Server cooling system and method based on liquid cooling convection and related equipment

Abstract

The invention relates to a server cooling system and method based on liquid cooling convection and related equipment. The server cooling system based on liquid cooling convection comprises a liquid cooling module, a temperature monitoring module, a liquid cooling control module, a temperature prediction module and a leakage monitoring module, and the liquid cooling module is used for performing liquid cooling on a server; the temperature monitoring module is used for monitoring temperature data of the server in real time and inputting the temperature data to the temperature prediction module and the liquid cooling control module; the temperature prediction module is used for presetting a timestamp, calculating a temperature change rate according to the temperature data and the timestamp, and inputting the temperature change rate to the liquid cooling control module; the liquid cooling control module generates a liquid cooling control instruction according to the temperature data and the temperature change rate, and controls the liquid cooling module to execute cooling work according to the liquid cooling control instruction; the leakage monitoring device is used for monitoring the air pressure leakage condition in the server. The method has the effect of improving the working performance of the server.

Description

Technical Field

[0001] The present application relates to the technical field of server heat dissipation, and in particular to a server cooling system, method and related equipment based on liquid cooling convection. Background Art

[0002] During the operation of the server system, the CPU, memory and other components need to process a large amount of data, which makes them the main source of heat. If the heat generated by the server components cannot be dissipated in time, the server system will overheat, thus affecting its normal operation. Server overheating will not only reduce the performance of the server, making it unable to meet the needs of real-time processing and storage of data, but also shorten the service life of the server and may even cause the system to crash, causing huge economic losses to enterprises and organizations. In order to ensure the normal operation of the server, effective heat dissipation measures must be taken. At present, many servers use the traditional heat dissipation method of fan radiators to dissipate the heat generated during operation.

[0003] Regarding the above-mentioned related technologies, there are the following defects: the performance of server systems is constantly improving, and traditional heat dissipation methods (fan heat sinks) are often difficult to meet the heat dissipation requirements of high-density, high-performance servers. In addition, as server systems develop towards higher efficiency and smaller size, traditional heat dissipation methods have been unable to meet the heat dissipation requirements of servers, thereby reducing the working performance of the servers. Summary of the invention

[0004] In order to improve the working performance of the server, the present application provides a server cooling system, method and related equipment based on liquid cooling convection.

[0005] In the first aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions: A server cooling system based on liquid cooling convection includes a liquid cooling module, a temperature monitoring module, a liquid cooling control module, a temperature prediction module and a leakage monitoring module, wherein the liquid cooling module is used to perform liquid cooling on the server; the temperature monitoring module is used to monitor the temperature data of the server in real time, and input the temperature data into the temperature prediction module and the liquid cooling control module; the temperature prediction module is used to preset a timestamp, calculate the temperature change rate according to the temperature data and the timestamp, and input the temperature change rate into the liquid cooling control module; the liquid cooling control module generates a liquid cooling control instruction according to the temperature data and the temperature change rate, and controls the liquid cooling module to perform cooling according to the liquid cooling control instruction; the leakage monitoring device is used to monitor the air pressure leakage in the server.

[0006] By adopting the above technical solution, the temperature data of the server can be monitored in real time, and the working status and temperature changes of the server can be understood in time, which is helpful for early warning and taking measures to prevent overheating and reduce the temperature of the server. By predicting the temperature change rate, the trend and rate of the server temperature can be predicted in advance, so that the liquid cooling control module can perform more accurate control according to the prediction results and take appropriate measures to reduce the temperature of the server. Liquid cooling control instructions are generated according to temperature data and temperature change rate. The liquid cooling control module can realize precise control of the liquid cooling system, improve the cooling effect, ensure that the server operates within the appropriate temperature range, and avoid overheating or overcooling. Among them, the liquid cooling process uses liquid for heat convection to take away the heat of various components of the server. Through the cooperation of the liquid cooling control module and the liquid cooling module, the cooling effect of the server is improved, so that the server is in a temperature range suitable for work, thereby improving the work efficiency and performance of the server.

