Data center immersed liquid cooling control method, equipment, medium and product

Abstract

The invention relates to the technical field of liquid cooling control, in particular to a data center immersed liquid cooling control method and device, a medium and a product, and the method comprises the steps: determining a cooling liquid flowing strategy corresponding to a liquid cooling tank based on a heating parameter and a working parameter of each heating device; determining a heating distribution diagram corresponding to the liquid cooling tank based on the heating parameters of each heating device; driving a simulated liquid cooling tank model corresponding to the liquid cooling tank based on the cooling flow strategy, and determining a cooling distribution diagram corresponding to the cooling liquid flow strategy; determining an abnormal heat dissipation area and an abnormal cooling area based on the heating distribution diagram and the cooling distribution diagram; and determining an auxiliary cooling strategy based on the abnormal heat dissipation area and the abnormal cooling area, and cooling all heating equipment in the liquid cooling tank based on a cooling liquid flowing strategy and the auxiliary cooling strategy. According to the invention, the heat dissipation effect is improved, and the probability that the computing power of equipment is reduced due to starting of down-conversion protection is reduced.

Description

Technical Field

[0001] This application relates to the field of liquid cooling control technology, and in particular to a data center immersion liquid cooling control method, equipment, medium and product. Background Technology

[0002] With the rapid development of the digital economy, data centers, as the core of computing infrastructure, are experiencing a continuous expansion in the scale of business they support, and their computing density is also increasing exponentially. In the large-scale construction and operation of data centers, users have increasingly stringent requirements for equipment stability, response speed, and service continuity. If the heat generated by the equipment cannot be dissipated in time, it may directly lead to increased chip temperature, decreased computing efficiency, or even serious failures such as hardware crashes and data loss. Therefore, efficient heat dissipation has become a core bottleneck restricting the improvement of computing power and stable operation of data centers.

[0003] The mainstream heat dissipation solution in conventional data centers still relies on traditional air cooling technology. The indoor air is cooled to a specified range by the air conditioning in the server room, and then the cool air is driven by the internal fans of the server to flow through the heat-generating components. The heat is dissipated through convection heat exchange. However, because the high-density arrangement of components may form dense physical gaps, it is difficult for the cool air to effectively penetrate the gaps between the components. This can easily lead to a heat island effect around the chip, which directly weakens the cooling effect. Not only can it not meet the heat dissipation requirements of high heat density equipment, but the continuous overheating forces the equipment to activate frequency reduction protection, which further aggravates the loss of computing power and creates a vicious cycle of insufficient heat dissipation and decreased computing power. Summary of the Invention

[0004] To improve heat dissipation and reduce the probability of decreased computing power due to the activation of frequency reduction protection, this application provides a data center immersion liquid cooling control method, equipment, medium, and product.

[0005] Firstly, this application provides a data center immersion liquid cooling control method, which adopts the following technical solution: A data center immersion liquid cooling control method includes: The heating parameters of each heating device in the liquid cooling tank and the operating parameters corresponding to a preset time period are obtained, and the coolant flow strategy corresponding to the liquid cooling tank is determined based on the heating parameters and operating parameters of each heating device. The heat distribution diagram corresponding to the liquid cooling tank is determined based on the heat parameters of each heat-generating device. Based on the cooling flow strategy, drive the simulated liquid cooling tank model corresponding to the liquid cooling tank, and determine the cooling distribution diagram corresponding to the coolant flow strategy; Based on the heat distribution map and the cooling distribution map, abnormal heat dissipation areas and abnormal cooling areas are determined; Based on the abnormal heat dissipation area and the abnormal cooling area, an auxiliary cooling strategy is determined, and based on the coolant flow strategy and the auxiliary cooling strategy, all heat-generating devices in the liquid cooling tank are cooled.

[0006] By adopting the above technical solution, the heat-generating equipment in the data center is immersed in a liquid cooling tank. This direct immersion and close contact with the cold plate facilitates the elimination of multi-stage thermal resistance between air, heat sinks, and chips, thus improving cooling efficiency. Furthermore, the coolant flow strategy for the liquid cooling tank is not a fixed approach but rather tailored to the actual heat generation of each device within the tank and its potential operational status over a future period. This improves the cooling effect on the heat-generating equipment. In addition, simulating the effect of the coolant flow strategy within the tank allows for the timely detection of uneven cooling. By developing corresponding auxiliary cooling strategies for uneven cooling and employing a synergistic cooling approach, the accuracy, dynamic adaptability, and operational reliability of the liquid cooling tank's heat dissipation are improved, thereby enhancing heat dissipation and reducing the probability of reduced computing power due to throttling protection.

[0007] In one possible implementation, determining the auxiliary cooling strategy based on the abnormal heat dissipation area and the abnormal cooling area includes: The abnormal heat dissipation area and abnormal heat dissipation value of the abnormal heat dissipation region are identified from the heat dissipation distribution map, and the abnormal cooling area of ​​the abnormal cooling region is identified from the cooling distribution map. The stirring frequency is determined based on the ratio of the abnormal heat dissipation area to the abnormal cooling area. The stirring direction is determined based on the abnormal heat dissipation area and the abnormal cooling area, and the stirring-assisted cooling strategy is determined based on the stirring direction and the stirring frequency. The stirring-assisted cooling strategy is used to control the stirring rod in the liquid cooling tank to stir and cool the coolant. Identify the abnormal heat dissipation area corresponding to the abnormal heat-generating device, and generate a micro-channel cooling auxiliary strategy based on the abnormal heat dissipation area and the abnormal heat dissipation value. The micro-channel cooling auxiliary strategy is used to control the external micro-channel of the abnormal heat-generating device to perform auxiliary cooling. The stirring-assisted cooling strategy and the microchannel cooling-assisted strategy constitute the auxiliary cooling strategy.

