determining the temperature adjustment range according to the deviation between the predicted temperature value and the standard temperature value, the temperature control device of the centrifuge is adjusted through a PID controller based on dynamically adjusted parameters, so that the working environment temperature of the centrifuge meets the target requirements. The solution provided by the embodiments of this application can obtain the working environment of the centrifuge and predict the environmental changes during the working cycle, and achieve dynamic and precise temperature adjustment based on such environmental changes, thereby reducing the impact and damage on the centrifugation effect due to temperature changes during the use of the centrifuge.

Description

Technical Field

[0001] This application relates to the technical field of medical equipment, and specifically to a centrifuge temperature control method and a centrifuge. Background Art

[0002] Desktop medical centrifuges are usually used to separate blood components, such as separating plasma and red blood cells, or extracting biomolecules such as DNA and RNA. When the centrifuge performs high-speed centrifugal motion, frictional heat will be generated, resulting in an increase in the temperature in the separation chamber. If the temperature exceeds the tolerance range of the sample, there will be a risk of sample damage. For example, for proteins, abnormal temperature increase will cause enzymes and antibodies to become inactivated, thus affecting the detection accuracy; deposited cells will produce hemolysis due to temperature increase, thus destroying blood components. For example, during red blood cell separation, the separation will not be successful; DNA / RNA is easily broken at high temperatures, thus affecting the extraction quality.

[0003] Currently, temperature control devices are provided in most medical centrifuges to control the temperature of the centrifugation environment. However, the temperature control system in the prior art has a slow response speed to temperature changes, and the temperature change in the environment is not a linear change. The existing temperature control system is difficult to quickly reach the set temperature after startup, and the existing temperature control system cannot adapt to load changes and the heat capacity differences of different samples. Usually, only a general temperature control logic is used, which is difficult to meet the temperature changes in the case of multiple samples and multiple rotation speeds, and cannot achieve precise control of the temperature. Summary of the Invention

[0004] In order to solve the technical problems existing in the prior art, the embodiments of this application provide a centrifuge temperature control method and a centrifuge. By obtaining the working environment of the centrifuge and predicting the environmental changes during the working cycle, and based on such environmental changes, dynamic and precise temperature adjustment is realized, thereby reducing the influence and damage of temperature changes on the centrifugation effect during the use of the centrifuge.

[0005] In order to achieve the above purpose, the technical solutions adopted in the embodiments of this application are as follows:

[0006] In a first aspect, a centrifuge temperature control method is provided. The method includes: obtaining the predicted centrifugation environment temperature at the next time node of the centrifuge, and determining the deviation degree from the standard centrifugation environment temperature; the predicted centrifugation environment temperature is the predicted value of the centrifugation environment temperature corresponding to the next time node; when the deviation degree exceeds the established range, the deviation is used as an error and processed by a PID controller with dynamically adjusted parameters to generate a control signal, and the control signal acts on the temperature control device.

[0007] In some specific implementation manners, the method further includes: obtaining the real-time centrifugation environment temperature at the current time node of the centrifuge, and obtaining the predicted centrifugation environment temperature based on the deviation degree between the real-time centrifugation environment temperature and the standard centrifugation environment temperature.

[0008] In some specific implementation manners, determine the standard centrifugation environment temperatures at the current time node and the next time node based on the time node and the heating curve.

[0009] In some specific implementation manners, when the first temperature difference between the real-time centrifugation environment temperature and the standard centrifugation environment temperature exceeds the temperature threshold, obtain the predicted centrifugation environment temperature at the next time node of the centrifuge.

[0010] In some specific implementation manners, when the deviation degree exceeds the established range, taking the deviation as an error and processing it through a PID controller with dynamically adjusted parameters to generate a control signal, includes: when the second temperature difference between the predicted centrifugation environment temperature and the standard centrifugation environment temperature corresponding to the next time node exceeds the temperature threshold, taking the second temperature difference as an error and processing it through a PID controller with dynamically adjusted parameters to generate a control signal.

[0011] In some specific implementation manners, the obtaining the predicted centrifugation environment temperature at the next time node includes: obtaining the centrifugation environment temperature data, centrifuge rotation speed data, and centrifuge motor temperature data of multiple previous time nodes, and processing the centrifugation environment temperature data, centrifuge rotation speed data, and centrifuge motor temperature data through encoding and decoding based on a temperature prediction model to obtain the predicted centrifugation environment temperature at the next time node.