[0007] Optionally, the cooling system further includes a data storage module, which is used to preset a historical liquid cooling heat dissipation database to record temperature data and temperature change rate when the liquid cooling module executes liquid cooling control instructions.

[0008] By adopting the above technical solution, the temperature data and temperature change rate when the liquid cooling module executes the liquid cooling control instruction are recorded, and a historical temperature data set and a temperature change rate data set are established. These data sets are used to analyze the performance of the liquid cooling system and optimize the liquid cooling control strategy.

[0009] Optionally, the cooling system further includes an air pressure monitoring module, which acquires air pressure data from a monitoring server in real time and inputs the air pressure data into the leakage monitoring module.

[0010] By adopting the above technical solutions, the dimension of leakage monitoring is increased, the accuracy of leakage monitoring of server liquid cooling is improved, and leakage is discovered in time.

[0011] In the second aspect, the above invention objective of the present application is achieved through the following technical solutions: A server cooling method based on liquid cooling convection includes the following steps: The temperature monitoring module monitors the temperature data of the server in real time and inputs the temperature data into the temperature prediction module and the liquid cooling control module; The temperature prediction module is preset with a timestamp, calculates the temperature change rate according to the temperature data and the timestamp, and inputs the temperature change rate into the liquid cooling control module; The liquid cooling control module generates a liquid cooling control instruction according to the temperature data and the temperature change rate; The liquid cooling control module controls the liquid cooling module to perform cooling work according to the liquid cooling control instruction.

[0012] By adopting the above technical solution, the temperature data of the server can be monitored in real time, and the working status and temperature change of the server can be timely understood, which is helpful for early warning and taking measures to prevent overheating and reduce the temperature of the server. By predicting the temperature change rate, the trend and rate of the server temperature can be predicted in advance, so that the liquid cooling control module can perform more accurate control according to the prediction results and take appropriate measures to reduce the temperature of the server. Liquid cooling control instructions are generated according to temperature data and temperature change rate. The liquid cooling control module can realize precise control of the liquid cooling system. This can improve the cooling effect, ensure that the server operates within the appropriate temperature range, and avoid overheating or overcooling. Through the cooperation of the liquid cooling control module and the liquid cooling module, the cooling effect of the server is improved, thereby improving the work efficiency of the server.

[0013] In a preferred example, the present application can be further configured as follows: after the step in which the liquid cooling control module controls the liquid cooling module to perform the cooling operation according to the temperature data and the temperature change rate, the following steps are included: The air pressure monitoring module monitors the server in real time to obtain air pressure data, and inputs the air pressure data into the leakage monitoring module; The leakage monitoring module calculates the difference between the air pressure data and a preset reference value according to a preset air pressure calculation model, and obtains an air pressure deviation value; Determining whether the deviation value is within a preset air pressure threshold; If the deviation value is not within the air pressure threshold, an air pressure leakage alarm signal is issued.

[0014] By adopting the above technical solution, by detecting leaks in the liquid cooling system and implementing leak control measures, the loss of cooling medium and the degradation of system performance can be prevented, which helps maintain the stability and safety of the liquid cooling system and reduces the need for repair and maintenance.

[0015] In a preferred example, the present application can be further configured as follows: after the step in which the liquid cooling control module controls the liquid cooling module to perform the cooling operation according to the temperature data and the temperature change rate, the following steps are included: Inputting the liquid cooling control instruction into a preset historical liquid cooling heat dissipation database, wherein a plurality of the liquid cooling control instructions form a control instruction data set; The temperature data and the temperature change rate when the liquid cooling module executes the liquid cooling control instruction are input into the historical liquid cooling heat dissipation database, the temperature data and the temperature change rate are mapped with the corresponding liquid cooling control instruction, a number of the temperature data form a historical temperature data set, and a number of the temperature change rates form a temperature change rate data set.

[0016] By adopting the above technical solution, the temperature data and temperature change rate when the liquid cooling module executes the liquid cooling control instruction are recorded, and a historical temperature data set and a temperature change rate data set are established. These data sets are used to analyze the performance of the liquid cooling system and optimize the liquid cooling control strategy.