[0008] By adopting the above technical solution, targeted stirring treatment is carried out based on abnormal heat dissipation and abnormal cooling areas, which facilitates precise control of the flow direction of cooling resources, thereby improving the utilization rate of cooling resources. In addition, by activating the micro-channels of abnormal heat-generating equipment for auxiliary cooling, it is possible to achieve precise cooling treatment while reducing the impact on other non-abnormal heat-generating equipment in the liquid cooling tank.

[0009] In one possible implementation, when there are multiple abnormal heat dissipation areas, the method further includes: Identify the abnormal heat dissipation edges of each abnormal heat dissipation area, and determine the abnormal integration area corresponding to all abnormal heat dissipation areas based on each abnormal heat dissipation edge. Identify the abnormal integration distribution map corresponding to the abnormal integration region from the heat distribution map, and identify the outward expansion rate and outward expansion direction of the abnormal integration distribution map; Identify the auxiliary cooling devices within the abnormal integration area, and determine the corresponding integrated auxiliary cooling strategy for the auxiliary cooling devices based on the outward expansion rate and direction of the abnormal integration distribution map.

[0010] By adopting the above technical solution, by identifying the edges of each abnormal heat dissipation area and integrating them into an abnormal integrated area, it is easier to discover the possible correlation between multiple scattered abnormal heat dissipation areas. This avoids the problem of heat migration or secondary heat accumulation caused by isolating and cooling a single abnormal heat dissipation area. By identifying the outward expansion rate and direction of the abnormal integrated area, it is easier to predict the trend of abnormal heat spread, thereby facilitating the adjustment of the effective range and intensity of the auxiliary cooling equipment in advance, and thus improving the cooling effect.

[0011] In one possible implementation, determining the integrated auxiliary cooling strategy corresponding to the auxiliary cooling device based on the outward expansion rate and direction of the abnormal integration distribution map includes: When the outward expansion rate is higher than a preset rate threshold, the outward expansion influencing device corresponding to the outward expansion direction is identified. The outward expansion influencing device is a heating device located on the outward expansion path corresponding to the outward expansion direction. Identify the equipment level and heating parameters of each externally affected device, and determine the abnormal equipment level of each externally affected device based on the equipment level and heating parameters; Based on the abnormal device level of each externally affected device within the abnormal integration area, the regional abnormality level of the abnormal integration area is determined. Based on the anomaly level of the region and the number of auxiliary cooling devices, the corresponding integrated auxiliary cooling strategy for the anomaly integration region is determined.

[0012] By adopting the above technical solution, when the outward expansion rate of the hot zone exceeds the standard, the equipment affected by the outward expansion is located first, rather than the entire liquid cooling tank is cooled indiscriminately. This helps to avoid blindly expanding the cooling range. By analyzing the abnormal equipment level of each equipment affected by the outward expansion, and determining the regional abnormality level of the abnormal integration area based on the abnormal equipment level, it is easier to clearly locate the auxiliary cooling intensity required for the abnormal integration area. By accurately matching the auxiliary cooling intensity through the regional abnormality level, the problem of excessive or insufficient cooling is avoided.

[0013] In one possible implementation, when the extended influence device includes a device of interest, the method further includes: Identify the heat dissipation edge line of the heat dissipation area corresponding to the device of concern from the heat distribution map; Identify the integration edge line of the abnormal integration area, and determine the supporting cooling device based on the integration edge line, wherein the interval distance between the supporting cooling device and the integration edge line is less than a preset interval distance threshold; Determine the edge line contact interval between the heat dissipation edge line and the integration edge line; When the edge line contact interval is less than the preset contact interval, a support cooling strategy is determined based on the outward expansion rate and the edge line contact interval. The support cooling strategy is used to control the peripheral microchannel of the support device to perform support cooling.

[0014] By adopting the above technical solution, and by analyzing the distance between the heat dissipation edge line of the affected equipment and the integration edge line of the abnormal integration area, it is easier to accurately determine the risk range of the affected equipment that may be affected by the spread of heat, rather than making a general judgment on whether the equipment in the entire cooling tank is threatened. The distance makes it easier to prioritize the degree of risk faced by the affected equipment. When the degree of risk is high, the integration edge line of the abnormal integration area makes it easier to screen out the support cooling equipment with the closest distance, thereby shortening the support protection response time. The support cooling strategy is determined by the outward expansion rate and the edge line contact interval, which makes it easier to dynamically trigger support according to the urgency of the risk, thereby avoiding the problem of over- or under-protection.

[0015] In one possible implementation, the method further includes: Obtain each abnormal integration region and abnormal integration image recorded within a preset integration time period, and determine the intersection region of all abnormal integration regions based on each abnormal integration image; Identify the impurity accumulation area of ​​the liquid cooling tank corresponding to the preset integration time period, and identify the accumulation area of ​​the impurity accumulation area; When the accumulated area is greater than a preset area threshold, and the distance between the impurity accumulation area and the intersection area is less than a preset distance threshold, an impurity cleaning instruction is generated based on the impurity accumulation area and the accumulated area. The impurity cleaning instruction is used to remind relevant personnel to clean the impurities in the liquid cooling tank.

[0016] By adopting the above technical solution, the intersection area of ​​all abnormal integration areas within a preset time period can be obtained, making it easier to locate the core area in the liquid cooling tank where thermal anomalies occur repeatedly over a long period of time. By linking the impurity accumulation area with the intersection area, it is easier to determine whether the impurities are a potential cause of the thermal anomaly. A cleaning instruction is only generated when the impurity accumulation area exceeds the standard and is close to a high-risk intersection area. This avoids frequent shutdowns for cleaning due to a small amount of impurities and delays in processing due to excessive impurities. By improving the targeting of impurity cleaning, it is easier to ensure the stability of the cooling effect of the liquid cooling tank.

[0017] Secondly, this application provides an electronic device that adopts the following technical solution: An electronic device comprising: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute the above-described data center immersion liquid cooling control method.

[0018] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program stored thereon that can be loaded by a processor and execute the above-described data center immersion liquid cooling control method.

[0019] Fourthly, this application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program that, when executed by a processor, implements the aforementioned data center immersion liquid cooling control method.