[0012] In some specific implementation manners, the method further includes: splitting multiple previous time nodes in time order to obtain a first sequence group and a second sequence group, where each sequence group contains the centrifugation environment temperature data, centrifuge rotation speed data, and centrifuge motor temperature data corresponding to at least one time node; respectively performing encoding processing and decoding processing based on the self-attention mechanism on the first sequence group and the second sequence group to obtain the predicted centrifugation environment temperature at the next time node.

[0013] In some specific implementation manners, the method further includes: obtaining a centrifugation environment temperature memory information matrix through encoding processing, obtaining a centrifugation environment temperature change sequence through decoding processing, and performing attention calculation on the centrifugation environment temperature memory information matrix and the centrifugation environment temperature change sequence to obtain the predicted centrifugation environment temperature at the next time node.

[0014] In some specific implementation manners, the dynamic adjustment of the parameters generates an initial control quantity through a PID controller, determines the control performance based on the initial control quantity, and optimizes the parameters of the PID controller until the control performance is maximized to determine the target parameters of the PID controller.

[0015] In a second aspect, a centrifuge is provided, including: a centrifugal motor, a centrifugal chamber, a temperature control device, a sensor assembly, and a processing device; the sensor assembly includes a first temperature sensor and a second temperature sensor, the first temperature sensor is used to obtain the temperature of the centrifugal motor, and the second temperature sensor is used to obtain the centrifugal environment temperature in the centrifugal chamber; the processing device is used to execute the centrifuge temperature control method described in any one of the above, send a control signal to the temperature control device, and the processing device includes: a data processing module, configured to obtain the predicted centrifugal environment temperature at the next time node of the centrifuge and determine the deviation degree from the standard centrifugal environment temperature; a control module, configured to, when the deviation degree exceeds a predetermined range, use the deviation as an error and process it through a PID controller with dynamically adjusted parameters to generate a control signal, and the control signal acts on the temperature control device.

[0016] In the technical solution provided by the embodiments of the present application, by obtaining the temperature value of the centrifuge at the current time node and predicting the temperature value at the next time node according to the deviation state of the current node temperature value, and determining the temperature adjustment range according to the deviation between the predicted temperature value and the standard temperature value, the temperature control device of the centrifuge is adjusted through a PID controller with dynamically adjusted parameters, so that the working environment temperature of the centrifuge meets the target requirements. The solution provided by the embodiments of the present application can obtain the working environment of the centrifuge and predict the environmental changes during the working cycle, and achieve dynamic and accurate temperature adjustment based on such environmental changes, thereby reducing the influence and damage of temperature changes on the centrifugation effect during the use of the centrifuge. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0018] The methods, systems, and / or programs in the drawings will be further described according to exemplary embodiments. These exemplary embodiments will be described in detail with reference to the drawings. These exemplary embodiments are non-limiting exemplary embodiments, where the example numbers represent similar mechanisms in the various views of the drawings.

[0019] Figure 1It is a schematic diagram of the structure of a centrifuge provided in an embodiment of the present application.

[0020] Figure 2 It is a flow chart of the centrifuge temperature control method provided in the embodiment of the present application.

[0021] Figure 3 It is a schematic diagram of the structure of the processing device provided in an embodiment of the present application.

[0022] Figure 4 It is a schematic diagram of the terminal device structure provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to better understand the above technical scheme, the technical scheme of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical scheme of the present application, rather than limitations on the technical scheme of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0024] In the following detailed description, numerous specific details are set forth by way of example in order to provide a comprehensive understanding of the relevant guidance. However, it will be apparent to those skilled in the art that the present application may be practiced without these details. In other cases, well-known methods, procedures, systems, compositions and / or circuits have been described at a relatively high level, without detail, in order to avoid unnecessarily obscuring aspects of the present application.

[0025] Flowcharts are used in the present application to illustrate the execution process performed by the system according to the embodiment of the present application. It should be clearly understood that the execution process of the flowchart may not be performed in order. On the contrary, these execution processes may be performed in reverse order or simultaneously. In addition, at least one other execution process may be added to the flowchart. One or more execution processes may be deleted from the flowchart.

[0026] Before further describing the embodiments of the present invention in detail, the nouns and terms involved in the embodiments of the present invention are described. The nouns and terms involved in the embodiments of the present invention are subject to the following interpretations.