[0017] In a preferred example, the present application may be further configured as follows: after the temperature data and the temperature change rate when the liquid cooling module executes the liquid cooling control instruction are input into the historical liquid cooling heat dissipation database, the temperature data and the temperature change rate are mapped with the corresponding liquid cooling control instruction, a number of the temperature data form a historical temperature data set, and a number of the temperature change rates form a temperature change rate data set, the following steps are included: The preset liquid cooling optimization model retrieves the control instruction data set and the corresponding historical temperature data set and the temperature change rate data set. The liquid cooling optimization model performs self-learning on the control instruction data set based on a neural network algorithm to optimize the generation of liquid cooling control instructions.

[0018] By adopting the above technical solution and using a neural network algorithm for self-learning, the liquid cooling optimization model can generate more accurate and optimized liquid cooling control instructions based on the patterns and trends in historical data, thereby improving the cooling effect of the liquid cooling system, reducing energy consumption, and ensuring the stable operation of the server.

[0019] In a preferred example, the present application can be further configured as follows: after the step in which the liquid cooling control module controls the liquid cooling module to perform the cooling operation according to the temperature data and the temperature change rate, the following steps are included: The temperature prediction module performs data analysis on the historical temperature data set and the temperature change rate data set based on a big data algorithm, and optimizes a preset temperature change prediction model; The optimized temperature change prediction model predicts the real-time temperature data and generates predicted temperature data; Determine whether the predicted temperature data is within the preset temperature threshold; If the predicted temperature data is not within the temperature threshold, a temperature alarm signal is issued.

[0020] By adopting the above technical solution, real-time temperature data can be predicted, potential temperature increase trends or abnormal conditions can be discovered in advance, and timely measures can be taken to adjust the working state of the liquid cooling system to keep the server temperature within a safe range.

[0021] On the third aspect, the above-mentioned purpose of the present application is achieved through the following technical solutions: An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned server cooling method based on liquid cooling convection are implemented.

[0022] Fourthly, the above-mentioned purpose of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned server cooling method based on liquid cooling convection are implemented.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: 1. Real-time monitoring of the server's temperature data can timely understand the server's working status and temperature changes, which helps to provide early warning and take measures to prevent overheating and reduce the server's temperature. By predicting the temperature change rate, the trend and rate of the server's temperature can be predicted in advance, so that the liquid cooling control module can perform more accurate control based on the prediction results and take appropriate measures to reduce the server's temperature. Liquid cooling control instructions are generated based on temperature data and temperature change rate. The liquid cooling control module can achieve precise control of the liquid cooling system. This can improve the cooling effect, ensure that the server operates within the appropriate temperature range, and avoid overheating or overcooling. Through the cooperation of the liquid cooling control module and the liquid cooling module, the cooling effect of the server is improved, thereby improving the server's work efficiency; 2. By detecting leaks in the liquid cooling system and implementing leak control measures, the loss of cooling medium and the degradation of system performance can be prevented, which helps maintain the stability and safety of the liquid cooling system and reduces the need for repair and maintenance; 3. Record the temperature data and temperature change rate when the liquid cooling module executes the liquid cooling control instruction, and establish a historical temperature data set and a temperature change rate data set. These data sets are used to analyze the performance of the liquid cooling system and optimize the liquid cooling control strategy; 4. By using neural network algorithms for self-learning, the liquid cooling optimization model can generate more accurate and optimized liquid cooling control instructions based on patterns and trends in historical data, thereby improving the cooling effect of the liquid cooling system, reducing energy consumption, and ensuring the stable operation of the server. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a schematic diagram of a module framework of a server cooling system based on liquid cooling convection in the present application; Figure 2 This is a schematic diagram of the steps of a server cooling method based on liquid cooling convection in the present application; Figure 3It is a flow chart after step S40 in a server cooling method based on liquid cooling convection of the present application; Figure 4 This is a flow chart after step S402 of a server cooling method based on liquid cooling convection of the present application; Figure 5 This is a flow chart after step S40 in a server cooling method based on liquid cooling convection of the present application; Figure 6 It is a schematic diagram of the framework of an electronic device of the present application.