[0020] In summary, this application includes at least one of the following beneficial technical effects: By immersing the heat-generating equipment in a liquid cooling tank, a direct immersion and close contact cooling method is used to eliminate the multi-stage thermal resistance of air, heat sinks, and chips in air cooling, thereby improving cooling efficiency. Furthermore, the coolant flow strategy for the liquid cooling tank is not a fixed approach, but rather tailored to the actual heat generation of each device within the tank and its potential operational status over a future period. This improves the cooling effect on the heat-generating equipment. In addition, simulating the effect of the coolant flow strategy within the tank allows for the timely detection of uneven cooling. By developing corresponding auxiliary cooling strategies for uneven cooling and employing a synergistic cooling approach, the accuracy, dynamic adaptability, and operational reliability of the liquid cooling tank's heat dissipation are improved, thereby enhancing heat dissipation and reducing the probability of a decrease in computing power due to equipment throttling protection.

[0021] By analyzing the distance between the heat dissipation edge line of the affected equipment and the integration edge line of the abnormal integration area, it is easier to accurately determine the risk range of the affected equipment that may be affected by the spread of heat, rather than making a general judgment on whether the equipment in the entire cooling tank is threatened. The distance makes it easier to prioritize the degree of risk faced by the affected equipment. When the degree of risk is high, the integration edge line of the abnormal integration area makes it easier to screen out the support cooling equipment with the closest distance, thereby shortening the support and protection response time. The support cooling strategy is determined by the outward expansion rate and the edge line contact interval, which makes it easier to dynamically trigger support according to the urgency of the risk, thereby avoiding the problem of over- or under-protection. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a data center immersion liquid cooling control method according to an embodiment of this application; Figure 2 This is a flowchart illustrating a method for determining a cooling strategy in an embodiment of this application. Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0023] The following is in conjunction with the appendix Figures 1 to 3 This application will be described in further detail.

[0024] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0027] Specifically, this application provides a data center immersion liquid cooling control method, executed by an electronic device. This electronic device can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this connection.

[0028] refer to Figure 1 , Figure 1 This is a flowchart illustrating a data center immersion liquid cooling control method according to an embodiment of this application. The method includes steps S110-S150, wherein: Step S110: Obtain the heating parameters of each heating device in the liquid cooling tank and the operating parameters corresponding to the preset time period, and determine the coolant flow strategy corresponding to the liquid cooling tank based on the heating parameters and operating parameters of each heating device.

[0029] Specifically, heat-generating devices refer to equipment within a data center that generates heat due to participating in data processing and related tasks. These devices can include server CPUs, GPUs, switches, routers, and computing acceleration devices. The specific heat-generating devices are not specifically limited in this embodiment and can be set and analyzed according to actual conditions. Heat generation parameters characterize the specific heat generation of the devices. These parameters may include, but are not limited to, the actual temperature of each heat-generating component and the relative position of each component within the corresponding heat-generating device. These parameters can be recorded by relevant personnel based on the actual conditions of each heat-generating device within the liquid cooling tank and uploaded to the electronic equipment. The preset time period is a period of time following the current moment. The duration of the preset time period can be 2 hours or 3 hours; the specific duration is not specifically limited in this embodiment. The working parameters corresponding to the preset time period are the data processing-related tasks that the heat-generating devices need to perform in the future. These working parameters include, but are not limited to, the task volume, task type, and task load rhythm. These parameters can be uploaded to the electronic equipment in advance by relevant personnel based on the actual allocation of each heat-generating device and historical task execution data.

[0030] After coolant is injected into the liquid cooling tank, the heat-generating equipment immersed in the tank can be cooled. To improve the cooling effect and ensure safety during the cooling process, a base liquid with high specific heat capacity, low viscosity, good chemical stability, and electrical insulation properties, such as deionized water and fluorinated liquid, can be selected, and appropriate additives can be added to improve the heat dissipation performance, corrosion resistance, and antimicrobial growth performance of the coolant. At the same time, a comprehensive performance test of the coolant is required before use, including but not limited to thermal conductivity test, compatibility test with metal materials, and electrical insulation performance test, to ensure that the coolant can meet the long-term stable operation requirements of the complex environment of the data center.

[0031] When determining the coolant flow strategy for the liquid cooling tank based on the heating parameters and operating parameters of each heating device, the water level of the coolant in the liquid cooling tank can be determined first based on the relative position of each heating element in the corresponding heating device, ensuring that the coolant can completely immerse each heating element of each heating device. Then, based on the historical heating response characteristics of each heating element in each heating device, the operating parameters faced by each heating device in a preset time period are converted into the predicted temperature of each heating element. The specific implementation process of determining the predicted temperature can be achieved using model prediction or empirical analysis, etc., and is not specifically limited in this embodiment. The historical heating response characteristics of the heating elements refer to the temperature change law of the heating elements under different workloads. The heating level of each heating device is determined based on the actual temperature and predicted temperature of each heating element in each heating device. Then, based on the device spacing and heating level of each heating device in the liquid cooling tank, the flow rate and temperature of the coolant in the liquid cooling tank are determined. Finally, the coolant flow strategy corresponding to the liquid cooling tank is determined based on the water level, flow rate, and temperature of the coolant in the liquid cooling tank.

[0032] Step S120: Determine the heat distribution diagram corresponding to the liquid cooling tank based on the heat parameters of each heat-generating device.

[0033] Step S130: Based on the cooling flow strategy, drive the simulated liquid cooling tank model corresponding to the liquid cooling tank and determine the cooling distribution diagram corresponding to the coolant flow strategy.

[0034] Specifically, after determining the coolant flow strategy, the liquid cooling tank is not directly drained based on the coolant flow strategy. Instead, the cooling effect needs to be predicted and analyzed before the strategy is actually implemented. The specific method is as follows: the heat situation in the liquid cooling tank is determined based on the actual heat situation and predicted heat situation of each heat-generating device. The cooling situation during the coolant flow process is simulated based on the coolant flow strategy. The heat situation and the cooling situation are superimposed and analyzed. The cooling effect of the coolant flow strategy can be evaluated based on the superposition result.