[0027] (1) In response to, it is used to indicate the conditions or states on which the executed operation depends. When the dependent conditions or states are met, one or more operations executed may be in real time or with a set delay. Unless otherwise specified, there is no restriction on the order in which the multiple operations executed are executed.

[0028] (2) Based on the conditions or states on which the operations to be performed depend, when the dependent conditions or states are met, one or more operations to be performed can be real-time or can have a set delay; without special instructions, there is no restriction on the execution order of multiple operations to be performed.

[0029] Refer to Figure 1 , an embodiment of the present application provides a centrifuge 10, including a centrifuge main body 11 and a processing device 12, wherein the centrifuge main body drives an object to rotate, especially a non-solid object to rotate, so as to achieve separation between substances, and is commonly used in medical detection scenarios, including but not limited to scenarios such as plasma separation and tissue fluid separation.

[0030] Among them, the structure of the centrifuge main body mainly includes a centrifugal motor for providing rotational power; a centrifugal chamber for providing a centrifugal space for the object to be centrifuged. Among them, the structure of the centrifugal motor and the centrifugal chamber is a non-connected structure. It also includes: a temperature control device 13 for controlling the temperature in the centrifugal chamber to make the centrifugal environment temperature meet the temperature requirements of the object to be centrifuged; a sensor assembly 14 for acquiring specific data.

[0031] In this embodiment, the sensor assembly is a temperature sensor for acquiring specific temperature data. Further, the sensor assembly is composed of two independent temperature sensors, namely the first temperature sensor placed at the centrifugal motor and the second temperature sensor placed in the centrifugal chamber. The first temperature sensor is used to acquire the first temperature of the centrifugal motor, and the second temperature sensor is used to acquire the real-time centrifugal environment temperature in the centrifugal chamber.

[0032] In the actual use scenario, different objects to be centrifuged have different temperature sensitivities according to their own characteristics, that is, the temperature in the centrifugal chamber of the centrifuge should have different upper and lower temperature limits according to different objects to be centrifuged. Especially for biological objects such as blood and tissue fluid, there should be a strict temperature upper limit to avoid inactivation of the object to be centrifuged and invalidation of the sample. Therefore, a temperature control device is set to achieve the adjustment of the temperature in the centrifugal chamber. Generally, in the prior art, the logic for temperature adjustment is to acquire the ambient temperature at the unit time node in the centrifugal chamber through the second temperature sensor, and when the ambient temperature exceeds the warning value, the temperature is adjusted through the temperature control device.

[0033] However, this control method cannot achieve precise control because in actual scenarios, it is difficult for the temperature control device to quickly reach the set temperature after startup. Moreover, the main reasons for the temperature change in the centrifuge chamber are the heat dissipation generated by the motor operation and the heat generated by rotational friction. And this kind of heat change is not a linear change. If the traditional temperature control method is used, it is necessary to set multiple data collection time points with a small interval to avoid the problem of lag in the processing time point caused by a long collection time interval. However, if a multi-node short-time interval data collection strategy is adopted, it will increase the operating cost of the temperature control device. And because it is difficult for the temperature control to quickly reach the set temperature after startup, the corresponding effect cannot be achieved within one time period for temperature control. Moreover, for the usage scenarios of this centrifuge, the melting heat differences of different medical samples are relatively large, and the heat dissipation generated due to different rotation speeds for centrifugation operations of different samples is also different. Therefore, the centrifuges in the prior art cannot achieve the effect of fine temperature control for different types of samples.

[0034] To solve this problem, a processing device is also provided in the centrifuge in this embodiment. A temperature control method is configured in the processing device to generate a control signal acting on the temperature control device so that the temperature control device can precisely regulate the ambient temperature in the centrifuge chamber. Among them, the processing device in this embodiment can be a module set at the central control end or a module set in the temperature control device. In this embodiment, the physical structure and hardware structure thereof will not be elaborated further.

[0035] Specifically, for the temperature control method configured in the processing device, reference can be made to Figure 2 , including the following steps:

[0036] Step S21. Obtain the predicted centrifugation ambient temperature at the next time node of the centrifuge, and determine the deviation degree from the standard centrifugation ambient temperature.