[0025] Description of reference numerals: 1. Liquid cooling module; 2. Temperature monitoring module; 3. Liquid cooling control module; 4. Temperature prediction module; 5. Leakage monitoring module; 6. Data storage module; 7. Air pressure monitoring module. DETAILED DESCRIPTION

[0026] The present application is further described in detail below in conjunction with the accompanying drawings.

[0027] In one embodiment, a server cooling system based on liquid cooling convection is provided, such as Figure 1 As shown, a server cooling system based on liquid cooling convection includes a liquid cooling module 1, a temperature monitoring module 2, a liquid cooling control module 3, a temperature prediction module 4 and a leakage monitoring module 5. The liquid cooling module 1 is used to perform liquid cooling on the server; the temperature monitoring module 2 is used to monitor the temperature data of the server in real time, and input the temperature data to the temperature prediction module 4 and the liquid cooling control module 3; the temperature prediction module 4 is used to preset a timestamp, calculate the temperature change rate according to the temperature data and the timestamp, and input the temperature change rate to the liquid cooling control module 3; the liquid cooling control module 3 generates a liquid cooling control instruction according to the temperature data and the temperature change rate, and controls the liquid cooling module 1 to perform the cooling work according to the liquid cooling control instruction; the leakage monitoring device is used to monitor the air pressure leakage in the server, The cooling system also includes a data storage module 6 and an air pressure monitoring module 7. The data storage module 6 is used to preset a historical liquid cooling heat dissipation database to record the temperature data and temperature change rate when the liquid cooling module 1 executes the liquid cooling control instruction. The air pressure monitoring module 7 obtains the air pressure data of the monitoring server in real time and inputs the air pressure data to the leakage monitoring module 5.

[0028] Each module in the above-mentioned server cooling system based on liquid cooling convection can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0029] In one embodiment, if Figure 2-5 As shown, the present application discloses a server cooling method based on liquid cooling convection, which specifically includes the following steps: S10: The temperature monitoring module 2 monitors the temperature data of the server in real time, and inputs the temperature data to the temperature prediction module 4 and the liquid cooling control module 3; Specifically, the temperature monitoring module 2 uses a temperature sensor to monitor the temperature of the server in real time. The sensor is installed in key parts of the server, such as the processor, memory or hard disk, to obtain accurate temperature data. The temperature data can be communicated with the control unit of the liquid cooling system through the sensor for real-time transmission and processing, so as to input the temperature data into the temperature prediction module 4 and the liquid cooling control module 3.

[0030] S20: The temperature prediction module 4 is preset with a timestamp, calculates the temperature change rate according to the temperature data and the timestamp, and inputs the temperature change rate to the liquid cooling control module 3; Specifically, the temperature prediction module 4 uses time series analysis to calculate the temperature change rate. The temperature prediction module 4 receives temperature data and timestamps as inputs and analyzes the temperature data to determine the temperature change trend and rate. Based on historical data and model training, the prediction module can estimate future temperature changes and calculate the temperature change rate.

[0031] S30: The liquid cooling control module 3 generates a liquid cooling control instruction according to the temperature data and the temperature change rate; Specifically, the liquid cooling control module 3 receives the temperature data and the temperature change rate as input, and generates a liquid cooling control instruction according to a preset control strategy. The control instruction includes the operation of the flow rate, temperature or other related parameters of the cooling medium in the liquid cooling module 1. According to the temperature data and the predicted temperature change rate, the control module dynamically adjusts the operating state of the liquid cooling module 1 to achieve cooling.

[0032] S40: the liquid cooling control module 3 controls the liquid cooling module 1 to perform a cooling operation according to the liquid cooling control instruction; Specifically, the liquid cooling module 1 can adjust the flow rate, temperature or other parameters of the cooling medium according to instructions to achieve the purpose of cooling. In the embodiment of the present application, this is achieved by controlling valves, fans or other liquid cooling equipment.

