Intelligent control and monitoring method and system applied to immersed liquid cooling system

Abstract

The invention relates to the technical field of heat dissipation control, and discloses an intelligent control and monitoring method and system applied to an immersed liquid cooling system, and the method comprises the steps: monitoring the immersed liquid cooling system and a calculation system corresponding to the immersed liquid cooling system, obtaining first operation data of the immersed liquid cooling system for the computing system and second operation data of the computing system; according to the second operation data, heat dissipation demand information corresponding to the system is analyzed and calculated; based on the determined heat dissipation parameter optimization model, according to the first operation data and the heat dissipation demand information, adjusting a heat dissipation control parameter corresponding to the immersed liquid cooling system to obtain a target control parameter corresponding to the immersed liquid cooling system; and controlling the immersed liquid cooling system to execute heat dissipation operation corresponding to the target control parameter for the computing system according to the target control parameter. It can be seen that the control flexibility and control accuracy of the heat dissipation system can be improved while efficient heat dissipation is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of heat dissipation control, and particularly to an intelligent control and monitoring method and system applied to an immersion liquid cooling system. Background Art

[0002] Currently, in the fields of artificial intelligence, data centers, and 5G communications, with the continuous development of technologies, the power density of devices is continuously increasing, and the device volume is gradually shrinking, facing increasingly severe heat dissipation challenges.

[0003] In practical applications, existing heat dissipation solutions usually adopt air-cooled heat dissipation technology. However, the heat generated by current high-density devices has far exceeded the processing capacity of traditional air-cooled heat dissipation systems, unable to meet the heat dissipation requirements of devices, thus easily causing device overheating, affecting the operating performance of devices, and even causing device damage.

[0004] Therefore, it is particularly important to propose a technical solution that can improve the control flexibility and control accuracy of the heat dissipation system while achieving efficient heat dissipation. Summary of the Invention

[0005] The present invention provides an intelligent control and monitoring method and system applied to an immersion liquid cooling system, which can improve the control flexibility and control accuracy of the heat dissipation system while achieving efficient heat dissipation.

[0006] To solve the above technical problems, in the first aspect of the present invention, an intelligent control and monitoring method applied to an immersion liquid cooling system is disclosed. The method includes:

[0007] Monitoring the immersion liquid cooling system and the corresponding computing system, and obtaining first operation data of the immersion liquid cooling system for the computing system and second operation data of the computing system;

[0008] Analyzing the heat dissipation requirement information corresponding to the computing system according to the second operation data;

[0009] Based on the determined heat dissipation parameter optimization model, adjusting the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the first operation data and the heat dissipation requirement information to obtain target control parameters corresponding to the immersion liquid cooling system;

[0010] Controlling the immersion liquid cooling system to perform a heat dissipation operation corresponding to the target control parameters for the computing system according to the target control parameters.

[0011] As an alternative implementation, in the first aspect of the present invention, the second operation data includes the device temperature data corresponding to the computing system, the cumulative operation duration data of the device corresponding to the computing system, the operation time period data of the device corresponding to the computing system, and the operation performance data of the device corresponding to the computing system;

[0012] Among them, analyzing the heat dissipation requirement information corresponding to the computing system according to the second operation data includes:

[0013] Estimating the operation heat generation information generated by the computing system within a preset time period according to the second operation data;

[0014] Generating the heat dissipation requirement information corresponding to the computing system according to the operation heat generation information.

[0015] As an alternative implementation, in the first aspect of the present invention, based on the determined heat dissipation parameter optimization model, adjusting the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the first operation data and the heat dissipation requirement information to obtain the target control parameters corresponding to the immersion liquid cooling system includes:

[0016] Determining the current heat dissipation capacity of the immersion liquid cooling system according to the first operation data; the current heat dissipation capacity is used to represent the heat dissipation amount and / or heat dissipation efficiency that the immersion liquid cooling system can achieve under the first operation data;

[0017] Determining the target heat dissipation capacity that the immersion liquid cooling system needs to achieve according to the heat dissipation requirement information;

[0018] Based on the determined heat dissipation parameter optimization model, adjusting the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the target heat dissipation capacity and the current heat dissipation capacity to obtain the target control parameters corresponding to the immersion liquid cooling system.

[0019] As an alternative implementation, in the first aspect of the present invention, the immersion liquid cooling system includes multiple subsystems, and each subsystem is one of a liquid cooling cabinet system, a circulating liquid pump cabinet system, and an outdoor heat dissipation system;

[0020] Among them, the method further includes:

[0021] Obtaining the operation standard index corresponding to the immersion liquid cooling system and the index value range corresponding to the operation standard index;

[0022] Analyzing the first operation data according to the operation standard index and the index value range to obtain the operation prediction result corresponding to the immersion liquid cooling system;

[0023] Based on the operation prediction result, determine whether the immersion liquid cooling system meets the pre-set abnormal operation judgment conditions;

[0024] When it is determined that the immersion liquid cooling system meets the abnormal operation judgment conditions, generate a system maintenance plan for the operation prediction result according to the first operation data and the operation prediction result;

[0025] Execute system maintenance operations on the immersion liquid cooling system according to the system maintenance plan.

[0026] As an optional implementation manner, in the first aspect of the present invention, the first operation data includes subsystem operation data corresponding to each subsystem in the immersion liquid cooling system; the operation standard indicators include subsystem standard indicators corresponding to each subsystem in the immersion liquid cooling system;

[0027] Among them, the analyzing the first operation data according to the operation standard indicators and the index value range to obtain the operation prediction result corresponding to the immersion liquid cooling system includes:

[0028] For each subsystem in the immersion liquid cooling system, analyze the operation data value corresponding to the subsystem operation data of the subsystem and the index value range corresponding to the subsystem standard indicator of the subsystem to obtain the numerical analysis result corresponding to the subsystem; the numerical analysis result includes a numerical comparison result and a numerical change trend analysis result;

[0029] For each subsystem in the immersion liquid cooling system, detect whether there is alarm data in the subsystem operation data corresponding to the subsystem to obtain the alarm detection result corresponding to the subsystem;

[0030] For each subsystem in the immersion liquid cooling system, generate a subsystem prediction result corresponding to the subsystem according to the numerical analysis result and the alarm detection result; the subsystem state prediction result includes a subsystem numerical prediction result and a subsystem state prediction result;

[0031] Determine the operation state prediction result corresponding to the immersion liquid cooling system according to the subsystem prediction results corresponding to all the subsystems;

[0032] Among them, the operation prediction result includes the subsystem prediction result corresponding to each subsystem and the operation state prediction result.

[0033] As an optional implementation manner, in the first aspect of the present invention, the method further includes:

[0034] Obtain the system structure information corresponding to the immersion liquid cooling system; the system structure information includes the connection relationship between multiple subsystems and / or the device structure information corresponding to each subsystem;

[0035] For each subsystem in the immersion liquid cooling system, according to the system structure information, determine the predicted operation influence coefficient of the remaining subsystems on this subsystem; the predicted operation influence coefficient is used to represent the influence degree of the operation conditions of the remaining subsystems on the operation conditions of this subsystem;

[0036] Wherein, for each subsystem in the immersion liquid cooling system, generating the subsystem prediction result corresponding to this subsystem according to the numerical analysis result and the alarm detection result includes:

[0037] Generate the initial prediction result corresponding to this subsystem according to the numerical analysis result and the alarm detection result;

[0038] Optimize the initial prediction result corresponding to this subsystem according to the predicted operation influence coefficient of the remaining subsystems on this subsystem, and obtain the subsystem prediction result corresponding to this subsystem.

[0039] As an optional implementation manner, in the first aspect of the present invention, judging whether the immersion liquid cooling system meets the preset abnormal operation judgment conditions according to the operation prediction result includes:

[0040] For each subsystem in the immersion liquid cooling system, when the subsystem numerical prediction result corresponding to this subsystem is an abnormal numerical prediction result or the subsystem state prediction result corresponding to this subsystem is the first abnormal state prediction result, determine this subsystem as a predicted abnormal subsystem;

[0041] Judge whether there is the predicted abnormal subsystem in the immersion liquid cooling system or whether the operation state prediction result is the second abnormal state prediction result;

[0042] When it is judged that there is the predicted abnormal subsystem in the immersion liquid cooling system or the operation state prediction result is the second abnormal state prediction result, determine that the immersion liquid cooling system meets the preset abnormal operation judgment conditions;

[0043] When it is judged that there is no predicted abnormal subsystem in the immersion liquid cooling system or the operation state prediction result is not the second abnormal state prediction result, determine that the immersion liquid cooling system does not meet the preset abnormal operation judgment conditions.