[0035] The process of determining the heat distribution map of the liquid cooling tank based on the heat parameters of each heat-generating device involves transforming the discrete heat data of each heat-generating device into a visualized spatial heat distribution. This is achieved through three steps: parameter standardization, spatial coordinate mapping, and heat distribution hierarchical rendering. The specific process is as follows: Parameter standardization: For the actual temperature in the heating parameters, outliers are removed, and missing data is supplemented by weighted average of the average of 5 consecutive data points and the average temperature of similar equipment under the same load, ensuring that the actual temperature data is continuous and reliable; For the relative positions of heating components, they are uniformly converted into three-dimensional absolute coordinates within the liquid cooling tank. That is, with the lower left corner of the liquid cooling tank as the origin, the absolute coordinates of each component are calculated based on the position of each heating device within the liquid cooling tank and the relative offset of each component within the corresponding heating device, ensuring that the position data of each component can be directly mapped to the space inside the liquid cooling tank; Spatial coordinate mapping: The liquid cooling tank is divided into multiple three-dimensional grid cells according to a preset division ratio. Each grid cell corresponds to a unique coordinate interval. The absolute coordinates of each component are matched to the corresponding three-dimensional grid cell. If a single three-dimensional grid cell contains multiple heat-generating components, the weighted average of the temperatures of all components is taken as the grid temperature. The weight is based on the proportion of heat flux density of each heat-generating component, with higher heat flux density resulting in greater weight. If there are no heat-generating components in a three-dimensional grid cell, such as in the gap area between equipment, the temperature can be calculated using distance-weighted interpolation. That is, the grid temperature of adjacent three-dimensional grid cells can be referenced, with closer proximity resulting in greater weight, thus avoiding data gaps. Thermal grading rendering: Based on preset color allocation principles, the mesh temperature is divided into multiple temperature ranges, and a corresponding color is matched for each temperature range. For example, when the temperature range is below 50 degrees Celsius, the corresponding color is blue; when the temperature range is 51-65 degrees Celsius, the corresponding color is light blue; and when the temperature range is 66-75 degrees Celsius, the corresponding color is yellow. The specific preset color allocation principles are not limited in this embodiment.

[0036] The process of generating a cooling distribution map based on a simulated liquid cooling tank model driven by a cooling flow strategy is essentially about reproducing the actual flow state and heat dissipation effect of the coolant using a digital twin, transforming the abstract coolant flow strategy into a visualized cooling distribution. The specific steps are as follows: Using the physical structure of a liquid-cooled tank as a prototype, a three-dimensional geometric model is constructed in a preset simulation software, including the internal cavity dimensions of the tank, the spatial layout of the heating devices, and the coolant flow channels. The preset simulation software can be ANSYS Fluent, COMSOL, etc., and the specific software is not limited. The absolute coordinates of each heating element are used as parameters of the model and assigned to the device model at the corresponding location. Based on the actual characteristics and flow strategy of the coolant, the actual flow path of the coolant is simulated in the model to obtain the corresponding cooling distribution map. Since the number of heating devices set in different locations is different, there may be areas with different flow rates and different cooling effects. In order to intuitively show the cooling effect at each location, a cold zone hierarchical rendering method can also be used. For details, please refer to the process of hot zone hierarchical rendering in the above embodiment, which will not be elaborated here.

[0037] Step S140: Based on the heat distribution map and the cooling distribution map, determine the abnormal heat dissipation area and the abnormal cooling area.

[0038] Specifically, the heat dissipation map and the cooling distribution map are overlaid to obtain an overlaid distribution map. Based on preset abnormal temperature values ​​and preset abnormal cooling values, or by color recognition, abnormal heat dissipation areas and abnormal cooling areas can be determined from the overlaid distribution map. For example, areas in the overlaid distribution map that are higher than the preset abnormal temperature value can be identified as abnormal heat dissipation areas, indicating poor heat dissipation in these areas. Areas in the overlaid distribution map that are lower than the preset abnormal cooling value can be identified as abnormal cooling areas, indicating excessive cooling in these areas. The specific preset abnormal temperature value and preset abnormal cooling value are not specifically limited in this embodiment of the application.

[0039] Step S150: Determine an auxiliary cooling strategy based on the abnormal heat dissipation area and the abnormal cooling area, and perform cooling treatment on all heat-generating equipment in the liquid cooling tank based on the coolant flow strategy and the auxiliary cooling strategy.

[0040] Specifically, after identifying and characterizing the abnormal heat dissipation and abnormal cooling areas, if a coolant flow strategy is used to cool the heat-generating equipment immersed in the liquid cooling tank, some heat-generating equipment may not achieve effective cooling. This can be improved by lowering the coolant temperature or increasing the flow rate. However, this improvement method only ensures effective cooling for the heat-generating equipment that has not yet achieved cooling, but may result in wasted cooling resources. Furthermore, excessively low cooling temperatures may affect the computing performance of various heat-generating devices in the data center. Therefore, this application can also determine corresponding auxiliary cooling strategies based on the abnormal heat dissipation and abnormal cooling areas. Ultimately, all heat-generating equipment in the liquid cooling tank is cooled based on both the coolant flow strategy and the auxiliary cooling strategy. Further, to facilitate precise cooling while minimizing the impact on other non-abnormal heat-generating equipment in the liquid cooling tank, auxiliary cooling strategies are determined based on the abnormal heat dissipation and abnormal cooling areas. These strategies may include: The abnormal heat dissipation area and abnormal heat dissipation value of abnormal heat dissipation regions are identified from the heat dissipation distribution map, and the abnormal cooling area of ​​abnormal cooling regions is identified from the cooling distribution map. The stirring frequency is determined based on the ratio of abnormal heat dissipation area to abnormal cooling area. The stirring direction is determined based on the abnormal heat dissipation region and the abnormal cooling region. The stirring-assisted cooling strategy is determined based on the stirring direction and stirring frequency. The stirring-assisted cooling strategy is used to control the stirring rod in the liquid cooling tank to stir and cool the coolant. The abnormal heat dissipation equipment corresponding to the abnormal heat dissipation region is identified. A micro-channel cooling auxiliary strategy is generated based on the abnormal heat dissipation area and abnormal heat dissipation value. The micro-channel cooling auxiliary strategy is used to control the external micro-channel of the abnormal heat dissipation equipment to perform auxiliary cooling. The stirring-assisted cooling strategy and the micro-channel cooling auxiliary strategy constitute the auxiliary cooling strategy.