[0033] After the step S40: the liquid cooling control module 3 controls the liquid cooling module 1 to perform the cooling operation according to the temperature data and the temperature change rate, the following steps are included: S401: inputting a liquid cooling control instruction into a preset historical liquid cooling heat dissipation database, wherein a plurality of liquid cooling control instructions form a control instruction data set; Specifically: the liquid cooling control module 3 records the generated liquid cooling control instructions in the historical liquid cooling heat dissipation database. In the embodiment of the present application, the liquid cooling control instructions include operations for adjusting the flow, temperature or other parameters of the cooling medium in the liquid cooling module 1. These instructions will be recorded and form a control instruction data set.

[0034] S402: inputting the temperature data and the temperature change rate when the liquid cooling module 1 executes the liquid cooling control instruction into the historical liquid cooling heat dissipation database, mapping the temperature data and the temperature change rate with the corresponding liquid cooling control instruction, forming a historical temperature data set with a plurality of temperature change rates, and forming a temperature change rate data set with a plurality of temperature change rates; Specifically, when the liquid cooling module 1 executes the liquid cooling control instruction, the liquid cooling module 1 will record the corresponding temperature data and temperature change rate, and map it with the executed liquid cooling control instruction. These temperature data and temperature change rate will be recorded in the historical liquid cooling heat dissipation database, and form a historical temperature data set and a temperature change rate data set.

[0035] After the step of S402: inputting the temperature data and the temperature change rate when the liquid cooling module 1 executes the liquid cooling control instruction into the historical liquid cooling heat dissipation database, mapping the temperature data and the temperature change rate with the corresponding liquid cooling control instruction, forming a historical temperature data set with a plurality of temperature change rates, and forming a temperature change rate data set with a plurality of temperature change rates, the following steps are included: S4021: The preset liquid cooling optimization model retrieves the control instruction data set and the corresponding historical temperature data set and temperature change rate data set. The liquid cooling optimization model performs self-learning on the control instruction data set based on a neural network algorithm to optimize the generation of liquid cooling control instructions. Specifically, the preset liquid cooling optimization model can be a model based on a neural network algorithm, which can retrieve the previously established control instruction data set, historical temperature data set, and temperature change rate data set. By training and learning these data, the liquid cooling optimization model can optimize the generation method of liquid cooling control instructions, so that the liquid cooling module 1 can more intelligently adjust the flow rate, temperature and other parameters of the cooling medium to achieve a better cooling effect.

[0036] After the step of S402: inputting the temperature data and the temperature change rate when the liquid cooling module 1 executes the liquid cooling control instruction into the historical liquid cooling heat dissipation database, mapping the temperature data and the temperature change rate with the corresponding liquid cooling control instruction, forming a historical temperature data set with a plurality of temperature change rates, and forming a temperature change rate data set with a plurality of temperature change rates, the following steps are also included: S4022: The temperature prediction module 4 performs data analysis on the historical temperature data set and the temperature change rate data set based on the big data algorithm, and optimizes the preset temperature change prediction model; Specifically: The temperature prediction module 4 uses a big data algorithm to analyze the historical temperature data set and the temperature change rate data set. By analyzing these data, the temperature prediction module 4 can identify the temperature change pattern and trend. Then, the preset temperature change prediction model will be optimized based on these analysis results to improve the accuracy and reliability of temperature prediction.

[0037] S4023: The optimized temperature change prediction model predicts the real-time temperature data and generates predicted temperature data; The optimized temperature change prediction model predicts the current temperature data based on the previous optimization process. By inputting real-time temperature data, the temperature change prediction model can generate predicted temperature data, that is, the predicted value of the temperature in the future.

[0038] S4024: Determine whether the predicted temperature data is within a preset temperature threshold; Specifically, the predicted temperature data is compared with a preset temperature threshold. If the predicted temperature data exceeds or approaches the preset temperature threshold, it indicates that the temperature of the liquid cooling system may have reached or exceeded a safe range.

