A method and device for protecting a liquid cooling system, electronic equipment and storage medium

Abstract

The application provides a method and device for protecting a liquid cooling system, electronic equipment and a storage medium, the method comprising: generating a target data model of a target liquid cooling system according to a basic curve and historical operation data of each component in the target liquid cooling system; monitoring the target liquid cooling system in operation and obtaining current operation data of the target liquid cooling system in operation; inputting the current operation data into the target data model to obtain an operation result output by the target data model; and taking a protection measure corresponding to the operation result on the target liquid cooling system according to the operation result. The application can monitor each component in the target liquid cooling system, and each component has its own monitoring standard. When any component in the target liquid cooling system fails, the monitoring standard can timely alarm and take a protection measure, thereby improving the accuracy of protection of the target liquid cooling system and avoiding property loss.

Description

Technical Field

[0001] This application relates to the field of liquid cooling system technology, and more specifically, to a method, apparatus, electronic device, and storage medium for protecting a liquid cooling system. Background Technology

[0002] With the rapid development of technology, the burden on various processing equipment is also increasing dramatically, generating a large amount of heat. If this heat cannot be released in time, it will significantly impact the lifespan of the processing equipment. To eliminate the heat generated by processing equipment, liquid cooling systems have emerged, which remove heat through the flow of liquid.

[0003] To ensure the safe operation of liquid cooling systems, corresponding protective measures are implemented. In existing technologies, protection for liquid cooling systems is based on the extreme operating conditions of certain components within the system. Since liquid cooling systems contain numerous components, this approach only activates protection measures when the specific operating conditions of each component are reached, resulting in insufficient precision and failing to meet current operational requirements. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a method, apparatus, electronic device and storage medium for protecting a liquid cooling system, which can more accurately protect the liquid cooling system.

[0005] In a first aspect, embodiments of this application provide a method for protecting a liquid cooling system, the method comprising:

[0006] For the target liquid cooling system, a target data model of the target liquid cooling system is generated based on the basic curves and historical operating data of each component in the target liquid cooling system.

[0007] Monitor the target liquid cooling system that is in operation and acquire the current operating data of the target liquid cooling system;

[0008] The current running data is input into the target data model to obtain the running results output by the target data model;

[0009] Based on the operational results, protective measures corresponding to the operational results are taken for the target liquid cooling system.

[0010] In some technical solutions of this application, the above-mentioned generation of the target data model of the target liquid cooling system based on the basic curves and historical operating data of each component in the target liquid cooling system includes:

[0011] Based on the basic curves and historical operating data of each component in the target liquid cooling system, a target sub-data model for each component is generated.

[0012] The target sub-data models of each component in the target liquid cooling system are integrated to obtain the target data model of the target liquid cooling system.

[0013] In some technical solutions of this application, each component corresponds to multiple types of historical operating data and multiple types of basic curves; the method targets the sub-data model in the following ways, including:

[0014] Based on the historical operating data of each type of component in the target liquid cooling system, the intermediate data of that type of historical operating data is determined.

[0015] Based on the basic curves of each component in the target liquid cooling system and the intermediate data corresponding to the basic curves, the historical operating curves of the components under this type are generated.

[0016] By integrating the historical operating curves of the components under each type, the target sub-data model of the components is obtained.

[0017] In some technical solutions of this application, the above method also includes:

[0018] The response interval configuration operation generates corresponding warning intervals on each historical running curve of the target sub-data model.

[0019] In some technical solutions of this application, the above-mentioned inputting the current running data into the target data model to obtain the running result output by the target data model includes:

[0020] The current running data is input into the target data model, and the target data model compares the historical running curve corresponding to the current running data in the corresponding target sub-data model.

[0021] The operating result is determined based on the range of each warning interval in the historical operating curve and the current operating data.

[0022] Secondly, embodiments of this application provide a device for protecting a liquid cooling system, the device comprising:

[0023] The generation module is used to generate a target data model of the target liquid cooling system based on the basic curves and historical operating data of each component in the target liquid cooling system.

[0024] The acquisition module is used to monitor the target liquid cooling system in operation and acquire the current operating data of the target liquid cooling system in operation;

[0025] The first processing model is used to input the current running data into the target data model and obtain the running results output by the target data model;

[0026] The second processing model is used to take protective measures for the target liquid cooling system based on the operating results.