[0044] The second aspect of the present invention discloses an intelligent control and monitoring system applied to an immersion liquid cooling system, and the system includes:

[0045] A monitoring module, configured to monitor the immersion liquid cooling system and the corresponding computing system of the immersion liquid cooling system, and obtain first operation data of the immersion liquid cooling system for the computing system and second operation data of the computing system;

[0046] An analysis module, configured to analyze heat dissipation requirement information corresponding to the computing system according to the second operation data;

[0047] An adjustment module, configured to adjust heat dissipation control parameters corresponding to the immersion liquid cooling system according to the first operation data and the heat dissipation requirement information based on a determined heat dissipation parameter optimization model, and obtain target control parameters corresponding to the immersion liquid cooling system;

[0048] A control module, configured to control the immersion liquid cooling system to perform a heat dissipation operation corresponding to the target control parameters for the computing system according to the target control parameters.

[0049] As an optional implementation manner, in the second aspect of the present invention, the second operation data includes device temperature data corresponding to the computing system, device cumulative operation duration data corresponding to the computing system, device operation time period data corresponding to the computing system, and device operation performance data corresponding to the computing system;

[0050] Wherein, the specific manner in which the analysis module analyzes heat dissipation requirement information corresponding to the computing system according to the second operation data includes:

[0051] Estimate operation heat information generated by the computing system within a preset time period according to the second operation data;

[0052] Generate heat dissipation requirement information corresponding to the computing system according to the operation heat information.

[0053] As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the adjustment module adjusts heat dissipation control parameters corresponding to the immersion liquid cooling system according to the first operation data and the heat dissipation requirement information based on a determined heat dissipation parameter optimization model, and obtains target control parameters corresponding to the immersion liquid cooling system includes:

[0054] Determine the current heat dissipation capacity of the immersion liquid cooling system according to the first operation data; the current heat dissipation capacity is used to represent the heat dissipation amount and / or heat dissipation efficiency that the immersion liquid cooling system can achieve under the first operation data;

[0055] Determine the target heat dissipation capacity that the immersion liquid cooling system needs to achieve according to the heat dissipation requirement information;

[0056] Based on the determined heat dissipation parameter optimization model, according to the target heat dissipation capacity and the current heat dissipation capacity, adjust the heat dissipation control parameters corresponding to the immersion liquid cooling system to obtain the target control parameters corresponding to the immersion liquid cooling system.

[0057] As an optional implementation manner, in the second aspect of the present invention, the immersion liquid cooling system includes a plurality of subsystems, and each of the subsystems is one of a liquid cooling cabinet system, a circulating liquid pump cabinet system, and an outdoor heat dissipation system;

[0058] Wherein, the system further includes:

[0059] A first acquisition module, configured to acquire the operation standard indexes corresponding to the immersion liquid cooling system and the index value ranges corresponding to the operation standard indexes;

[0060] The analysis module is further configured to analyze the first operation data according to the operation standard indexes and the index value ranges to obtain an operation prediction result corresponding to the immersion liquid cooling system;

[0061] A judgment module, configured to judge whether the immersion liquid cooling system meets a preset abnormal operation judgment condition according to the operation prediction result;

[0062] A generation module, configured to generate a system maintenance plan for the operation prediction result according to the first operation data and the operation prediction result when the judgment module judges that the immersion liquid cooling system meets the abnormal operation judgment condition;

[0063] A maintenance module, configured to perform system maintenance operations on the immersion liquid cooling system according to the system maintenance plan.

[0064] As an optional implementation manner, in the second aspect of the present invention, the first operation data includes subsystem operation data corresponding to each subsystem in the immersion liquid cooling system; the operation standard indexes include subsystem standard indexes corresponding to each subsystem in the immersion liquid cooling system;

[0065] Wherein, the specific manner in which the analysis module analyzes the first operation data according to the operation standard indexes and the index value ranges to obtain an operation prediction result corresponding to the immersion liquid cooling system includes:

[0066] For each subsystem in the immersion liquid cooling system, analyze the operation data value corresponding to the subsystem operation data of the subsystem and the index value range corresponding to the subsystem standard index of the subsystem to obtain a numerical analysis result corresponding to the subsystem; the numerical analysis result includes a numerical comparison result and a numerical change trend analysis result;

[0067] For each of the subsystems in the immersion liquid cooling system, detect whether there is alarm data in the subsystem operation data corresponding to the subsystem, and obtain the alarm detection result corresponding to the subsystem;

[0068] For each of the subsystems in the immersion liquid cooling system, generate a subsystem prediction result corresponding to the subsystem according to the numerical analysis result and the alarm detection result; the subsystem status prediction result includes a subsystem numerical prediction result and a subsystem status prediction result;

[0069] Determine the operation status prediction result corresponding to the immersion liquid cooling system according to the subsystem prediction results corresponding to all the subsystems;

[0070] Wherein, the operation prediction result includes the subsystem prediction result corresponding to each of the subsystems and the operation status prediction result.

[0071] As an optional implementation manner, in the second aspect of the present invention, the system further includes:

[0072] A second acquisition module, configured to acquire system structure information corresponding to the immersion liquid cooling system; the system structure information includes the connection relationship between multiple subsystems and / or the device structure information corresponding to each subsystem;

[0073] A determination module, configured to determine, for each of the subsystems in the immersion liquid cooling system, a predicted operation influence coefficient of the remaining subsystems on the subsystem according to the system structure information; the predicted operation influence coefficient is used to represent the influence degree of the operation conditions of the remaining subsystems on the operation conditions of the subsystem;

[0074] Wherein, for each of the subsystems in the immersion liquid cooling system, the specific manner in which the analysis module generates a subsystem prediction result corresponding to the subsystem according to the numerical analysis result and the alarm detection result includes:

[0075] Generate an initial prediction result corresponding to the subsystem according to the numerical analysis result and the alarm detection result;

[0076] Optimize the initial prediction result corresponding to the subsystem according to the predicted operation influence coefficient of the remaining subsystems on the subsystem, and obtain the subsystem prediction result corresponding to the subsystem.

[0077] As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the judgment module judges whether the immersion liquid cooling system meets a preset abnormal operation judgment condition according to the operation prediction result includes:

[0078] For each of the subsystems in the immersion liquid cooling system, when the subsystem numerical prediction result corresponding to the subsystem is an abnormal numerical prediction result or the subsystem state prediction result corresponding to the subsystem is a first abnormal state prediction result, the subsystem is determined as a predicted abnormal subsystem;

[0079] Determine whether there is the predicted abnormal subsystem in the immersion liquid cooling system or whether the operating state prediction result is a second abnormal state prediction result;

[0080] When it is determined that there is the predicted abnormal subsystem in the immersion liquid cooling system or the operating state prediction result is the second abnormal state prediction result, it is determined that the immersion liquid cooling system meets the preset abnormal operation judgment condition;

[0081] When it is determined that there is no predicted abnormal subsystem in the immersion liquid cooling system or the operating state prediction result is not the second abnormal state prediction result, it is determined that the immersion liquid cooling system does not meet the preset abnormal operation judgment condition.

[0082] The third aspect of the present invention discloses another intelligent control and monitoring system applied to an immersion liquid cooling system, and the system includes:

[0083] A memory storing executable program code;

[0084] A processor coupled to the memory;

[0085] The processor calls the executable program code stored in the memory and executes some or all of the steps of the intelligent control and monitoring method applied to the immersion liquid cooling system disclosed in the first aspect of the present invention.

[0086] The fourth aspect of the present invention discloses a computer storage medium, and the computer storage medium stores computer instructions, which are used to execute some or all of the steps of the intelligent control and monitoring method applied to the immersion liquid cooling system disclosed in the first aspect of the present invention when being called.