[0041] Specifically, the abnormal heat dissipation area and abnormal heat dissipation value of abnormal heat dissipation areas can be identified from the heat distribution map using a preset feature recognition algorithm. Similarly, the abnormal cooling area of ​​abnormal cooling areas can be identified from the cooling distribution map using a preset feature recognition algorithm. The specific preset feature recognition algorithm is not limited in this embodiment. The sum of the abnormal heat dissipation areas of all abnormal heat dissipation areas is calculated to obtain the total abnormal heat dissipation area. The sum of the abnormal cooling areas of all abnormal cooling areas is calculated to obtain the total abnormal cooling area. The ratio of the total abnormal heat dissipation area to the total abnormal cooling area is calculated to obtain the abnormal proportion. Then, the stirring frequency corresponding to this abnormal proportion is determined according to a preset frequency mapping relationship. The preset frequency mapping relationship is the correspondence between the abnormal proportion and the stirring frequency; the smaller the abnormal proportion, the larger the corresponding stirring frequency. The specific content of the preset frequency mapping relationship is not limited in this embodiment and can be determined by relevant personnel based on historical experimental data and uploaded to the electronic device. The abnormal heat dissipation locations of each abnormal heat dissipation area within the liquid cooling tank are identified, and the heat dissipation concentration areas of all abnormal heat dissipation areas are determined based on these locations. The center point of each heat dissipation concentration area is then identified as the abnormal heat dissipation point. Based on this method, the abnormal cooling points corresponding to each abnormal cooling area can be obtained. The stirring direction is determined based on the abnormal cooling points and the abnormal heat dissipation points. Finally, a stirring-assisted cooling strategy is generated to control the stirring rods installed inside the liquid cooling tank to stir the coolant along the stirring direction, thereby increasing the flow of the coolant within the liquid cooling tank. This facilitates the use of the low temperature conditions of the abnormal cooling areas to balance the high temperature conditions of the abnormal heat dissipation areas, and improves the cooling effect through internal stirring.

[0042] In addition, a microchannel cooling auxiliary strategy corresponding to the abnormal heat dissipation area and abnormal heat dissipation value can be determined according to a preset auxiliary strategy mapping relationship. The preset auxiliary strategy mapping relationship is the correspondence between the parameter combination of the abnormal heat dissipation area and abnormal heat dissipation value and the microchannel cooling auxiliary strategy. The specific content of the preset auxiliary strategy mapping relationship is not specifically limited in this application embodiment, and can be determined by relevant personnel based on historical experimental data and uploaded to the electronic device. The microchannel cooling auxiliary strategy is used to control the microchannels of the abnormal heat dissipation device's external device within the abnormal heat dissipation area to provide auxiliary cooling for the abnormal heat dissipation area, that is, for the abnormal heat dissipation device, so as to improve the cooling effect of the heat dissipation device itself while reducing the impact on other non-abnormal heat dissipation devices. In this application embodiment, microchannel heat dissipation technology is used to set microchannels on the surface of each heat dissipation device. Each microchannel has a corresponding valve and is connected to a coolant pump. When using microchannels to cool the heat dissipation device, the coolant flows into the microchannel through the coolant pump, which is independent of the coolant in the liquid cooling tank, so as to increase the contact area between the coolant and the heat dissipation device, thereby improving the heat exchange efficiency. The auxiliary cooling strategy is composed of a stirring-assisted cooling strategy and a microchannel cooling auxiliary strategy.

[0043] In this embodiment, the data center's heat-generating equipment is immersed in a liquid cooling tank, using direct immersion and close contact with the cold plate for cooling. This eliminates the multi-stage thermal resistance of air, heat sinks, and chips in air cooling, thereby improving cooling efficiency. Furthermore, the coolant flow strategy for the liquid cooling tank is not a fixed approach, but rather tailored to the actual heat generation of each heat-generating device within the tank and its potential operational status over a future period. This improves the cooling effect on the heat-generating equipment. Additionally, simulating the effect of the coolant flow strategy within the tank allows for the timely detection of uneven cooling. By developing corresponding auxiliary cooling strategies for uneven cooling and employing a synergistic cooling approach, the accuracy, dynamic adaptability, and operational reliability of the liquid cooling tank's heat dissipation are improved, thereby enhancing heat dissipation and reducing the probability of reduced computing power due to frequency throttling protection.

[0044] Furthermore, when there are multiple abnormal heat dissipation areas, the method provided in this application embodiment further includes: Identify the abnormal heat dissipation edges of each abnormal heat dissipation area, and determine the abnormal integration area corresponding to all abnormal heat dissipation areas based on each abnormal heat dissipation edge; identify the abnormal integration distribution map corresponding to the abnormal integration area from the heat distribution map, and identify the outward expansion rate and outward expansion direction of the abnormal integration distribution map; identify the auxiliary cooling devices in the abnormal integration area, and determine the integrated auxiliary cooling strategy corresponding to the auxiliary cooling devices based on the outward expansion rate and outward expansion direction of the abnormal integration distribution map.