[0037] In this embodiment, for this process, which is a prerequisite for temperature adjustment, that is, the predicted ambient temperature at the next time node needs to be compared with the standard centrifugation ambient temperature. When there is a deviation and the deviation degree does not meet the requirements, temperature adjustment is performed. However, it should be noted that determining the predicted ambient temperature at the next time node is not required every time temperature is collected. In this embodiment, it is only collected when there is a deviation between the real-time centrifugation ambient temperature corresponding to the current time node and the standard centrifugation ambient temperature, and the deviation degree does not meet the requirements.

[0038] Therefore, in this embodiment, according to the execution logic, the real-time centrifugation ambient temperature at the current time node should be obtained first, and whether to obtain the predicted centrifugation ambient temperature is determined based on the deviation between the real-time centrifugation ambient temperature and the standard centrifugation ambient temperature.

[0039] Specifically, in this embodiment, the standard centrifugation ambient temperatures for the current time node and the next time node are determined through specific time nodes and heating curves. Therefore, in this embodiment, a heating curve is also set in the processing device. The heating curve is a curve showing the change of the temperature in the centrifuge chamber over time when the object to be centrifuged performs centrifugation operation by itself without the influence of an external heat source. It can be understood that the heating curve is the ideal temperature change of the object to be centrifuged. This heating curve is obtained through multiple simulation experiments by constructing a simulation model, and can also be obtained by fitting after multiple actual measurements under stable room temperature conditions away from heat sources. In this embodiment, the heating curve is obtained by fitting.

[0040] Moreover, it should be noted that the heating curves for different centrifugation objects are different. Therefore, in this embodiment, when performing actual centrifugation operations, the corresponding heating curve can be obtained by selecting the object to be centrifuged.

[0041] In this embodiment, constructing the heating curve can fully reflect the ideal heating process of the object in the centrifugation environment, and using the heating curve as the baseline for temperature control can better conform to the changes in specific centrifugation operations, providing a more accurate reference object for temperature control.

[0042] Among them, in this embodiment, since the centrifugation operation times of different objects to be centrifuged are different, the settings of the time nodes for temperature acquisition are also different. In this embodiment, the settings of the time nodes are determined according to the change of the tangent slope of the heating curve. This is easy to understand. In the temperature change, the slope of the curve tangent can express the degree of temperature change. By determining multiple change inflection points in the heating curve and taking the inflection points with a larger change rate as the time points for temperature acquisition, the heating process can be better judged. Generally, 8 heating inflection points can be selected, and the settings of multiple time nodes should cover the entire centrifugation process. In this way, the processing cost caused by frequent temperature acquisition is reduced, and the problem of missed acquisition caused by reducing the sampling points can be ensured.

[0043] In this embodiment, a corresponding temperature increase curve and corresponding time nodes are determined based on the object to be centrifuged, and the real-time centrifugation ambient temperature at the corresponding time nodes is collected during centrifugation. The deviation degree is judged based on the collected real-time centrifugation ambient temperature and the standard centrifugation ambient temperature, that is, the first temperature difference between the real-time centrifugation ambient temperature and the standard centrifugation ambient temperature is determined, and it is determined whether the first temperature difference exceeds the temperature threshold. Among them, the temperature threshold refers to the range within which the deviation is allowed, rather than the temperature range.

[0044] It should be noted that the setting of the temperature threshold in this embodiment is not a unified value. The setting of this temperature threshold should be determined according to the temperature value corresponding to the specific time node. For example, in the early stage of the centrifugation process, the range of the temperature threshold is larger than that in the later stage of the centrifugation process in order to reduce the control cost, and the threshold range is also different for different centrifugation objects. For this process, first, the corresponding temperature threshold is retrieved based on the current time node, and then it is determined whether the first temperature difference between the real-time centrifugation ambient temperature and the standard centrifugation ambient temperature exceeds the temperature threshold. If it does not exceed, it means that the current temperature change is within the allowed range; if it exceeds, it means that the current temperature change is outside the allowed range.

[0045] In the prior art, the treatment for exceeding the temperature threshold is to directly perform temperature control. However, for the temperature system, especially for the occasional temperature change of a non-ideal temperature change system, it does not mean the overall temperature change trend. In order to reduce the frequency and cost of temperature control. In this embodiment, it is determined whether the current temperature environment should be adjusted by predicting the centrifugation ambient temperature at the next time point.