[0027] In some technical solutions of this application, the above-mentioned generation module is also used to generate target sub-data models of each component based on the basic curves and historical operating data of each component in the target liquid cooling system.

[0028] The target sub-data models of each component in the target liquid cooling system are integrated to obtain the target data model of the target liquid cooling system.

[0029] In some technical solutions of this application, the above-mentioned generation module is also used to: determine the intermediate data of the historical operating data of each type of component in the target liquid cooling system;

[0030] Based on the basic curves of each component in the target liquid cooling system and the intermediate data corresponding to the basic curves, the historical operating curves of the components under this type are generated.

[0031] By integrating the historical operating curves of the components under each type, the target sub-data model of the components is obtained.

[0032] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for protecting a liquid cooling system.

[0033] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the above-described method for protecting a liquid cooling system.

[0034] The technical solutions provided by the embodiments of this application may include the following beneficial effects:

[0035] This application's method includes: generating a target data model for a target liquid cooling system based on the fundamental curves and historical operating data of each component in the target liquid cooling system; monitoring the target liquid cooling system in operation and acquiring its current operating data; inputting the current operating data into the target data model to obtain the operating result output by the target data model; and taking protective measures corresponding to the operating result for the target liquid cooling system. This application generates a target sub-data model for each component by analyzing its fundamental curves and historical operating data, thereby generating the target data model for the entire target liquid cooling system. This method enables monitoring of each component in the target liquid cooling system, and each component has its own monitoring standard. When any component in the target liquid cooling system fails, the monitoring standard promptly issues an alarm and collects protective measures, improving the accuracy of protection for the target liquid cooling system and preventing property damage.

[0036] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0037] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 A flowchart illustrating a method for protecting a liquid cooling system provided in an embodiment of this application is shown;

[0039] Figure 2 This illustration shows a schematic diagram of a prior art provided by an embodiment of this application;

[0040] Figure 3 This illustration shows another prior art schematic provided by an embodiment of this application;

[0041] Figure 4 A schematic diagram of a device for protecting a liquid cooling system provided in an embodiment of this application is shown;

[0042] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0044] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0045] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0046] The characteristics of liquid cooling systems include: continuous operation 24 / 7, multiple operating states (light load, heavy load, full load, overload), precise control of small modules (small capacity of individual components), significant seasonality (e.g., extremely low load ratio in winter, extremely high load ratio in summer), and large margin for extreme operating conditions (e.g., in summer, when extremely high temperatures occur, the system and its components' failure rate exceeds 15%, the overall efficiency does not exceed 80%, and even significant overload operation occurs). Given these characteristics, many components need to be selected based on extreme operating conditions to ensure reliable and stable system operation. However, this also introduces other problems. Under normal system operation, the components have a large margin; when a component fails, its own protection conditions are not met, resulting in delayed action. Secondly, due to the inherent characteristics of the components and the uncertainty of the interface with the user, when a component fails, it only initiates its own protection action without feedback to the branch circuits or the main system. In this case, when the fault is significant, the component's own protection action may fail to protect itself, causing system impact and even system paralysis. For example, when the frequency converter fails, the pump may not stop or may even run overload. Because of the fault, the frequency converter cannot provide protection, and the system can only passively wait for a short circuit to occur before the protection system can activate. When the short circuit occurs, it can cause the branch circuit or even the entire system to trip and shut down. Furthermore, depending on the characteristics of different components and their operating time, the aging and wear of the components will vary, ultimately resulting in different failure probabilities. Therefore, the failure probabilities of different components need to be calculated separately.

[0047] Current electrical protection in the industry mainly relies on the inherent physical properties of each component. For example, the protective action of a circuit breaker is achieved through thermomagnetic tripping, which is a fixed curve (as shown below). Figure 2 For example, the protection action of a frequency converter is also based on a fixed characteristic curve (as shown below). Figure 3 While existing protection systems offer some customization options for protecting the equipment itself, key protection features are determined by fixed protection curves. These fixed protection characteristics cannot be customized based on the system or different situations. Furthermore, considering environmental factors and the wear and tear from long-term operation, the performance degradation rate of these components cannot be qualitatively or quantitatively determined. Ultimately, for liquid cooling systems, the response speed and accuracy of existing protection systems are insufficient, forcing systems to passively wait for problems to occur before replacing them, leaving serious hidden dangers.