[0045] Specifically, if there are multiple abnormal heat dissipation areas within a unit time period, it is necessary to combine all abnormal heat dissipation areas for comprehensive analysis to avoid heat migration or secondary heat accumulation problems caused by isolating and cooling a single abnormal heat dissipation area. The abnormal heat dissipation edges of each abnormal heat dissipation area can be identified using a preset feature recognition algorithm. By stitching together the edge points of each abnormal heat dissipation edge, an abnormal integrated area corresponding to all abnormal heat dissipation areas can be obtained. The abnormal integrated area contains at least all abnormal heat dissipation areas. The integrated edge line of the abnormal integrated area is identified, and then an abnormal integrated distribution map is extracted from the heat distribution map based on the preset feature recognition algorithm and the integrated edge line. The preset feature recognition algorithm is not specifically limited in this embodiment. Multiple abnormal integrated distribution maps are continuously extracted by the real-time changing integrated edge line to facilitate the determination of the outward expansion rate and direction of the abnormal integrated distribution map. At this time, it is necessary to determine the integrated auxiliary cooling strategy corresponding to the outward expansion rate and direction based on the preset auxiliary cooling strategy mapping relationship. The integrated auxiliary cooling strategy is used to control the micro-channels of the auxiliary cooling device peripherals within the abnormal integrated area to provide auxiliary cooling to the interior of the abnormal integrated area, so as to reduce the abnormal temperature expansion of the abnormal integrated area from the source.

[0046] By identifying the edges of each abnormal heat dissipation area and integrating them into an abnormal integration area, it is easier to discover the possible correlation between multiple scattered abnormal heat dissipation areas, thus avoiding heat migration or secondary heat accumulation problems caused by isolating and cooling a single abnormal heat dissipation area.

[0047] Furthermore, to facilitate the clear identification of the required auxiliary cooling intensity for the abnormal integration area, when determining the integration auxiliary cooling strategy corresponding to the auxiliary cooling equipment based on the outward expansion rate and direction of the abnormal integration distribution map, it may specifically include: When the outward expansion rate exceeds a preset rate threshold, identify the outward expansion-affected devices corresponding to the outward expansion direction. These affected devices are heat-generating devices located along the corresponding outward expansion path. Identify the device level and heat generation parameters of each affected device, and determine the abnormal device level of each affected device based on the device level and heat generation parameters. Based on the abnormal device levels of each affected device within the abnormal integration area, determine the regional abnormality level of the abnormal integration area. Based on the regional abnormality level and the number of auxiliary cooling devices, determine the corresponding integration auxiliary cooling strategy for the abnormal integration area.

[0048] Specifically, when the outward expansion rate exceeds a preset rate threshold, it indicates a severe outward expansion of abnormal temperature within the abnormal integration area. In this case, simply providing auxiliary cooling from within the abnormal integration area may be insufficient to control the outward expansion in a timely manner. Therefore, the outward expansion direction can be used to determine whether highly affected devices are included. To identify affected devices, the corresponding outward expansion route can be determined based on the outward expansion direction and a preset path width. Heating devices located along this route are identified as affected devices. That is, after the abnormal integration area continues to expand, affected devices will be the first to be affected. The preset path width is not specifically limited in this embodiment. After identifying affected devices, the abnormal device level corresponding to each affected device can be determined by analyzing its device level and heating parameters. Finally, the abnormal device levels of all affected devices are summed to determine the regional abnormality level corresponding to the abnormal integration area. The abnormal device level corresponding to different device levels and heating parameters can be determined based on a preset device level mapping relationship, which is the correspondence between the combination of device level and heating parameters and the abnormal device level. After determining the regional anomaly level of the abnormal integration area, the integrated auxiliary cooling strategy corresponding to the regional anomaly level and the number of auxiliary cooling devices is determined according to the preset integrated auxiliary cooling strategy mapping relationship. The preset integrated auxiliary cooling strategy mapping relationship is the correspondence between the combination of regional anomaly level and the number of auxiliary cooling devices and the integrated auxiliary cooling strategy. The specific content of the preset device level mapping relationship and the preset integrated auxiliary cooling strategy mapping relationship is not specifically limited in this application embodiment, and can be determined by relevant personnel based on experimental data and uploaded to electronic equipment.

[0049] Furthermore, when the extended affected devices include devices of interest, the method provided in this application embodiment further includes steps S210-S240, such as... Figure 2 As shown, where: Step S210: Identify the heat dissipation edge line of the corresponding heat dissipation area of ​​the device of interest from the heat distribution map.

[0050] Specifically, the devices of concern are those whose abnormality level exceeds a preset threshold. An abnormality in these devices could cause significant damage to the data center. Therefore, when these devices are included in the expanded impact list, customized cooling measures are needed to ensure their stable operation. The specific value of the preset threshold is not limited in this embodiment and can be set by relevant personnel according to actual needs. The heat dissipation edge line of the corresponding heat dissipation area of ​​the device of concern can be identified from the heat distribution map using a preset feature recognition algorithm. The specific preset feature recognition algorithm is not limited in this embodiment.

[0051] Step S220: Identify the integration edge line of the abnormal integration area, and determine the supporting cooling device based on the integration edge line. The interval distance between the supporting cooling device and the integration edge line is less than a preset interval distance threshold.

[0052] Specifically, based on the aforementioned method for determining the heat dissipation edge line, the integration edge line of the abnormal integration area can be identified. The specific process will not be elaborated here. Supporting cooling devices are identified near the integration edge line based on a preset interval distance threshold. If the interval distance between the supporting cooling device and the integration edge line is less than the preset interval distance threshold, the supporting cooling device may be using microchannels for auxiliary cooling, or it may not be using its own microchannels for auxiliary cooling. Because the abnormal devices affecting the device have a higher priority, the cooling strategies ensuring their stable execution also have a higher priority. The relevant executing devices, i.e., the supporting cooling devices, also have a higher priority. When a supporting cooling device is using microchannels for auxiliary cooling, after identifying the heat-generating device as a supporting cooling device, the currently executing auxiliary cooling strategy needs to be stopped immediately, and the electronic equipment needs to be allowed to reallocate a new cooling strategy.

[0053] Step S230: Determine the edge line contact interval between the heat dissipation edge line and the integration edge line.