[0046] Among them, the predicted temperature value for the next time node is obtained by using a temperature prediction model in this embodiment. Also, since the main interference sources for the temperature change in the centrifugation environment are the rotation speed of the centrifuge and the heat dissipation temperature of the centrifugation motor, in this embodiment, the temperature prediction model infers the predicted temperature value for the next time node by collecting the above data and based on machine learning.

[0047] Furthermore, in order to better improve the accuracy of the temperature prediction model, the above data should be continuous data during the centrifugation operation, because continuous data can reflect the relationship between temperature and time. Therefore, the input data of the temperature prediction model in this embodiment should be the previous data including the current time node, that is, the centrifugation ambient temperature data, the centrifuge rotation speed data, and the centrifugation motor temperature data corresponding to multiple time points are obtained, and the output result is the predicted value of the centrifugation ambient temperature at the next time node.

[0048] Among them, for the temperature prediction model, a machine learning model is adopted in this embodiment, specifically a Transformer model, which includes an embedding layer, an encoder, a decoder, and an output layer.

[0049] Specifically, the embedding layer is used to extract the time series, that is, time nodes, and the corresponding data. The above data is converted into a data embedding matrix, and the data embedding matrix is converted into a time series embedding matrix by extracting the time series information of the time nodes. Among them, for the conversion process of the data, through the weight matrix and bias of the corresponding learnable parameters, the centrifugal environment temperature data, the centrifuge speed data, and the centrifugal motor temperature data are mapped to a high-dimensional representation space, so that the long-distance dependence relationship of the centrifugal environment temperature sequence can be better captured in the subsequent processing process.

[0050] Among them, the data embedding matrix is represented based on the following formula:

[0051] ; where , , respectively represent the high-dimensional representations corresponding to the centrifuge speed data, the centrifugal environment temperature data, and the centrifugal motor temperature data, , and respectively represent the input matrices corresponding to the centrifuge speed data, the centrifugal environment temperature data, and the centrifugal motor temperature data, , and respectively represent the weight matrices corresponding to the centrifuge speed data, the centrifugal environment temperature data, and the centrifugal motor temperature data, , and respectively represent the biases corresponding to the centrifuge speed data, the centrifugal environment temperature data, and the centrifugal motor temperature data.

[0052] Among them, the output of the embedding layer is the sum of the above-mentioned high-dimensional matrix and the position encoding matrix, and finally represented as an embedding matrix. Among them, the position encoding matrix is obtained by processing the time series information based on the trigonometric function position encoding. The trigonometric function position encoding process can be implemented by the existing technology solutions and will not be elaborated in this embodiment.

[0053] In this embodiment, the encoder is composed of multiple encoding block layers with the same structure but different parameters stacked together. Each encoding block layer includes a multi-head self-attention layer, a feed-forward neural network, a residual connection, and a layer normalization structure. Among them, in the multi-head self-attention layer, by calculating the coefficient attention distribution of the embedding matrix, the change trends of the centrifugal environment temperature, the centrifuge speed, and the centrifugal motor temperature in the high-dimensional features are captured, and the similarity between the high-dimensional feature vectors is obtained. The feed-forward neural network layer extracts the temperature memory information matrix of the centrifugal motor temperature in the similarity for the decoder to perform prediction calculations.

[0054] Among them, the decoder is similar in structure to the encoder, and is also composed of multiple decoder layers with the same structure but different parameters stacked together. The input of the decoder is the embedding matrix processed by the embedding layer. The difference in obtaining the embedding matrix of the decoder from that of the encoder is that the embedding matrix of the encoder is obtained by performing embedding processing based on the first sequence group, while the embedding matrix of the decoder is obtained by performing embedding processing based on the second sequence group.

[0055] Among them, the first sequence group and the second sequence group are obtained by dividing the overall data sequence according to time nodes; that is, the previous multiple time nodes are divided in time order. The sequence group corresponding to the embedding sequence input to the encoder is the first half of the time group, while the sequence group corresponding to the embedding sequence input to the decoder is the second half of the time group. The reason for this setting is that it can enable the model to understand the data changes corresponding to time changes and better capture the relationship between time and changes.

[0056] Specifically, each decoder layer group is provided with a multi-head self-attention layer, an interactive attention layer, a feed-forward neural network layer, a residual connection, and a layer normalization structure. The sparse attention scores of the embedding matrix are calculated through the multi-head self-attention layer, and the obtained adjacent temperature trend is used as the query matrix of the interactive attention layer. The temperature memory information matrix output by the encoder layer is used as the key matrix and value matrix of the interactive attention layer to calculate the interactive attention scores representing the similarity of the centrifugal environment temperature changes, and the change trend of the centrifugal environment temperature is preliminarily generated through the feed-forward neural network layer.