[0087] Compared with the prior art, the present invention has the following beneficial effects:

[0088] In the present invention, a submerged liquid cooling system and a corresponding computing system are monitored to obtain first operation data of the submerged liquid cooling system for the computing system and second operation data of the computing system; according to the second operation data, the heat dissipation requirement information corresponding to the computing system is analyzed; based on the determined heat dissipation parameter optimization model, according to the first operation data and the heat dissipation requirement information, the heat dissipation control parameters corresponding to the submerged liquid cooling system are adjusted to obtain the target control parameters corresponding to the submerged liquid cooling system; according to the target control parameters, the submerged liquid cooling system is controlled to perform a heat dissipation operation corresponding to the target control parameters for the computing system. It can be seen that implementing the present invention can monitor the submerged liquid cooling system and the corresponding computing system to obtain the first operation data and the second operation data, then analyze the heat dissipation requirement of the computing system according to the second operation data, and then adjust the heat dissipation control parameters based on the heat dissipation parameter optimization model and according to the first operation data and the heat dissipation requirement, so as to control the submerged liquid cooling system to perform the corresponding heat dissipation operation according to the obtained target control parameters, which can realize intelligent monitoring and optimization of the heat dissipation operation of the submerged liquid cooling system, thereby improving the control flexibility and control accuracy of the submerged liquid cooling system while achieving efficient heat dissipation, and further facilitating improving the heat dissipation accuracy and heat dissipation efficiency of the submerged liquid cooling system for the computing system, and further facilitating improving the operation stability and operation safety of the computing system. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0090] Figure 1 It is a schematic flowchart of an intelligent control and monitoring method applied to a submerged liquid cooling system disclosed in an embodiment of the present invention;

[0091] Figure 2 It is a schematic flowchart of another intelligent control and monitoring method applied to a submerged liquid cooling system disclosed in an embodiment of the present invention;

[0092] Figure 3 It is a schematic structural diagram of an intelligent control and monitoring system applied to a submerged liquid cooling system disclosed in an embodiment of the present invention;

[0093] Figure 4 It is a schematic structural diagram of another intelligent control and monitoring system applied to a submerged liquid cooling system disclosed in an embodiment of the present invention;

[0094] Figure 5It is a schematic structural diagram of another intelligent control and monitoring system applied to an immersion liquid cooling system disclosed in an embodiment of the present invention. Detailed implementation manners

[0095] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0096] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or terminal including a series of steps or units is not limited to the listed steps or units, but optionally further includes unlisted steps or units, or optionally further includes other steps or units inherent to these processes, methods, products or terminals.

[0097] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0098] The present invention discloses an intelligent control and monitoring method and system applied to an immersion liquid cooling system, which can obtain first operation data and second operation data by monitoring the immersion liquid cooling system and the corresponding computing system, then analyze the heat dissipation requirements of the computing system according to the second operation data, and then adjust the heat dissipation control parameters based on the heat dissipation parameter optimization model and according to the first operation data and the heat dissipation requirements, so as to control the immersion liquid cooling system to perform corresponding heat dissipation operations according to the obtained target control parameters, which can realize intelligent monitoring and optimization of the heat dissipation operations of the immersion liquid cooling system, so as to improve the control flexibility and control accuracy of the heat dissipation system while achieving efficient heat dissipation, and further contribute to improving the heat dissipation accuracy and heat dissipation efficiency of the heat dissipation system for the computing system, and further contribute to improving the operation stability and operation safety of the computing system. The following will be described in detail respectively.

[0099] Embodiment 1

[0100] Please refer to Figure 1 ,Figure 1 It is a schematic flowchart of an intelligent control and monitoring method applied to an immersion liquid cooling system disclosed in an embodiment of the present invention. Among them, Figure 1 The described intelligent control and monitoring method applied to the immersion liquid cooling system can be applied to an intelligent control and monitoring system, which can include one of an intelligent device, an intelligent terminal, and a server. Among them, the server can include a local server or a cloud server, which is not limited in the embodiments of the present invention. As Figure 1 shown, the intelligent control and monitoring method applied to the immersion liquid cooling system can include the following operations:

[0101] 101. Monitor the immersion liquid cooling system and the corresponding computing system of the immersion liquid cooling system to obtain the first operation data of the immersion liquid cooling system for the computing system and the second operation data of the computing system.

[0102] In the embodiments of the present invention, the immersion liquid cooling system is a heat dissipation system capable of performing heat dissipation operations on the computing system; further, the computing system can include multiple computing devices. Further, each computing device can be immersed in the above immersion liquid cooling system, which is not limited in the embodiments of the present invention. Among them, optionally, the immersion liquid cooling system includes multiple subsystems. Further optionally, each subsystem can be one of a liquid cooling cabinet system, a circulating liquid pump cabinet system, and an outdoor heat dissipation system, which is not limited in the embodiments of the present invention; among them, each liquid cooling cabinet included in the liquid cooling cabinet system is used to immerse the computing device in the coolant to dissipate heat from the computing device.

[0103] 102. Analyze the heat dissipation requirement information corresponding to the computing system according to the second operation data.

[0104] In the embodiments of the present invention, optionally, the heat dissipation requirement information corresponding to the computing system can include current heat dissipation requirement information and / or heat dissipation requirement change information, which is not limited in the embodiments of the present invention; among them, the heat dissipation requirement change information can be used to represent the change in the current heat dissipation requirement of the computing system compared with the previously determined historical heat dissipation requirement.

[0105] In the embodiments of the present invention, optionally, the current heat dissipation requirement information can include the heat dissipation efficiency currently required by the computing system and / or the amount of heat that the computing system currently needs to dissipate; optionally, the heat dissipation requirement change information can include a heat dissipation efficiency difference and / or a heat dissipation heat difference, which is not limited in the embodiments of the present invention.

[0106] 103. Based on the determined heat dissipation parameter optimization model, adjust the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the first operation data and the heat dissipation requirement information to obtain the target control parameters corresponding to the immersion liquid cooling system.

[0107] In an embodiment of the present invention, optionally, the heat dissipation parameter optimization model may be a pre-trained model generated based on artificial intelligence technology and / or machine learning technology, and the embodiments of the present invention do not make limitations thereto.

[0108] In an embodiment of the present invention, optionally, the heat dissipation control parameters corresponding to the immersion liquid cooling system may include heat dissipation control parameters for each computing device in the computing system; optionally, the heat dissipation control parameters may include coolant control parameters and / or circulation control parameters, and the embodiments of the present invention do not make limitations thereto; further optionally, the coolant control parameters may include one or more combinations of coolant injection type, coolant injection volume, coolant flow rate, coolant flow, coolant flow direction, coolant temperature, coolant pressure, etc., and the embodiments of the present invention do not make limitations thereto; further optionally, the circulation control parameters may include one or more combinations of circulation pipeline layout parameters, circulation pipeline length, circulation pump speed, main and standby liquid pump switching control parameters, etc., and the embodiments of the present invention do not make limitations thereto.

[0109] 104. According to the target control parameter, control the immersion liquid cooling system to perform a heat dissipation operation corresponding to the target control parameter for the computing system.

[0110] In an embodiment of the present invention, the heat dissipation operation may specifically be: after immersing the computing device in the insulating coolant, based on the target control parameter, by controlling the flow of the coolant, taking away the heat of the heat-generating components, and then transferring the heat to the outdoor heat dissipation system (the outdoor heat dissipation system may include a cooling tower or an air-cooled condenser) through a heat exchanger, so as to dissipate the heat to the outdoor environment.

[0111] It can be seen that implementing the method described in the embodiments of the present invention can monitor the immersion liquid cooling system and the corresponding computing system to obtain the first operation data and the second operation data, then analyze the heat dissipation requirements of the computing system according to the second operation data, and then adjust the heat dissipation control parameters based on the heat dissipation parameter optimization model and according to the first operation data and the heat dissipation requirements, so as to control the immersion liquid cooling system to perform the corresponding heat dissipation operation according to the obtained target control parameter, which can realize intelligent monitoring and optimization of the heat dissipation operation of the immersion liquid cooling system, thereby improving the control flexibility and control accuracy of the heat dissipation system while achieving efficient heat dissipation, and further being beneficial to improving the heat dissipation accuracy and heat dissipation efficiency of the heat dissipation system for the computing system, and further being beneficial to improving the operation stability and operation safety of the computing system.

[0112] In an alternative embodiment, the second operation data includes device temperature data corresponding to the computing system, device cumulative operation duration data corresponding to the computing system, device operation time period data corresponding to the computing system, and device operation performance data corresponding to the computing system.

[0113] Optionally, the device temperature data corresponding to the computing system may include the device temperature of each computing device, the device cumulative operation duration data corresponding to the computing system may include the cumulative operation duration of each computing device during the current operation, the device operation time period data corresponding to the computing system may include the time period required for each computing device to operate, and the device operation performance data corresponding to the computing system may include the computing performance of each computing device. The embodiments of the present invention are not limited thereto.

[0114] In this optional embodiment, optionally, analyzing the heat dissipation requirement information corresponding to the computing system according to the second operation data may include the following operations:

[0115] Estimating the operation heat information generated by the computing system within a preset time period according to the second operation data;

[0116] Generating the heat dissipation requirement information corresponding to the computing system according to the operation heat information.