[0054] Specifically, the contact interval between the heat dissipation edge line and the integration edge line can be determined by methods such as the discrete point distance method, the perpendicular line segment distance method, and the buffer analysis method. The specific implementation method is not specifically limited in this application embodiment. When using the discrete point distance method, the discrete points on the heat dissipation edge line and the integration edge line can be paired according to the principle of spatial proximity. Then, the straight-line distance of each pair of matched points can be calculated using the Euclidean distance formula. Finally, the average of the distances of all point pairs can be taken to obtain the contact interval between the heat dissipation edge line and the integration edge line.

[0055] Step S240: When the edge line contact interval is less than the preset contact interval, a support cooling strategy is determined based on the outward expansion rate and the edge line contact interval. The support cooling strategy is used to control the microchannels of the support device to perform support cooling.

[0056] Specifically, the support cooling strategy corresponding to the expansion rate and edge line contact interval can be determined according to the preset support cooling strategy mapping relationship. The preset support cooling strategy mapping relationship is the correspondence between the combination of expansion rate and edge line contact interval and the support cooling strategy. The specific content of the preset support cooling strategy mapping relationship is not specifically limited in this embodiment of the application, and can be determined by relevant personnel based on experimental data and then uploaded to the electronic device. After the support cooling strategy is determined, the microchannels of each support device are controlled to perform support cooling near the integration edge line, so as to slow down the expansion rate of the integration edge line.

[0057] In this embodiment of the application, by analyzing the distance between the heat dissipation edge line of the device of concern and the integration edge line of the abnormal integration area, it is convenient to accurately determine the risk range of the device of concern that may be affected by the spread of heat, rather than making a general judgment on whether the equipment in the entire cooling tank is threatened. The distance makes it easy to prioritize the degree of risk faced by the device of concern. When the degree of risk is high, the integration edge line of the abnormal integration area makes it easy to screen out the support cooling equipment with the closest distance, thereby shortening the support protection response time. The support cooling strategy is determined by the outward expansion rate and the edge line contact interval, which makes it easy to dynamically trigger support according to the urgency of the risk, thereby avoiding the problem of over- or under-protection.

[0058] Furthermore, to ensure the stability of the cooling effect of the liquid cooling tank, the method provided in this application embodiment also includes: Acquire each abnormal integration region and abnormal integration image recorded within a preset integration time period, and determine the intersection region of all abnormal integration regions based on each abnormal integration image; identify the impurity accumulation area corresponding to the liquid cooling tank within the preset integration time period, and identify the accumulation area of ​​the impurity accumulation area; when the accumulation area is greater than a preset area threshold, and the area distance between the impurity accumulation area and the intersection region is less than a preset area distance threshold, generate an impurity cleaning instruction based on the impurity accumulation area and the accumulation area. The impurity cleaning instruction is used to remind relevant personnel to clean the impurities in the liquid cooling tank.

[0059] Specifically, the preset integration time period is a period of time prior to the current moment. The duration of the preset integration time period can be 24 hours or 36 hours. The specific duration is not specifically limited in this embodiment and can be set by relevant personnel according to actual needs. The abnormal integration image is a real-shot image inside the liquid cooling tank corresponding to the abnormal integration area. The real-shot image can be an infrared thermal image or a high-definition visible light image. The specific image type is not limited in this embodiment. To improve the accuracy of determining the intersection area, before determining the intersection area of ​​all abnormal integration areas based on each abnormal integration image, the abnormal integration image can be preprocessed with image enhancement. For example, when the abnormal integration image is an infrared thermal image, the contrast of the hot area can be enhanced by grayscale stretching. A temperature threshold can be set, and the outline of the thermal anomaly area in the abnormal integration image can be automatically extracted and converted into image pixel coordinates. Then, according to the image calibration information, the extracted image pixel coordinates are converted into physical coordinates inside the liquid cooling tank to ensure that the spatial range of the extracted image area is consistent with the abnormal integration area data.

[0060] By overlaying all the anomalous integrated images after image enhancement preprocessing, the intersection area of ​​all anomalous integrated regions can be determined. Besides using layer overlay to determine the intersection area, contour intersection operations can also be used. The specific method for determining the intersection area is not limited in this embodiment. The impurity accumulation area and its area within a preset integration time period can be determined from the intersection area image corresponding to the intersection area through feature recognition. In addition, impurity monitoring data of the liquid cooling tank within the preset integration time period can be collected and combined with ultrasonic sensor data to supplement the identification of impurities in areas not covered by the image, merging them into a complete impurity accumulation area, and calculating the accumulation area. The specific method for determining the impurity accumulation area and its area is not specifically limited in this embodiment.

[0061] When the accumulated area exceeds a preset area threshold, it indicates that the impurities accumulated in the liquid cooling tank have significantly affected the cooling effect of the corresponding area. When the distance between the impurity accumulation area and the intersection area is less than a preset distance threshold, it indicates that the impurities accumulated in the liquid cooling tank will significantly exacerbate the abnormal heat dissipation in the intersection area. In this case, it is necessary to generate an impurity cleaning instruction based on the impurity accumulation area and the accumulated area to remind relevant personnel to clean the impurities in the liquid cooling tank in a timely manner. The method for determining the distance between the impurity accumulation area and the intersection area can refer to the method for determining the edge contact interval between the heat dissipation edge line and the integration edge line in the above embodiment, and will not be elaborated here.

[0062] By acquiring the intersection of all abnormal integration areas within a preset time period, it is easier to locate the core area in the liquid cooling tank where thermal anomalies occur repeatedly over a long period of time. By correlating the impurity accumulation area with the intersection area, it is easier to determine whether the impurities are a potential cause of the thermal anomalies. A cleaning instruction is only generated when the impurity accumulation area exceeds the standard and is close to a high-risk intersection area. This avoids frequent shutdowns for cleaning due to a small amount of impurities and delays in processing due to excessive impurities. By improving the targeting of impurity cleaning, it is easier to ensure the stability of the cooling effect of the liquid cooling tank.

[0063] This application provides an electronic device, such as... Figure 3 As shown, Figure 3 The illustrated electronic device 300 includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one type, and the structure of this electronic device 300 does not constitute a limitation on the embodiments of this application.