[0057] For the output layer, a multi-layer perceptron structure is adopted. Each neuron in the first hidden layer shares the output of the decoder in the same layer. The output dimension of the second hidden layer is set to the number of prediction tasks, so that the output of the decoder is gradually mapped into the target space, and the centrifugal environment temperature is predicted at one time, thereby reducing the cumulative error of temperature prediction.

[0058] In this embodiment, the temperature prediction model with the above structure can determine the centrifugal environment temperature information at the next time point, and this information is used to determine whether there is a deviation in the temperature in the current centrifugal environment. Among them, the standard centrifugal environment temperature information is determined according to the time-temperature relationship of the heating curve.

[0059] Step S22. When the deviation degree exceeds the established range, the deviation is regarded as an error and processed by a PID controller with dynamically adjusted parameters to generate a control signal, and the control signal acts on the temperature control device.

[0060] In this embodiment, through step S21, the predicted centrifugal environment temperature at the next time point can be determined, and the predicted centrifugal environment temperature is calculated with the standard centrifugal environment temperature to obtain a deviation value. Then, the deviation value is compared with the temperature threshold. When the deviation value exceeds the temperature threshold, it indicates that temperature adjustment is required.

[0061] Specifically, the temperature adjustment in this embodiment is implemented by a PID controller, but it is different from the PID temperature control in the prior art. The PID controller in this embodiment determines the optimal PID control parameter value by a dynamic adjustment method.

[0062] Among them, the input for PID control is the deviation value determined in step S21, that is, the difference between the predicted centrifugal environment temperature value and the standard centrifugal environment temperature value. The deviation value is input into the PID controller to generate an initial control quantity, and the control performance is determined based on the initial control quantity; then the parameters of the PID controller are optimized until the control performance is maximized. At this time, the parameters of the PID controller are determined as the target parameters, and then a target PID controller is constructed based on these target parameters. The input deviation value is processed by the target PID controller to obtain the final control quantity, and the temperature control device is adjusted based on this control quantity.

[0063] Specifically, the parameters for PID control include the proportional coefficient kp, the integral coefficient ki, and the differential coefficient kd. Among them, the optimization and optimal search for the above three parameters are implemented by the ISSA algorithm in this embodiment. Specifically, the ISSA algorithm uses the PWLCM chaotic mapping initialization strategy and the Levy flight strategy to optimize the initialization population of the standard sparrow search algorithm and the position equations of the discoverers and guardians in the population, and seeks the sparrow individual with the smallest fitness value through the improved sparrow search algorithm. The sparrow individual with the smallest fitness value is the optimal PID control parameter.

[0064] Specifically, the processing process is to initialize the sparrow population based on the PWLCM chaotic map. Among them, in this embodiment, the PWLCM chaotic map initialization strategy is used to enhance the diversity of the number of sparrow initial populations in the sparrow search algorithm, thereby improving the performance of subsequent iterative optimization of the sparrow search algorithm. Among them, the function representation of the chaotic map is as follows: ; where and are respectively random numbers within [0, 1]. Calculate the initial fitness value based on the fitness function, and the initial fitness value is used to characterize the control adaptability of the current control system. Among them, the fitness function is represented by the following formula: ; where u(t) represents the output of the PID controller, e(t) represents the deviation value, tu represents the rise time of the PID controller, , , and respectively represent the weighted values of each item in the fitness function. In this embodiment, the above weighted values are respectively taken as the following values: 0.999, 0.111, 2, and 100.

[0065] Use Levy flight to update the position of the discoverer. Among them, Levy flight is a random walk strategy with the characteristic that the probability distribution of the step size is a heavy-tailed distribution. Based on this characteristic, when performing random walk, the time of small-step walk occupies more, and the time of large-step walk is less. By this characteristic, the existing sparrow search algorithm will be improved, which can enhance the local search ability and find the local optimal solution. In this embodiment, by using Levy flight to update the position of the discoverer, the position of the follower, and the position of the vigilant, recalculate the fitness of each individual in the sparrow population and update the position of the sparrow individual. If the maximum number of iterations is reached or the optimal solution is found, stop the operation and output the optimal PID controller parameters; if the iteration requirement is not met, continue to use the loop operation of updating the position of the discoverer, the position of the follower, and the position of the vigilant by Levy flight.