[0039] S4025: If the predicted temperature data is not within the temperature threshold, a temperature alarm signal is issued; Specifically, if the predicted temperature data exceeds or approaches a preset temperature threshold, the liquid cooling control module 3 may issue a temperature alarm signal, which may be achieved by triggering an alarm device, sending a notification, or executing other early warning measures.

[0040] After the step S40: the liquid cooling control module 3 controls the liquid cooling module 1 to perform the cooling operation according to the temperature data and the temperature change rate, the following steps are also included: S403: the air pressure monitoring module 7 monitors the server in real time to obtain air pressure data, and inputs the air pressure data to the leakage monitoring module 5; S404: the leakage monitoring module 5 performs difference calculation between the air pressure data and the preset reference value according to the preset air pressure calculation model, and obtains the air pressure deviation value; Specifically, in order to detect leakage in the liquid cooling system, a leakage sensor and a leakage detection device can be installed. These devices can monitor the pressure, liquid displacement and leakage of the liquid cooling system in real time. When a leakage is detected, the liquid cooling control module 3 can take corresponding leakage control measures, such as closing the valve near the leakage point, repairing the leakage point or stopping the operation of the liquid cooling system.

[0041] S405: Determine whether the deviation value is within a preset air pressure threshold; S406: If the deviation value is not within the air pressure threshold, an air pressure leakage alarm signal is issued.

[0042] The leakage detection and control steps in the liquid cooling convection system include the generation and analysis of predicted temperature data, the optimization of liquid cooling control instructions, the automatic adjustment of the temperature of the liquid cooling system, and the detection and control of leakage conditions, which can realize the intelligent control and optimization of the liquid cooling system and improve the stability, safety and efficiency of the system.

[0043] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0044] In one embodiment, an electronic device is provided. The electronic device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The electronic device includes a processor, a memory, a network interface and a database connected via a system bus. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the electronic device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a server cooling method based on liquid cooling convection is implemented.

[0045] In one embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: The temperature monitoring module monitors the temperature data of the server in real time and inputs the temperature data into the temperature prediction module and the liquid cooling control module; The temperature prediction module is preset with a timestamp, calculates the temperature change rate according to the temperature data and the timestamp, and inputs the temperature change rate into the liquid cooling control module; The liquid cooling control module generates a liquid cooling control instruction according to the temperature data and the temperature change rate; The liquid cooling control module controls the liquid cooling module to perform cooling work according to the liquid cooling control instruction.

[0046] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: The temperature monitoring module monitors the temperature data of the server in real time and inputs the temperature data into the temperature prediction module and the liquid cooling control module; The temperature prediction module is preset with a timestamp, calculates the temperature change rate according to the temperature data and the timestamp, and inputs the temperature change rate into the liquid cooling control module; The liquid cooling control module generates a liquid cooling control instruction according to the temperature data and the temperature change rate; The liquid cooling control module controls the liquid cooling module to perform cooling work according to the liquid cooling control instruction.

[0047] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0048] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0049] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A server cooling system based on liquid cooling convection, characterized in that: The invention comprises a liquid cooling module (1), a temperature monitoring module (2), a liquid cooling control module (3), a temperature prediction module (4) and a leakage monitoring module (5), wherein the liquid cooling module (1) is used for liquid cooling a server; the temperature monitoring module (2) is used for real-time monitoring of the temperature data of the server, and inputting the temperature data into the temperature prediction module (4) and the liquid cooling control module (3); the temperature prediction module (4) is used for presetting a timestamp, calculating a temperature change rate according to the temperature data and the timestamp, and inputting the temperature change rate into the liquid cooling control module (3); the liquid cooling control module (3) generates a liquid cooling control instruction according to the temperature data and the temperature change rate, and controls the liquid cooling module (1) to perform a cooling operation according to the liquid cooling control instruction; and the leakage monitoring device is used for monitoring the air pressure leakage in the server.