[0048] Based on this, the present application provides a method, apparatus, electronic device, and storage medium for protecting a liquid cooling system, which are described below through embodiments.

[0049] Figure 1 The diagram illustrates a flow chart of a method for protecting a liquid cooling system according to an embodiment of this application, wherein the method includes steps S101-S104; specifically:

[0050] S101. For the target liquid cooling system, generate a target data model of the target liquid cooling system based on the basic curves and historical operating data of each component in the target liquid cooling system.

[0051] S102. Monitor the target liquid cooling system that is in operation and obtain the current operating data of the target liquid cooling system;

[0052] S103. Input the current running data into the target data model to obtain the running results output by the target data model;

[0053] S104. Based on the operating results, take protective measures for the target liquid cooling system corresponding to the operating results.

[0054] This application analyzes the basic curves and historical operating data of each component in the target liquid cooling system to generate a target sub-data model for each component, thereby generating a target data model for the target liquid cooling system. This enables monitoring of each component in the target liquid cooling system, and each component has its own monitoring standard. When any component in the target liquid cooling system fails, the monitoring standard will promptly issue an alarm and collect protective measures, improving the accuracy of protection for the target liquid cooling system and avoiding property damage.

[0055] The following describes some embodiments of this application in detail. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0056] S101. For the target liquid cooling system, generate a target data model of the target liquid cooling system based on the basic curves and historical operating data of each component in the target liquid cooling system.

[0057] Currently, there are various liquid cooling systems on the market. Their main working principle is to remove heat by the flow of a heat-dissipating liquid (such as water), and each type of liquid cooling system consists of multiple components. For ease of description, the liquid cooling system to be protected in this application embodiment is referred to as the target liquid cooling system.

[0058] To provide more comprehensive and accurate protection for the target liquid cooling system, this embodiment of the application sets individual warning conditions for each component in the target liquid cooling system. When setting warning conditions for each component, this embodiment of the application first acquires the basic curves and historical operating data of each component in the target liquid cooling system.

[0059] The baseline curves here are those provided by the component at the factory, such as the current versus temperature curve or the voltage versus temperature curve for a particular component. The operating data here (including historical and current operating data) represents the component's environmental and attribute data. Environmental data includes the component's operating temperature and operating pressure, while attribute data includes electrical parameters such as voltage and current.

[0060] This application embodiment generates a target data model of the target liquid cooling system by analyzing the basic curves and historical operating data of each component.

[0061] As an optional embodiment of this application, when generating the target data model of the target liquid cooling system, this embodiment first generates the target sub-data models of each component in the target liquid cooling system, and then generates the target data model of the target liquid cooling system.

[0062] The specific process is as follows: Based on the basic curves and historical operating data of each component in the target liquid cooling system, a target sub-data model of each component is generated; the target sub-data models of each component in the target liquid cooling system are integrated to obtain the target data model of the target liquid cooling system.

[0063] Furthermore, each component corresponds to multiple types of historical operating data and multiple types of basic curves; the method targets the sub-data model in the following ways, including:

[0064] Based on the historical operating data of each type of component in the target liquid cooling system, the intermediate data of that type of historical operating data is determined.

[0065] Based on the basic curves of each component in the target liquid cooling system and the intermediate data corresponding to the basic curves, the historical operating curves of the components under this type are generated.

[0066] By integrating the historical operating curves of the components under each type, the target sub-data model of the components is obtained.