[0066] In this embodiment, by improving the sparrow search algorithm, the technical problems of lack of diversity in the initialization population and easy to fall into local optimum in the existing technology can be solved, thereby improving the overall optimization performance, making the target parameters of the PID controller reach the optimal effect, and thus greatly improving the overall temperature control accuracy.

[0067] In this embodiment, referring to Figure 3 , based on the processing process of steps S21 - S22, a virtual module for processing the above process is configured in the processing device, and in other embodiments, this virtual module can also independently execute the processing process of steps S21 - S22. Regarding this processing device 12, it includes the following modules:

[0068] A data processing module 121, configured to obtain the predicted centrifugation ambient temperature at the next time node of the centrifuge, and determine the degree of deviation from the standard centrifugation ambient temperature;

[0069] A control module 122, configured to, when the degree of deviation exceeds a predetermined range, use the deviation as an error and process it through a PID controller with dynamically adjusted parameters to generate a control signal, and the control signal acts on the temperature control device.

[0070] Refer to Figure 4 , in other embodiments, the above method may also be integrated into the provided terminal device 40. In view of the relatively large differences that may occur due to different configurations or performances of the device, it may include one or more processors 401 and a memory 402. One or more application programs or data may be stored in the memory 402. Among them, the memory 402 may be a transient storage or a persistent storage. The application programs stored in the memory 402 may include one or more modules (not shown in the figure), and each module may include a series of computer executable instructions in the terminal device. Further, the processor 401 may be set to communicate with the memory 402, and execute a series of computer executable instructions in the memory 402 on the terminal device. The terminal device may also include one or more power supplies 403, one or more wired or wireless network interfaces 404, one or more input / output interfaces 405, one or more keyboards 406, etc.

[0071] In a specific embodiment, the terminal device includes a memory, and one or more programs, where one or more programs are stored in the memory, and one or more programs may include one or more modules, and each module may include a series of computer executable instructions in the terminal device, and is configured to be executed by one or more processors. The one or more programs include computer executable instructions for performing the following:

[0072] Obtain the predicted centrifugation ambient temperature at the next time node of the centrifuge, and determine the degree of deviation from the standard centrifugation ambient temperature;

[0073] When the degree of deviation exceeds a predetermined range, use the deviation as an error and process it through a PID controller with dynamically adjusted parameters to generate a control signal, and the control signal acts on the temperature control device.

[0074] The following specifically introduces each component of the processor:

[0075] Among them, in this embodiment, the processor is an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. For example, one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs).

[0076] Optionally, the processor can execute various functions by running or executing software programs stored in the memory and calling data stored in the memory. For example, it can execute the Figure 1 method shown above.

[0077] In a specific implementation, as an embodiment, the processor may include one or more microprocessors.

[0078] Among them, the memory is used to store the software program for executing the solution of the present application and is controlled by the processor for execution. The specific implementation manner can refer to the above method embodiments and will not be elaborated here.

[0079] Optionally, the memory can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or it can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory can be integrated with the processor or exist independently and be coupled to the processing unit through the interface circuit of the processor. The embodiments of the present application do not make specific limitations on this.

[0080] It should be noted that the structure of the processor shown in this embodiment does not constitute a limitation on the device. The actual device may include more or fewer components than shown in the figure, or combine some components, or have a different component layout.

[0081] In addition, the technical effects of the processor may refer to the technical effects of the method described in the above method embodiments, which will not be elaborated here.

[0082] It should be understood that the processor in the embodiments of the present application may be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0083] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0084] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0085] In this application, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0086] It should be understood that in various embodiments of the present application, the sequence numbers of the above processes do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0087] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professionals can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0088] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0089] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings, direct couplings, or communication connections shown or discussed with each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0090] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0092] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The foregoing storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0093] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims described above.