[0117] Among them, the operation heat information generated by the computing system within a preset time period may include the heat value generated by each computing device during operation within the preset time period. The embodiments of the present invention are not limited thereto.

[0118] It can be seen that this optional embodiment can estimate the operation heat that the computing system may generate according to the second operation data corresponding to the computing system, and then generate the heat dissipation requirement information according to the operation heat information. It can improve the estimation accuracy of the operation heat information of the computing system by accurately analyzing the operation situation of the computing system, thereby facilitating improving the determination accuracy of the heat dissipation requirement information corresponding to the computing system, and further facilitating improving the optimization accuracy of the heat dissipation operation of the immersion liquid cooling system.

[0119] In this optional embodiment, optionally, generating the heat dissipation requirement information corresponding to the computing system according to the operation heat information may include the following operations:

[0120] Obtaining the temperature performance influence information corresponding to the computing system and the target operation performance required for each computing device; wherein, the temperature performance influence information is used to represent the influence relationship over time between the heat generated by the device temperature of the computing device and the computing performance of the computing device;

[0121] Determining the heat that each computing device currently needs to dissipate according to the operation heat information, the temperature performance influence information, and the target operation performance required for each computing device;

[0122] Determining the heat dissipation duration threshold corresponding to each computing device to reach the target operation performance according to the target operation performance required for each computing device and the temperature performance influence information;

[0123] Determine the heat dissipation efficiency required for each computing device to achieve the corresponding target operating performance according to the heat and heat dissipation duration threshold currently required for heat dissipation by each computing device.

[0124] Among them, the current heat dissipation demand information corresponding to the computing system includes the heat currently required for heat dissipation by the computing system and / or the heat dissipation efficiency currently required by the computing system.

[0125] Among them, the heat dissipation duration threshold corresponding to each computing device achieving the target operating performance can be the maximum heat dissipation duration corresponding to each computing device achieving the target operating performance. If the heat dissipation duration threshold is exceeded and the computing device has not yet achieved the target operating performance, it will cause a decrease in the computing efficiency of the computing device.

[0126] It can be seen that this optional embodiment can also determine the heat currently required for heat dissipation of the computing device according to the operating heat information corresponding to the computing system, the obtained temperature performance influence information corresponding to the computing system, and the target operating performance required for each computing device, and determine the heat dissipation duration threshold corresponding to each computing device achieving the target operating performance according to the target operating performance and the temperature performance influence information. Then, according to the heat and heat dissipation duration threshold currently required for heat dissipation by each computing device, determine the heat dissipation efficiency required for each computing device to achieve the corresponding target operating performance, which can improve the accuracy of determining the heat required for heat dissipation and the heat dissipation efficiency of each computing device in the computing system, thereby facilitating further improvement of the accuracy of determining the heat dissipation demand of the computing system.

[0127] In another optional embodiment, based on the determined heat dissipation parameter optimization model, adjust the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the first operating data and the heat dissipation demand information to obtain the target control parameters corresponding to the immersion liquid cooling system, which may include the following operations:

[0128] According to the first operating data, determine the current heat dissipation capacity of the immersion liquid cooling system; the current heat dissipation capacity is used to represent the heat dissipation amount and / or heat dissipation efficiency that the immersion liquid cooling system can achieve under the first operating data;

[0129] According to the heat dissipation demand information, determine the target heat dissipation capacity required for the immersion liquid cooling system; the target heat dissipation capacity is used to represent the target heat dissipation amount and / or target heat dissipation efficiency that the immersion liquid cooling system needs to achieve to meet the heat dissipation demand information;

[0130] Based on the determined heat dissipation parameter optimization model, adjust the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the target heat dissipation capacity and the current heat dissipation capacity to obtain the target control parameters corresponding to the immersion liquid cooling system.

[0131] Optionally, the heat dissipation parameter optimization model can adjust the heat dissipation control parameter by determining the difference between the current heat dissipation capacity and the target heat dissipation capacity, so as to obtain the target control parameter, which is not limited in the embodiments of the present invention.

[0132] It can be seen that the optional embodiment can determine the current heat dissipation capacity of the immersion liquid cooling system according to the first operation data, and determine the target heat dissipation capacity required by the immersion liquid cooling system according to the heat dissipation requirement information. Then, based on the determined heat dissipation parameter optimization model, combining the target heat dissipation capacity and the current heat dissipation capacity, the heat dissipation control parameter is adjusted to obtain the corresponding target control parameter of the immersion liquid cooling system, which can improve the analysis accuracy of the heat dissipation capacity corresponding to the heat dissipation system, thus facilitating the improvement of the optimization accuracy of the heat dissipation control parameter, and further facilitating the improvement of the control accuracy of the heat dissipation system.

[0133] Embodiment 2

[0134] Please refer to Figure 2 , Figure 2 which is a schematic flow chart of an intelligent control and monitoring method applied to an immersion liquid cooling system disclosed in the embodiments of the present invention. Among them, Figure 2 the described intelligent control and monitoring method applied to the immersion liquid cooling system can be applied to an intelligent control and monitoring system, and the system can include one of an intelligent device, an intelligent terminal and a server. Among them, the server can include a local server or a cloud server, which is not limited in the embodiments of the present invention. As Figure 2 shown, the intelligent control and monitoring method applied to the immersion liquid cooling system can include the following operations:

[0135] 201. Monitor the immersion liquid cooling system and the corresponding computing system of the immersion liquid cooling system to obtain the first operation data of the immersion liquid cooling system for the computing system and the second operation data of the computing system.

[0136] In the embodiments of the present invention, the immersion liquid cooling system includes multiple subsystems, and each subsystem is one of a liquid cooling cabinet system, a circulating liquid pump cabinet system and an outdoor heat dissipation system.

[0137] 202. Analyze the heat dissipation requirement information corresponding to the computing system according to the second operation data.

[0138] 203. Obtain the corresponding operation standard index of the immersion liquid cooling system and the index value range corresponding to the operation standard index.

[0139] In an embodiment of the present invention, optionally, the operating standard metrics may include one or more of a first standard metric corresponding to the liquid-cooled cabinet system, a second standard metric corresponding to the circulating liquid pump cabinet system, and a third standard metric corresponding to the outdoor heat dissipation system. The embodiments of the present invention do not make any limitations. Among them, further optionally, the first standard metric corresponding to the cold cabinet system may include one or more of the liquid-cooled cabinet liquid outlet temperature metric, the air pressure metric in the liquid-cooled tank, the liquid-cooled cabinet liquid inlet flow rate metric, the total server power consumption, the coolant temperature metric, and the first liquid level state metric. The embodiments of the present invention do not make any limitations. Further optionally, the second standard metric corresponding to the circulating liquid pump cabinet system may include one or more of the total liquid-cooling operating power metric, the liquid pump operating state metric, the first system operating mode, the first frequency converter frequency metric, the total main coolant circulation flow rate, the total standby coolant circulation flow rate, the circulating water pipe pressure metric, the liquid pump cabinet liquid inlet temperature metric, and the liquid pump cabinet liquid outlet temperature metric. The embodiments of the present invention do not make any limitations. Further optionally, the third standard metric corresponding to the outdoor heat dissipation system may include one or more of the heat exchanger water inlet temperature metric, the heat exchanger water outlet temperature metric, the dry cold air inlet flow rate metric, the fan operating state metric, the second liquid level state metric, the second frequency converter frequency metric, and the second system operating mode. The embodiments of the present invention do not make any limitations.

[0140] In an embodiment of the present invention, optionally, the metric value range may include at least one metric value threshold. Among them, by way of example, the metric value threshold may include a metric value minimum and / or a metric value maximum. The embodiments of the present invention do not make any limitations.

[0141] 204. Analyze the first operating data according to the operating standard metrics and the metric value range to obtain an operating prediction result corresponding to the immersion liquid cooling system.

[0142] In an embodiment of the present invention, optionally, a target standard metric corresponding one-to-one to the data type of the first operating data may be selected from the operating standard metrics, and then the first operating data may be analyzed based on the target standard metric and the corresponding metric value range to obtain an operating prediction result corresponding to the immersion liquid cooling system. The embodiments of the present invention do not make any limitations.

[0143] 205. Determine whether the immersion liquid cooling system meets a pre-set abnormal operation determination condition according to the operating prediction result.

[0144] In an embodiment of the present invention, when step 205 determines that the immersion liquid cooling system meets the abnormal operation determination condition, the operation of step 206 is executed. Optionally, when step 205 determines that the immersion liquid cooling system meets the abnormal operation determination condition, the operation of step 208 may be executed. The embodiments of the present invention do not make any limitations.