[0067] In this embodiment, the target liquid cooling system includes multiple components, and each component includes multiple types of historical operating data. The "types" here refer to the distinction between historical operating data; for example, historical operating temperature and historical operating pressure are two different types. On the other hand, each manufacturer measures each component at the factory to obtain its baseline curve. Since each component has multiple attributes or characteristics, multiple measurements are required to obtain multiple types of baseline curves. These "types" refer to the distinction between baseline curves; for example, voltage versus temperature is one type, and liquid flow rate versus temperature is another. When manufacturers measure components, they generally only measure a few data points, meaning the baseline curve contains relatively little data. This embodiment combines historical operating data to obtain more comprehensive component data. For example, if the baseline curve only includes voltage values ​​at 20°C and 30°C for a certain component, monitoring the component based solely on these two values ​​is clearly insufficient. This application analyzes the historical operating data (historical operating temperature and historical operating voltage) of the component, expanding the original basic curve with only two temperature values ​​of 20° and 30° to a historical operating curve that includes 20°, 22°, 24°, 26°, 26° and 30° (in specific implementation, the number of data values ​​can be selected as needed).

[0068] On another front, the types of basic curves for components are limited. To enable more accurate monitoring of these components, this application embodiment also generates historical operating curves of a different type than the basic curves based on the basic curves and historical operating data. Specifically, this application generates intermediate data corresponding to the historical operating data based on the historical operating curves, and then generates historical operating curves based on the intermediate data and the basic curves. For example, if the target liquid cooling system only has basic curves showing the changes in component temperature, this application embodiment analyzes the historical operating data to determine the impact of operating time on the components, and then combines this with the basic curves showing the changes in component temperature to obtain the component's failure rate, and then generates a curve showing the change in the failure rate.

[0069] After generating the historical operating curves for each component, all historical operating curves are integrated to obtain the integrated target sub-data model of the component. In other words, this target sub-data model contains multiple integrated curves. These integrated curves exhibit parallelism and intersection, and are combined to serve as the monitoring standard for the component.

[0070] As an optional embodiment of this application, in order to achieve more intelligent monitoring, this application also sets warning intervals on each curve in the target sub-data model. These warning intervals trigger alarms for the current operating data. Specifically, in response to the interval configuration operation, corresponding warning intervals are generated on each historical operating curve of the target sub-data model.

[0071] After obtaining the target data model of the target liquid cooling system, this embodiment of the application can monitor the operating target liquid cooling system based on the target data model to achieve automatic alarm. Specifically, the operating target liquid cooling system is monitored, and its current operating data is acquired. The current operating data is input into the target data model, which compares it with the historical operating curve corresponding to the current operating data in the corresponding target sub-data model. Based on the range of each warning interval in the historical operating curve and the current operating data, the operating result is determined. Based on the operating result, protective measures corresponding to the operating result are taken for the target liquid cooling system.

[0072] After acquiring the current operating data of the target liquid cooling system, it is compared with various warning intervals in the target data model. Different operating results are generated when the current operating data falls within different warning intervals. These results include whether an alarm has been triggered and the alarm level. To handle alarm events more efficiently, this application also sets corresponding protection measures for each alarm interval. After determining whether an alarm has been triggered and the alarm level, corresponding protection measures can be obtained. Timely implementation of these measures effectively protects the target liquid cooling system and prevents property damage.

[0073] In practical implementation, this embodiment can be manufactured as a liquid cooling system intelligent protection module (KPM), mainly consisting of a KPM main control board, an SD card, a communication interface, sensors, and a storage capacitor. The main control board has a built-in database for data configuration; the SD card stores data; the communication interface interfaces with different devices using different communication protocols; the sensors collect data from monitoring points; and the storage capacitor ensures normal operation of the system for half an hour during a power outage.

[0074] KPM's built-in database covers data on different equipment models, including technical data for various brands and models of commonly used components, and allows for the customization of different data types. By analyzing component data under different environmental and operating condition combinations of the liquid cooling system, it first categorizes the equipment's operating conditions, then intelligently analyzes and judges the data, and finally provides intelligent feedback.

[0075] Define the database, input data into the KPM database, establish a dedicated data model, predefine various situations, intelligently combine them, and determine the final state. The main definitions are as follows:

[0076] The rack operating conditions are defined as follows: below 30% is light load, 30% to 80% is heavy load, 80% to 100% is full load, and 100% to 150% is overload.

[0077] The component status is defined as follows: within ±5% is normal, above ±5% is abnormal, above ±10% is protection, and above 20% is fault.

[0078] Operating environment is defined as follows: below 30℃ is normal, below 40℃ is severe, and above 40℃ is harsh.