2. A server cooling system based on liquid cooling convection according to claim 1, characterized in that: The cooling system further comprises a data storage module (6), wherein the data storage module (6) is used to preset a historical liquid cooling heat dissipation database and record temperature data and temperature change rate when the liquid cooling module (1) executes a liquid cooling control instruction.

3. A server cooling system based on liquid cooling convection according to claim 2, characterized in that: The cooling system further comprises an air pressure monitoring module (7), which acquires air pressure data from a monitoring server in real time and inputs the air pressure data into the leakage monitoring module (5).

4. A server cooling method based on liquid cooling convection, characterized in that: A server cooling system based on liquid cooling convection according to any one of claims 1 to 3, comprising the following steps: The temperature monitoring module (2) monitors the temperature data of the server in real time, and inputs the temperature data into the temperature prediction module (4) and the liquid cooling control module (3); The temperature prediction module (4) is preset with a timestamp, calculates the temperature change rate according to the temperature data and the timestamp, and inputs the temperature change rate into the liquid cooling control module (3); The liquid cooling control module (3) generates a liquid cooling control instruction according to the temperature data and the temperature change rate; The liquid cooling control module (3) controls the liquid cooling module (1) to perform a cooling operation according to the liquid cooling control instruction.

5. The server cooling method based on liquid cooling convection according to claim 1, characterized in that: After the step in which the liquid cooling control module (3) controls the liquid cooling module (1) to perform a cooling operation according to the temperature data and the temperature change rate, the following steps are included: The air pressure monitoring module (7) monitors the server in real time to obtain air pressure data, and inputs the air pressure data into the leakage monitoring module (5); The leakage monitoring module (5) performs difference calculation between the air pressure data and a preset reference value according to a preset air pressure calculation model, and obtains an air pressure deviation value; Determining whether the deviation value is within a preset air pressure threshold; If the deviation value is not within the air pressure threshold, an air pressure leakage alarm signal is issued.

6. A server cooling method based on liquid cooling convection according to claim 5, characterized in that: After the step in which the liquid cooling control module (3) controls the liquid cooling module (1) to perform a cooling operation according to the temperature data and the temperature change rate, the following steps are included: Inputting the liquid cooling control instruction into a preset historical liquid cooling heat dissipation database, wherein a plurality of the liquid cooling control instructions form a control instruction data set; The temperature data and the temperature change rate when the liquid cooling module (1) executes the liquid cooling control instruction are input into the historical liquid cooling heat dissipation database, the temperature data and the temperature change rate are mapped with the corresponding liquid cooling control instruction, a plurality of the temperature data form a historical temperature data set, and a plurality of the temperature change rates form a temperature change rate data set.

7. A server cooling method based on liquid cooling convection according to claim 6, characterized in that: After the temperature data and the temperature change rate when the liquid cooling module (1) executes the liquid cooling control instruction are input into the historical liquid cooling heat dissipation database, the temperature data and the temperature change rate are mapped with the corresponding liquid cooling control instruction, a number of the temperature data form a historical temperature data set, and a number of the temperature change rates form a temperature change rate data set, the method comprises the following steps: The preset liquid cooling optimization model retrieves the control instruction data set and the corresponding historical temperature data set and the temperature change rate data set. The liquid cooling optimization model performs self-learning on the control instruction data set based on a neural network algorithm to optimize the generation of liquid cooling control instructions.

8. The server cooling method based on liquid cooling convection according to claim 7, characterized in that: After the step in which the liquid cooling control module (3) controls the liquid cooling module (1) to perform a cooling operation according to the temperature data and the temperature change rate, the following steps are included: The temperature prediction module (4) performs data analysis on the historical temperature data set and the temperature change rate data set based on a big data algorithm, and optimizes a preset temperature change prediction model; The optimized temperature change prediction model predicts the real-time temperature data and generates predicted temperature data; Determine whether the predicted temperature data is within the preset temperature threshold; If the predicted temperature data is not within the temperature threshold, a temperature alarm signal is issued.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of a server cooling method based on liquid cooling convection as described in any one of claims 4 to 8 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of a server cooling method based on liquid cooling convection as described in any one of claims 4 to 8 are implemented.

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