[0145] 206. Generate a system maintenance plan for the operation prediction result according to the first operation data and the operation prediction result.

[0146] In the embodiments of the present invention, optionally, the system maintenance plan may include at least one maintenance measure; further optionally, the maintenance measure may include an inspection measure and / or a heat dissipation control parameter adjustment measure, or may also include other measures that can optimize the operation / alarm situation of the immersion liquid cooling system, which are not limited in the embodiments of the present invention.

[0147] 207. Perform system maintenance operations on the immersion liquid cooling system according to the system maintenance plan.

[0148] 208. Based on the determined heat dissipation parameter optimization model, adjust the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the first operation data and the heat dissipation requirement information to obtain the target control parameters corresponding to the immersion liquid cooling system.

[0149] 209. Control the immersion liquid cooling system to perform heat dissipation operations corresponding to the target control parameters on the computing system according to the target control parameters.

[0150] In the embodiments of the present invention, optionally, steps 208-209 may also occur before steps 203-207, that is, the operations of steps 203-207 may be performed only after controlling the immersion liquid cooling system to perform heat dissipation operations corresponding to the target control parameters on the computing system, which are not limited in the embodiments of the present invention.

[0151] In the embodiments of the present invention, for other detailed descriptions of steps 201-202 and steps 208-209, please refer to the detailed descriptions of steps 101-104 in Embodiment 1, and the embodiments of the present invention will not be repeated.

[0152] It can be seen that implementing the method described in the embodiments of the present invention can obtain the first operation data and the second operation data by monitoring the immersion liquid cooling system and the corresponding computing system, then analyze the heat dissipation requirements of the computing system according to the second operation data, and then adjust the heat dissipation control parameters based on the heat dissipation parameter optimization model and according to the first operation data and the heat dissipation requirements, so as to control the immersion liquid cooling system to perform corresponding heat dissipation operations according to the obtained target control parameters, which can realize intelligent monitoring and optimization of the heat dissipation operations of the immersion liquid cooling system, thereby improving the control flexibility and control accuracy of the heat dissipation system while achieving efficient heat dissipation, and further being beneficial to improving the heat dissipation accuracy and heat dissipation efficiency of the heat dissipation system for the computing system, and further being beneficial to improving the operation stability and operation safety of the computing system. In addition, it is also possible to analyze the first operation data through the operation standard indicators and the corresponding indicator value ranges, so as to predict the operation prediction result of the immersion liquid cooling system, and then judge whether the immersion liquid cooling system is operating abnormally according to the operation prediction result. If the system meets the abnormal operation conditions, a system maintenance plan for the operation prediction result will be generated to maintain the system, which can realize real-time monitoring and prediction of the abnormal operation of the immersion liquid cooling system, thereby improving the prediction accuracy of the operation of the heat dissipation system, and further being beneficial to improving the timeliness of abnormal determination of the heat dissipation system to improve the timeliness of fault handling of the heat dissipation system, and further being beneficial to improving the operation safety of the heat dissipation system.

[0153] In an optional embodiment, the first operation data includes the subsystem operation data corresponding to each subsystem in the immersion liquid cooling system; the operation standard indicators include the subsystem standard indicators corresponding to each subsystem in the immersion liquid cooling system.

[0154] Optionally, analyzing the first operation data according to the operation standard indicators and the indicator value ranges to obtain the operation prediction result corresponding to the immersion liquid cooling system may include the following operations:

[0155] For each subsystem in the immersion liquid cooling system, analyze the operation data value corresponding to the subsystem operation data of the subsystem and the indicator value range corresponding to the subsystem standard indicator of the subsystem to obtain the numerical analysis result corresponding to the subsystem; the numerical analysis result includes the numerical comparison result and the numerical change trend analysis result;

[0156] For each subsystem in the immersion liquid cooling system, detect whether there is alarm data in the subsystem operation data corresponding to the subsystem to obtain the alarm detection result corresponding to the subsystem;

[0157] For each subsystem in the immersion liquid cooling system, generate the subsystem prediction result corresponding to the subsystem according to the numerical analysis result and the alarm detection result; the subsystem status prediction result includes the subsystem numerical prediction result and the subsystem status prediction result;

[0158] Determine the predicted operating state result corresponding to the immersion liquid cooling system according to the subsystem prediction results corresponding to all subsystems;

[0159] Among them, the operation prediction result includes the subsystem prediction result corresponding to each subsystem and the predicted operating state result.

[0160] Among them, optionally, the subsystem standard index corresponding to each subsystem in the immersion liquid cooling system can be respectively one of the first standard index corresponding to the above liquid cooling cabinet system, the second standard index corresponding to the circulating liquid pump cabinet system, and the third standard index corresponding to the outdoor heat dissipation system. The embodiments of the present invention do not make limitations; further optionally, the subsystem standard index corresponding to each subsystem can also include an operation energy consumption index, and the embodiments of the present invention do not make limitations.

[0161] Among them, optionally, the numerical comparison result included in the numerical analysis result can be the difference between any operating data value and the index value threshold included in the corresponding index value interval. The numerical change trend analysis result included in the numerical analysis result can be used to represent the change situation / change trend of the operating data value within a preset time period. The embodiments of the present invention do not make limitations.

[0162] Among them, optionally, the alarm data can include an alarm status signal, and the embodiments of the present invention do not make limitations; among them, exemplarily, the alarm status signal can include one or more of a downtime alarm signal, a temperature threshold alarm signal, a pump operation alarm signal, a flow rate alarm signal, and a hydraulic low-level alarm signal, and can also include alarm signals for other abnormal operation situations. The embodiments of the present invention do not make limitations.

[0163] It can be seen that this optional embodiment can analyze the operating data value corresponding to the subsystem operating data corresponding to each subsystem in the immersion liquid cooling system and the index value interval corresponding to the subsystem standard index corresponding to the subsystem, obtain the numerical analysis result corresponding to the subsystem, and detect whether there is alarm data in the subsystem operating data corresponding to the subsystem, obtain the alarm detection result corresponding to the subsystem, and then generate a subsystem prediction result according to the numerical analysis result and the alarm detection result. Then, by synthesizing all the subsystem prediction results, the predicted operating state result of the immersion liquid cooling system is determined, which can realize the targeted prediction of the predicted operating conditions of each subsystem, thereby improving the analysis accuracy of the predicted operating results of the immersion liquid cooling system, and further facilitating the subsequent timely discovery and handling of abnormal operating conditions of the heat dissipation system.

[0164] In this optional embodiment, optionally, the method may further include the following operations:

[0165] Obtain the system structure information corresponding to the immersion liquid cooling system; the system structure information includes the connection relationship between multiple subsystems and / or the device structure information corresponding to each subsystem;

[0166] For each subsystem in the immersion liquid cooling system, according to the system structure information, determine the predicted operation influence coefficient of the remaining subsystems on this subsystem; the predicted operation influence coefficient is used to represent the influence degree of the operation conditions of the remaining subsystems on the operation conditions of this subsystem;

[0167] Among them, for each subsystem in the immersion liquid cooling system, according to the numerical analysis result and the alarm detection result, generate the subsystem prediction result corresponding to this subsystem, including:

[0168] Generate the initial prediction result corresponding to this subsystem according to the numerical analysis result and the alarm detection result;

[0169] Optimize the initial prediction result corresponding to this subsystem according to the predicted operation influence coefficient of the remaining subsystems on this subsystem, and obtain the subsystem prediction result corresponding to this subsystem.

[0170] Among them, optionally, the connection relationship between multiple subsystems may include the structural connection relationship between multiple subsystems and / or the step connection relationship between the heat dissipation steps corresponding to multiple subsystems in the heat dissipation process corresponding to the immersion liquid cooling system, which is not limited in the embodiments of the present invention.

[0171] Among them, the higher the predicted operation influence coefficient of any remaining subsystem on this subsystem, the more likely it is that the abnormal operation of this remaining subsystem will cause the abnormal operation of this subsystem.

[0172] It can be seen that this optional embodiment can also, for each subsystem in the immersion liquid cooling system, determine the predicted operation influence coefficient of the remaining subsystems on this subsystem according to the obtained system structure information, and then optimize the initial prediction result corresponding to this subsystem according to the predicted operation influence coefficient to obtain the subsystem prediction result corresponding to this subsystem, and can optimize the operation prediction result by analyzing the operation influence of other subsystems on this subsystem, thereby improving the prediction accuracy of the operation conditions of the subsystem, and further being beneficial to improving the analysis accuracy of the operation prediction result of the immersion liquid cooling system, and further being beneficial to timely discovering and handling the abnormal operation conditions of the heat dissipation system subsequently.