Claims

1. A temperature control method for a centrifuge, characterized in that, The method includes: Obtaining the predicted centrifugation ambient temperature at the next time node of the centrifuge, and determining the degree of deviation from the standard centrifugation ambient temperature; the predicted centrifugation ambient temperature is the predicted value of the centrifugation ambient temperature corresponding to the next time node; the method further includes: obtaining the real-time centrifugation ambient temperature at the current time node of the centrifuge, and obtaining the predicted centrifugation ambient temperature based on the degree of deviation between the real-time centrifugation ambient temperature and the standard centrifugation ambient temperature; when the first temperature difference between the real-time centrifugation ambient temperature and the standard centrifugation ambient temperature exceeds the temperature threshold, obtaining the predicted centrifugation ambient temperature at the next time node of the centrifuge. When the degree of deviation between the predicted centrifugation ambient temperature at the next time node of the centrifuge and the standard centrifugation ambient temperature exceeds the established range, taking the deviation as an error and processing it through a PID controller with dynamically adjusted parameters to generate a control signal, including: when the second temperature difference between the predicted centrifugation ambient temperature and the standard centrifugation ambient temperature corresponding to the next time node exceeds the temperature threshold, taking the second temperature difference as an error and processing it through a PID controller with dynamically adjusted parameters to generate a control signal; the control signal acts on the temperature control device.

2. The centrifuge temperature control method according to claim 1, wherein Determining the standard centrifugation ambient temperature at the current time node and the next time node based on the time node and the heating curve.

3. The centrifuge temperature control method according to claim 1, characterized in that The obtaining of the predicted centrifugation ambient temperature at the next time node of the centrifuge includes: obtaining the centrifugation ambient temperature data, centrifuge speed data, and centrifuge motor temperature data at multiple previous time nodes, and processing the centrifugation ambient temperature data, centrifuge speed data, and centrifuge motor temperature data through encoding and decoding based on a temperature prediction model to obtain the predicted centrifugation ambient temperature at the next time node.

4. The centrifuge temperature control method according to claim 3, wherein The method further includes: splitting multiple previous time nodes in time order to obtain a first sequence group and a second sequence group, where each sequence group contains the centrifugation ambient temperature data, centrifuge speed data, and centrifuge motor temperature data corresponding to at least one time node; respectively performing encoding processing and decoding processing based on the self-attention mechanism on the first sequence group and the second sequence group to obtain the predicted centrifugation ambient temperature at the next time node.

5. The centrifuge temperature control method according to claim 4, characterized in that, The method further includes: obtaining a centrifugation ambient temperature memory information matrix through encoding processing, obtaining a centrifugation ambient temperature change sequence through decoding processing, and performing attention calculation on the centrifugation ambient temperature memory information matrix and the centrifugation ambient temperature change sequence to obtain the predicted centrifugation ambient temperature at the next time node.

6. The centrifuge temperature control method according to claim 1, wherein The dynamic adjustment of the parameters generates an initial control quantity through a PID controller, determines the control performance based on the initial control quantity, optimizes the parameters of the PID controller, and determines the target parameters of the PID controller.

7. A centrifuge, characterized in that, Including: A centrifuge motor, a centrifuge chamber, a temperature control device, a sensor assembly, and a processing device; The sensor assembly includes a first temperature sensor and a second temperature sensor, the first temperature sensor is used to obtain the centrifuge motor temperature of the centrifuge motor, and the second temperature sensor is used to obtain the centrifugation ambient temperature in the centrifuge chamber. The processing device is used to execute the centrifuge temperature control method described in any one of claims 1-6, and send a control signal to the temperature control device. The processing device includes: A data processing module, configured to obtain the predicted centrifugation environment temperature at the next time node of the centrifuge, and determine the deviation degree from the standard centrifugation environment temperature; it also includes: obtaining the real-time centrifugation environment temperature at the current time node of the centrifuge, and obtaining the predicted centrifugation environment temperature based on the deviation degree between the real-time centrifugation environment temperature and the standard centrifugation environment temperature; when the first temperature difference between the real-time centrifugation environment temperature and the standard centrifugation environment temperature exceeds the temperature threshold, obtain the predicted centrifugation environment temperature at the next time node of the centrifuge; A control module, configured to, when the deviation degree between the predicted centrifugation environment temperature at the next time node of the centrifuge and the standard centrifugation environment temperature exceeds the established range, take the deviation as an error and process it through a PID controller with dynamically adjusted parameters to generate a control signal, including: when the second temperature difference between the predicted centrifugation environment temperature and the standard centrifugation environment temperature corresponding to the next time node exceeds the temperature threshold, take the second temperature difference as an error and process it through a PID controller with dynamically adjusted parameters to generate a control signal; the control signal acts on the temperature control device.

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