[0064] Processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0065] Bus 302 may include a pathway for transmitting information between the aforementioned components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 302 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by only one line, but this does not mean that there is only one bus or one type of bus.

[0066] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0067] The memory 303 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0068] Electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Servers can also be included. Figure 3 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0069] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0070] This application provides a computer program product including a computer program that, when executed by a processor, implements the methods described in any of the above embodiments.

[0071] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0072] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method of data center immersion liquid cooling control, comprising: The method comprises the following steps: acquiring heat generation parameters of each heat-generating device in a liquid cooling tank and working parameters corresponding to a preset time period, and determining a cooling liquid flow strategy of the liquid cooling tank based on the heat generation parameters and the working parameters of each heat-generating device; determining a heat distribution map of the liquid cooling tank based on the heat generation parameters of each heat-generating device; driving a simulated liquid cooling tank model corresponding to the liquid cooling tank based on the cooling flow strategy to determine a cooling distribution map corresponding to the cooling liquid flow strategy; determining an abnormal heat dissipation area and an abnormal cooling area based on the heat distribution map and the cooling distribution map; determining an auxiliary cooling strategy based on the abnormal heat dissipation area and the abnormal cooling area, and performing cooling treatment on all heat-generating devices in the liquid cooling tank based on the cooling liquid flow strategy and the auxiliary cooling strategy.

2. The data center immersion liquid cooling control method of claim 1, wherein, The method of determining the auxiliary cooling strategy based on the abnormal heat dissipation area and the abnormal cooling area comprises the following steps: identifying an abnormal heat dissipation area and an abnormal cooling area from the heat distribution map and the cooling distribution map; determining a stirring frequency based on the ratio of the abnormal heat dissipation area to the abnormal cooling area; determining a stirring direction based on the abnormal heat dissipation area and the abnormal cooling area, and determining a stirring auxiliary cooling strategy based on the stirring direction and the stirring frequency, wherein the stirring auxiliary cooling strategy is used to control a stirring rod in the liquid cooling tank to stir the cooling liquid for cooling; identifying an abnormal heat-generating device corresponding to the abnormal heat dissipation area, and generating a micro-pipe cooling auxiliary strategy based on the abnormal heat dissipation area and the abnormal heat dissipation value, wherein the micro-pipe cooling auxiliary strategy is used to control a micro-pipe external to the abnormal heat-generating device to perform auxiliary cooling; The stirring auxiliary cooling strategy and the micro-pipe cooling auxiliary strategy constitute the auxiliary cooling strategy.

3. The data center immersion liquid cooling control method of claim 2, wherein, When there are multiple abnormal heat dissipation areas, the method further comprises the following steps: identifying an abnormal heat dissipation edge of each abnormal heat dissipation area, and determining an abnormal integrated area corresponding to all abnormal heat dissipation areas based on the abnormal heat dissipation edges; identifying an abnormal integrated distribution map corresponding to the abnormal integrated area from the heat distribution map, and identifying an expansion rate and an expansion direction of the abnormal integrated distribution map; identifying an auxiliary cooling device in the abnormal integrated area, and determining an integrated auxiliary cooling strategy corresponding to the auxiliary cooling device based on the expansion rate and the expansion direction of the abnormal integrated distribution map.

4. The data center immersion liquid cooling control method of claim 3, wherein, The method of determining the integrated auxiliary cooling strategy corresponding to the auxiliary cooling device based on the expansion rate and the expansion direction of the abnormal integrated distribution map comprises the following steps: when the expansion rate is higher than a preset rate threshold, identifying an expansion impact device corresponding to the expansion direction, wherein the expansion impact device is a heat-generating device located on an expansion route corresponding to the expansion direction; identifying a device level and a heat generation parameter of each expansion impact device, and determining an abnormal device level of each expansion impact device based on the device level and the heat generation parameter; determining a regional abnormal level of the abnormal integrated area based on the abnormal device levels of each expansion impact device in the abnormal integrated area; Determine an integrated auxiliary cooling strategy corresponding to the abnormal integrated area based on the abnormality level of the area and the number of auxiliary cooling devices.

5. The data center immersion liquid cooling control method of claim 4, wherein, When the expansion influence device includes a focus influence device, further comprising: Identify a heat dissipation edge line of a heat dissipation area corresponding to the focus influence device from the heat distribution map; Identify an integrated edge line of the abnormal integrated area, and determine a support cooling device based on the integrated edge line, the support cooling device having a distance to the integrated edge line less than a preset distance threshold; Determine an edge line contact interval between the heat dissipation edge line and the integrated edge line; When the edge line contact interval is less than a preset contact interval, determine a support cooling strategy based on the expansion rate and the edge line contact interval, the support cooling strategy being used to control the support device peripheral micro-pipe to perform support cooling.

6. The data center immersion liquid cooling control method of claim 3, wherein, Further comprising: Obtain each abnormal integrated area and abnormal integrated image recorded in a preset integrated time period, and determine an intersection area of all abnormal integrated areas based on each abnormal integrated image; Identify a foreign matter accumulation area of the liquid cooling tank corresponding to the preset integrated time period, and identify an accumulation area of the foreign matter accumulation area; When the accumulation area is greater than a preset area threshold, and the distance between the foreign matter accumulation area and the intersection area is less than a preset area distance threshold, generate a foreign matter cleaning instruction based on the foreign matter accumulation area and the accumulation area, the foreign matter cleaning instruction being used to remind relevant staff to clean the foreign matter of the liquid cooling tank.

7. An electronic device, comprising: The electronic device includes: At least one processor; Memory; At least one application program, wherein the at least one application program is stored in the memory and is configured to be executed by the at least one processor, and the at least one application program is configured to execute the data center immersion liquid cooling control method of any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, Including: The computer program is stored and can be loaded and executed by the processor to perform the data center immersion liquid cooling control method of any one of claims 1-6.

9. A computer program product, characterised in that, The computer program is executed by the processor to implement the steps of the data center immersion liquid cooling control method of any one of claims 1-6.

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