[0173] In this optional embodiment, optionally, the method may further include the following operations:

[0174] Obtain the outdoor environment data corresponding to the immersion liquid cooling system; among them, the outdoor environment data includes the outdoor environment temperature and / or the outdoor environment humidity;

[0175] Analyze the environmental impact coefficient of the outdoor environment data on the outdoor heat dissipation system according to the outdoor environment data, the third standard index in the operation standard index, and the index value range corresponding to the third standard index; wherein, the environmental impact coefficient is used to represent the influence degree of the outdoor environment on the operation of the outdoor heat dissipation system.

[0176] Among them, for each subsystem in the immersion liquid cooling system, according to the predicted operation influence coefficient of the remaining subsystems on this subsystem, optimize the initial prediction result corresponding to this subsystem to obtain the subsystem prediction result corresponding to this subsystem, which may include the following operations:

[0177] When this subsystem is an outdoor heat dissipation system, according to the predicted operation influence coefficient and environmental impact coefficient of the remaining subsystems on the outdoor heat dissipation system, optimize the initial prediction result corresponding to the outdoor heat dissipation system to obtain the subsystem prediction result corresponding to this outdoor heat dissipation system.

[0178] Among them, the higher the environmental impact coefficient, the more likely the outdoor environment is to cause abnormal operation of the outdoor heat dissipation system.

[0179] It can be seen that this optional embodiment can also analyze the environmental impact coefficient of the outdoor environment data on the outdoor heat dissipation system according to the obtained outdoor environment data, the third standard index in the operation standard index, and the index value range corresponding to the third standard index, so as to optimize the initial prediction result corresponding to the outdoor heat dissipation system according to the predicted operation influence coefficient and environmental impact coefficient of the remaining subsystems on the outdoor heat dissipation system, obtain the subsystem prediction result corresponding to the outdoor heat dissipation system, and can realize the analysis accuracy of the operation environment of the outdoor heat dissipation system, so as to accurately analyze the influence of the operation environment on the outdoor heat dissipation system, and further facilitate improving the prediction accuracy of the operation prediction result of the outdoor heat dissipation system.

[0180] In this optional embodiment, optionally, according to the operation prediction result, determine whether the immersion liquid cooling system meets the pre-set abnormal operation judgment condition, which may include the following operations:

[0181] For each subsystem in the immersion liquid cooling system, when the subsystem numerical prediction result corresponding to this subsystem is an abnormal numerical prediction result or the subsystem state prediction result corresponding to this subsystem is a first abnormal state prediction result, determine this subsystem as a predicted abnormal subsystem;

[0182] Judge whether there is a predicted abnormal subsystem in the immersion liquid cooling system or whether the operation state prediction result is a second abnormal state prediction result;

[0183] When it is determined that there is a predicted abnormal subsystem in the immersion liquid cooling system or the predicted result of the operating state is the second abnormal state prediction result, it is determined that the immersion liquid cooling system meets the preset abnormal operation judgment condition;

[0184] When it is determined that there is no predicted abnormal subsystem in the immersion liquid cooling system or the predicted result of the operating state is not the second abnormal state prediction result, it is determined that the immersion liquid cooling system does not meet the preset abnormal operation judgment condition.

[0185] Among them, the first abnormal state prediction result is the numerical analysis result corresponding to the subsystem, which is used to represent that the numerical difference is greater than the preset numerical difference and / or the alarm detection result corresponding to the subsystem, which is used to represent that there is an alarm signal. The second abnormal state prediction result is used to represent that the immersion liquid cooling system is in an abnormal operation state.

[0186] It can be seen that this optional embodiment can also determine that the immersion liquid cooling system meets the abnormal operation judgment condition when it is determined that there is a predicted abnormal subsystem or the predicted result of the operating state is the second abnormal state prediction result, that is, it is determined that the immersion liquid cooling system has an abnormality, which can improve the judgment accuracy of whether the heat dissipation system meets the abnormal operation judgment condition, thus contributing to improving the abnormality determination accuracy of the heat dissipation system, and further contributing to improving the fault handling accuracy of the heat dissipation system.

[0187] Embodiment III

[0188] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of an intelligent control and monitoring system applied to an immersion liquid cooling system disclosed in an embodiment of the present invention. Among them, Figure 3 the described intelligent control and monitoring system applied to the immersion liquid cooling system may include one of an intelligent device, an intelligent terminal, and a server. Among them, the server may include a local server or a cloud server, which is not limited in the embodiment of the present invention. As Figure 3 shown, the intelligent control and monitoring system applied to the immersion liquid cooling system may include:

[0189] A monitoring module 301, configured to monitor the immersion liquid cooling system and the computing system corresponding to the immersion liquid cooling system, and obtain first operation data of the immersion liquid cooling system for the computing system and second operation data of the computing system;

[0190] An analysis module 302, configured to analyze the heat dissipation requirement information corresponding to the computing system according to the second operation data;

[0191] An adjustment module 303, configured to optimize the heat dissipation parameter optimization model, and adjust the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the first operation data and the heat dissipation requirement information, so as to obtain the target control parameters corresponding to the immersion liquid cooling system;

[0192] A control module 304, configured to control the immersion liquid cooling system to perform a heat dissipation operation corresponding to the target control parameter on the computing system according to the target control parameter.

[0193] It can be seen that the system described in the embodiments of the present invention can monitor the immersion liquid cooling system and the corresponding computing system to obtain the first operation data and the second operation data, then analyze the heat dissipation requirement of the computing system according to the second operation data, and then optimize the heat dissipation control parameters based on the heat dissipation parameter optimization model and according to the first operation data and the heat dissipation requirement, so as to control the immersion liquid cooling system to perform the corresponding heat dissipation operation according to the obtained target control parameter, which can realize intelligent monitoring and optimization of the heat dissipation operation of the immersion liquid cooling system, thereby improving the control flexibility and control accuracy of the heat dissipation system while achieving efficient heat dissipation, and further facilitating improving the heat dissipation accuracy and heat dissipation efficiency of the heat dissipation system for the computing system, and further facilitating improving the operation stability and operation safety of the computing system.

[0194] In an optional embodiment, the second operation data includes device temperature data corresponding to the computing system, device cumulative operation duration data corresponding to the computing system, device operation time period data corresponding to the computing system, and device operation performance data corresponding to the computing system;

[0195] Among them, the specific manner in which the analysis module 302 analyzes the heat dissipation requirement information corresponding to the computing system according to the second operation data may include:

[0196] Estimate the operation heat information generated by the computing system within a preset time period according to the second operation data;

[0197] Generate heat dissipation requirement information corresponding to the computing system according to the operation heat information.

[0198] It can be seen that the system described in the optional embodiment can estimate the operation heat that the computing system may generate according to the second operation data corresponding to the computing system, and then generate heat dissipation requirement information according to the operation heat information, which can improve the estimation accuracy of the operation heat information of the computing system by accurately analyzing the operation situation of the computing system, thereby facilitating improving the determination accuracy of the heat dissipation requirement information corresponding to the computing system, and further facilitating improving the optimization accuracy of the heat dissipation operation of the immersion liquid cooling system.

[0199] In another alternative embodiment, the adjustment module 303 adjusts the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the first operation data and the heat dissipation requirement information based on the determined heat dissipation parameter optimization model. The specific manner of obtaining the target control parameters corresponding to the immersion liquid cooling system may include:

[0200] According to the first operation data, determine the current heat dissipation capacity of the immersion liquid cooling system; the current heat dissipation capacity is used to represent the heat dissipation amount and / or heat dissipation efficiency that the immersion liquid cooling system can achieve under the first operation data;

[0201] According to the heat dissipation requirement information, determine the target heat dissipation capacity that the immersion liquid cooling system needs to achieve;

[0202] Based on the determined heat dissipation parameter optimization model, adjust the heat dissipation control parameters corresponding to the immersion liquid cooling system according to the target heat dissipation capacity and the current heat dissipation capacity to obtain the target control parameters corresponding to the immersion liquid cooling system.

[0203] It can be seen that the system described in this alternative embodiment can determine the current heat dissipation capacity of the immersion liquid cooling system according to the first operation data, determine the target heat dissipation capacity that the immersion liquid cooling system needs to achieve according to the heat dissipation requirement information, and then based on the determined heat dissipation parameter optimization model, combine the target heat dissipation capacity and the current heat dissipation capacity to adjust the heat dissipation control parameters to obtain the target control parameters corresponding to the immersion liquid cooling system, which can improve the analysis accuracy of the heat dissipation capacity corresponding to the heat dissipation system, thereby facilitating the improvement of the optimization accuracy of the heat dissipation control parameters, and further facilitating the improvement of the control precision of the heat dissipation system.

[0204] In yet another alternative embodiment, the immersion liquid cooling system includes multiple subsystems, and each subsystem is one of a liquid cooling cabinet system, a circulating liquid pump cabinet system, and an outdoor heat dissipation system;

[0205] Among them, as Figure 4 shown, the system may further include:

[0206] A first acquisition module 305, configured to acquire the operation standard indexes corresponding to the immersion liquid cooling system and the index value ranges corresponding to the operation standard indexes;

[0207] The analysis module 302 is further configured to analyze the first operation data according to the operation standard indexes and the index value ranges to obtain an operation prediction result corresponding to the immersion liquid cooling system;

[0208] A judgment module 306, configured to judge whether the immersion liquid cooling system meets the preset abnormal operation judgment conditions according to the operation prediction result;

[0209] A generating module 307, configured to generate a system maintenance plan for the operation prediction result according to the first operation data and the operation prediction result when the determination module 306 determines that the immersion liquid cooling system meets the abnormal operation determination condition;

[0210] A maintenance module 308, configured to perform system maintenance operations on the immersion liquid cooling system according to the system maintenance plan.

[0211] It can be seen that the system described in implementing this optional embodiment can analyze the first operation data through the operation standard indicators and the corresponding indicator value ranges, so as to predict the operation prediction result of the immersion liquid cooling system, and then determine whether the immersion liquid cooling system operates abnormally according to the operation prediction result. If the system meets the abnormal operation condition, a system maintenance plan for the operation prediction result is generated to maintain the system, which can realize real-time monitoring and prediction of the abnormal operation of the immersion liquid cooling system, thereby improving the prediction accuracy of the operation of the heat dissipation system, further facilitating the timely determination of abnormalities in the heat dissipation system, improving the timeliness of fault handling in the heat dissipation system, and further enhancing the operation safety of the heat dissipation system.

[0212] In this optional embodiment, optionally, the first operation data includes the subsystem operation data corresponding to each subsystem in the immersion liquid cooling system; the operation standard indicators include the subsystem standard indicators corresponding to each subsystem in the immersion liquid cooling system;

[0213] Among them, the specific manner in which the analysis module 302 analyzes the first operation data according to the operation standard indicators and the indicator value ranges to obtain the operation prediction result corresponding to the immersion liquid cooling system may include:

[0214] For each subsystem in the immersion liquid cooling system, analyze the operation data value corresponding to the subsystem operation data of the subsystem and the indicator value range corresponding to the subsystem standard indicator of the subsystem to obtain the numerical analysis result corresponding to the subsystem; the numerical analysis result includes a numerical comparison result and a numerical change trend analysis result;

[0215] For each subsystem in the immersion liquid cooling system, detect whether there is alarm data in the subsystem operation data corresponding to the subsystem to obtain the alarm detection result corresponding to the subsystem;

[0216] For each subsystem in the immersion liquid cooling system, generate the subsystem prediction result corresponding to the subsystem according to the numerical analysis result and the alarm detection result; the subsystem status prediction result includes a subsystem numerical prediction result and a subsystem status prediction result;

[0217] According to the subsystem prediction results corresponding to all subsystems, determine the operation status prediction result corresponding to the immersion liquid cooling system;

[0218] Among them, the operation prediction results include the subsystem prediction results corresponding to each subsystem and the operation status prediction results.

[0219] It can be seen that the system described in this optional embodiment can also analyze, for each subsystem in the immersion liquid cooling system, the operation data values corresponding to the subsystem operation data of this subsystem and the index value range corresponding to the subsystem standard index of this subsystem, obtain the numerical analysis result corresponding to this subsystem, and detect whether there is alarm data in the subsystem operation data corresponding to this subsystem, obtain the alarm detection result corresponding to this subsystem, then generate a subsystem prediction result according to the numerical analysis result and the alarm detection result, and then comprehensively determine the operation status prediction result of the immersion liquid cooling system based on all subsystem prediction results, which can achieve targeted prediction of the predicted operation conditions of each subsystem, thereby improving the analysis accuracy of the operation prediction results of the immersion liquid cooling system, and further facilitating the timely discovery and handling of abnormal operation conditions of the heat dissipation system subsequently.

[0220] In this optional embodiment, optionally, as Figure 4 shown, the system may further include:

[0221] A second acquisition module 309, configured to acquire the system structure information corresponding to the immersion liquid cooling system; the system structure information includes the connection relationship between multiple subsystems and / or the device structure information corresponding to each subsystem;

[0222] A determination module 310, configured to, for each subsystem in the immersion liquid cooling system, determine the predicted operation influence coefficient of the remaining subsystems on this subsystem according to the system structure information; the predicted operation influence coefficient is used to represent the influence degree of the operation conditions of the remaining subsystems on the operation conditions of this subsystem;

[0223] Among them, for each subsystem in the immersion liquid cooling system, the specific manner in which the analysis module 302 generates the subsystem prediction result corresponding to this subsystem according to the numerical analysis result and the alarm detection result includes:

[0224] Generate an initial prediction result corresponding to this subsystem according to the numerical analysis result and the alarm detection result;

[0225] Optimize the initial prediction result corresponding to this subsystem according to the predicted operation influence coefficient of the remaining subsystems on this subsystem, and obtain the subsystem prediction result corresponding to this subsystem.

[0226] It can be seen that the system described in implementing this optional embodiment can also, for each subsystem in the immersion liquid cooling system, determine the predicted operation influence coefficient of the remaining subsystems on this subsystem according to the obtained system structure information, and then optimize the initial prediction result corresponding to this subsystem according to the predicted operation influence coefficient to obtain the subsystem prediction result corresponding to this subsystem. It can optimize the operation prediction result by analyzing the operation influence of other subsystems on this subsystem, thereby improving the prediction accuracy of the operation of the subsystem, and further facilitating the analysis accuracy of the operation prediction result of the immersion liquid cooling system, and further facilitating the subsequent timely discovery and handling of abnormal operation conditions of the heat dissipation system.

[0227] In this optional embodiment, optionally, the specific manner in which the judgment module 306 determines whether the immersion liquid cooling system meets the preset abnormal operation judgment conditions according to the operation prediction result may include:

[0228] For each subsystem in the immersion liquid cooling system, when the subsystem numerical prediction result corresponding to this subsystem is an abnormal numerical prediction result or the subsystem state prediction result corresponding to this subsystem is a first abnormal state prediction result, determine this subsystem as a predicted abnormal subsystem;

[0229] Judge whether there is a predicted abnormal subsystem in the immersion liquid cooling system or whether the operation state prediction result is a second abnormal state prediction result;

[0230] When it is judged that there is a predicted abnormal subsystem in the immersion liquid cooling system or the operation state prediction result is a second abnormal state prediction result, determine that the immersion liquid cooling system meets the preset abnormal operation judgment conditions;

[0231] When it is judged that there is no predicted abnormal subsystem in the immersion liquid cooling system or the operation state prediction result is not a second abnormal state prediction result, determine that the immersion liquid cooling system does not meet the preset abnormal operation judgment conditions.

[0232] It can be seen that the system described in implementing this optional embodiment can also determine that the immersion liquid cooling system meets the abnormal operation judgment conditions when it is judged that there is a predicted abnormal subsystem or the operation state prediction result is a second abnormal state prediction result, that is, determine that the immersion liquid cooling system has an abnormality, which can improve the judgment accuracy of whether the heat dissipation system meets the abnormal operation judgment conditions, thereby facilitating the improvement of the abnormal determination accuracy of the heat dissipation system, and further facilitating the improvement of the fault handling accuracy of the heat dissipation system.

[0233] Embodiment 4

[0234] Please refer to Figure 5 , Figure 5It is a schematic structural diagram of another intelligent control and monitoring system applied to an immersion liquid cooling system disclosed in an embodiment of the present invention. As Figure 5 shown, the intelligent control and monitoring system applied to the immersion liquid cooling system may include:

[0235] A memory 401 storing executable program code;

[0236] A processor 402 coupled to the memory 401;

[0237] The processor 402 calls the executable program code stored in the memory 401 and executes some or all of the steps in the intelligent control and monitoring method applied to the immersion liquid cooling system described in Embodiment 1 or Embodiment 2 of the present invention.

[0238] Embodiment 5

[0239] An embodiment of the present invention discloses a computer storage medium. When the computer instructions stored in the computer storage medium are called, they are used to execute some or all of the steps in the intelligent control and monitoring method applied to the immersion liquid cooling system described in Embodiment 1 or Embodiment 2 of the present invention.

[0240] Embodiment 6

[0241] An embodiment of the present invention discloses a computer program product. The computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps in the intelligent control and monitoring method applied to the immersion liquid cooling system described in Embodiment 1 or Embodiment 2.

[0242] The system embodiments described above are only illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0243] Through the specific descriptions of the above embodiments, those skilled in the art can clearly understand that each implementation mode can be realized by means of software plus a necessary general hardware platform, and of course, it can also be realized by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, and the storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other medium that can be used to carry or store data and is computer-readable.

[0244] Finally, it should be noted that: The intelligent control and monitoring method and system applied to the immersion liquid cooling system disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, and are only used to illustrate the technical solutions of the present invention, rather than limiting them; Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; And these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent control and monitoring method for an immersion liquid cooling system, characterized in that: The method comprises: Monitoring an immersion liquid cooling system and a computing system corresponding to the immersion liquid cooling system to obtain first operating data of the immersion liquid cooling system for the computing system and second operating data of the computing system; analyzing heat dissipation requirement information corresponding to the computing system according to the second operating data; Based on the determined heat dissipation parameter optimization model, and according to the first operating data and the heat dissipation demand information, adjusting the heat dissipation control parameters corresponding to the immersion liquid cooling system to obtain target control parameters corresponding to the immersion liquid cooling system; According to the target control parameter, the immersion liquid cooling system is controlled to perform a heat dissipation operation corresponding to the target control parameter on the computing system.

2. The intelligent control and monitoring method for an immersion liquid cooling system according to claim 1, characterized in that: The second operation data includes device temperature data corresponding to the computing system, accumulated operation time data of the device corresponding to the computing system, operation time period data of the device corresponding to the computing system, and operation performance data of the device corresponding to the computing system; The step of analyzing the heat dissipation requirement information corresponding to the computing system according to the second operating data includes: estimating the operating heat information generated by the computing system within a preset time period according to the second operating data; According to the operating heat information, heat dissipation requirement information corresponding to the computing system is generated.

3. The intelligent control and monitoring method for an immersion liquid cooling system according to claim 1 is characterized in that: The heat dissipation control parameters corresponding to the immersion liquid cooling system are adjusted based on the determined heat dissipation parameter optimization model according to the first operating data and the heat dissipation demand information to obtain target control parameters corresponding to the immersion liquid cooling system, including: Determining a current heat dissipation capacity of the immersion liquid cooling system according to the first operating data; the current heat dissipation capacity is used to indicate the heat dissipation amount and / or heat dissipation efficiency that can be achieved by the immersion liquid cooling system under the first operating data; Determining a target heat dissipation capacity that the immersion liquid cooling system needs to achieve based on the heat dissipation demand information; Based on the determined heat dissipation parameter optimization model, the heat dissipation control parameters corresponding to the immersion liquid cooling system are adjusted according to the target heat dissipation capacity and the current heat dissipation capacity to obtain the target control parameters corresponding to the immersion liquid cooling system.

4. The intelligent control and monitoring method for an immersion liquid cooling system according to any one of claims 1 to 3, characterized in that: The immersion liquid cooling system includes a plurality of subsystems, and each of the subsystems is one of a liquid cooling cabinet system, a circulating liquid pump cabinet system, and an outdoor heat dissipation system; Wherein, the method further comprises: Obtaining an operating standard index corresponding to the immersion liquid cooling system and an index value range corresponding to the operating standard index; Analyzing the first operating data according to the operating standard index and the index value range to obtain an operating prediction result corresponding to the immersion liquid cooling system; According to the operation prediction result, determining whether the immersion liquid cooling system meets a preset abnormal operation determination condition; When it is determined that the immersion liquid cooling system meets the abnormal operation determination condition, generating a system maintenance plan for the operation prediction result according to the first operation data and the operation prediction result; According to the system maintenance plan, a system maintenance operation is performed on the immersion liquid cooling system.

5. The intelligent control and monitoring method for an immersion liquid cooling system according to claim 4 is characterized in that: The first operating data includes subsystem operating data corresponding to each of the subsystems in the immersion liquid cooling system; the operating standard index includes a subsystem standard index corresponding to each of the subsystems in the immersion liquid cooling system; Wherein, analyzing the first operating data according to the operating standard index and the index value range to obtain the operating prediction result corresponding to the immersion liquid cooling system includes: For each of the subsystems in the immersion liquid cooling system, the operating data value corresponding to the subsystem operating data corresponding to the subsystem and the indicator value interval corresponding to the subsystem standard indicator corresponding to the subsystem are analyzed to obtain the numerical analysis result corresponding to the subsystem; the numerical analysis result includes a numerical comparison result and a numerical change trend analysis result; For each of the subsystems in the immersion liquid cooling system, detect whether there is alarm data in the subsystem operation data corresponding to the subsystem, and obtain an alarm detection result corresponding to the subsystem; For each of the subsystems in the immersion liquid cooling system, a subsystem prediction result corresponding to the subsystem is generated according to the numerical analysis result and the alarm detection result; the subsystem state prediction result includes a subsystem numerical prediction result and a subsystem state prediction result; Determine the operation state prediction result corresponding to the immersion liquid cooling system according to the subsystem prediction results corresponding to all the subsystems; The operation prediction result includes a subsystem prediction result corresponding to each of the subsystems and the operation status prediction result.

6. The intelligent control and monitoring method for an immersion liquid cooling system according to claim 5, characterized in that: The method further comprises: Obtaining system structure information corresponding to the immersion liquid cooling system; the system structure information includes connection relationships between the plurality of subsystems and / or device structure information corresponding to each subsystem; For each of the subsystems in the immersion liquid cooling system, determine a predicted operation influence coefficient of the remaining subsystems on the subsystem according to the system structure information; the predicted operation influence coefficient is used to indicate the degree of influence of the operation conditions of the remaining subsystems on the operation conditions of the subsystem; Wherein, for each of the subsystems in the immersion liquid cooling system, generating a subsystem prediction result corresponding to the subsystem according to the numerical analysis result and the alarm detection result includes: Generate an initial prediction result corresponding to the subsystem according to the numerical analysis result and the alarm detection result; According to the predicted operation influence coefficients of the remaining subsystems on the subsystem, the initial prediction result corresponding to the subsystem is optimized to obtain the subsystem prediction result corresponding to the subsystem.

7. The intelligent control and monitoring method for an immersion liquid cooling system according to claim 5 or 6, characterized in that: The step of judging whether the immersion liquid cooling system meets a preset abnormal operation judgment condition according to the operation prediction result includes: For each of the subsystems in the immersion liquid cooling system, when a subsystem numerical prediction result corresponding to the subsystem is an abnormal numerical prediction result or a subsystem state prediction result corresponding to the subsystem is a first abnormal state prediction result, the subsystem is determined as a predicted abnormal subsystem; Determine whether the predicted abnormal subsystem exists in the immersion liquid cooling system or whether the operation state prediction result is a second abnormal state prediction result; When it is determined that the predicted abnormal subsystem exists in the immersion liquid cooling system or the operation state prediction result is the second abnormal state prediction result, determining that the immersion liquid cooling system meets a preset abnormal operation judgment condition; When it is determined that the predicted abnormal subsystem does not exist in the immersion liquid cooling system or the operation state prediction result is not the second abnormal state prediction result, it is determined that the immersion liquid cooling system does not meet the preset abnormal operation judgment condition.

8. An intelligent control and monitoring system for an immersion liquid cooling system, characterized in that: The system comprises: A monitoring module, used to monitor the immersion liquid cooling system and the computing system corresponding to the immersion liquid cooling system, and obtain first operating data of the immersion liquid cooling system for the computing system and second operating data of the computing system; an analysis module, configured to analyze heat dissipation requirement information corresponding to the computing system according to the second operation data; an adjustment module, configured to adjust the heat dissipation control parameters corresponding to the immersion liquid cooling system based on the determined heat dissipation parameter optimization model and according to the first operating data and the heat dissipation demand information, so as to obtain target control parameters corresponding to the immersion liquid cooling system; A control module is used to control the immersion liquid cooling system to perform a heat dissipation operation corresponding to the target control parameter on the computing system according to the target control parameter.

9. An intelligent control and monitoring system for an immersion liquid cooling system, characterized in that: The system comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the intelligent control and monitoring method for an immersion liquid cooling system as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, which, when called, are used to execute the intelligent control and monitoring method for an immersion liquid cooling system as described in any one of claims 1 to 7.

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