[0079] The lifespan of a component is defined as follows: within 1 year it is good, within 3 years it is normal, within 5 years it is old, and more than 5 years it is ready for replacement.

[0080] The definition of component damage is as follows: less than 5% is good, less than 10% is minor, less than 15% is moderate, and more than 15% is severe.

[0081] Based on sensor detection data, the system uses intelligent data modeling to automatically analyze the data of each component. Under different environments and operating conditions, it automatically calculates the predicted data of the components and, combined with the actual operating data of the components, determines the status of the components and provides feedback to other units or systems.

[0082] For example, when the frequency converter malfunctions and cannot control the pump, the pump may become abnormal, resulting in overspeeding or runaway, which could cause the system to trip or crash. Connecting a KPM module can prevent such faults.

[0083] If the frequency converter is malfunctioning but the pump is functioning normally, the system is considered abnormal and requires attention or manual maintenance.

[0084] When the frequency converter malfunctions, the pump's status will also be abnormal. In this case, the affected branch will be stopped, the backup branch will be started, and a branch malfunction shutdown signal will be output.

[0085] When the frequency converter is in protection mode, the frequency converter and pump will be stopped immediately, and a branch protection signal will be output at the same time.

[0086] When the frequency converter is in protection mode, if the pump data does not enter the shutdown process as predicted, the power supply to the branch system will be immediately disconnected, and a branch protection disconnect signal will be output simultaneously.

[0087] When the frequency converter malfunctions, the branch power supply is immediately disconnected, and a branch fault disconnection signal is output.

[0088] Target data model establishment: First, the system and component states are predefined as the basic calculation conditions.

[0089] Secondly, different combinations of different states are predefined, and the relationships between different components are defined to form the foundation of the initial model. At the same time, all original factory data of equipment and components are entered into the model as the basis. Through communication interfaces and sensors, real-time data of the environment, system, and components are combined with the state definitions of the system and components to generate the basic prototype of the prediction results.

[0090] The model data of the component's predicted results are compared with the actual data. When the data matches, the system's healthy operation result is output. If the data does not match, but is within an acceptable range, abnormal data is identified, the component's status is traced, and self-repair processing is performed (the branch is temporarily suspended, a backup branch is used, original factory data is read, automatic testing and debugging are performed, and if the input-output correspondence does not match the original data, the deviation gain is automatically adjusted until the component data matches the original data, then the system is switched back to the branch). If repair is not possible, the branch is temporarily suspended, the backup branch is switched, and the abnormal status of the component is output.

[0091] Data analysis, as described in the model above, processes different real-time input data, analyzes the data type, the component to which it belongs, and the system to which it belongs, and combines it with predefined content, puts the data into a specific input port, and obtains results through the model.

[0092] A data model is a simulation and computation model that outputs specific results when real-time data is input. Based on a predefined state, it retrieves original equipment manufacturer (OEM) data and calculates the state the component should be in and the feedback data, then compares this with the output results to arrive at the final state result.

[0093] Figure 4 This illustration shows a structural schematic diagram of a liquid cooling system protection device provided in an embodiment of this application. The device includes:

[0094] The generation module is used to generate a target data model of the target liquid cooling system based on the basic curves and historical operating data of each component in the target liquid cooling system.

[0095] The acquisition module is used to monitor the target liquid cooling system in operation and acquire the current operating data of the target liquid cooling system in operation;

[0096] The first processing model is used to input the current running data into the target data model and obtain the running results output by the target data model;

[0097] The second processing model is used to take protective measures for the target liquid cooling system based on the operating results.

[0098] The step of generating a target data model for the target liquid cooling system based on the basic curves and historical operating data of each component in the target liquid cooling system includes:

[0099] Based on the basic curves and historical operating data of each component in the target liquid cooling system, a target sub-data model for each component is generated.

[0100] The target sub-data models of each component in the target liquid cooling system are integrated to obtain the target data model of the target liquid cooling system.

[0101] Each component corresponds to multiple types of historical operating data and multiple types of basic curves; the method targets the sub-data model in the following ways, including:

[0102] Based on the historical operating data of each type of component in the target liquid cooling system, the intermediate data of that type of historical operating data is determined.

[0103] Based on the basic curves of each component in the target liquid cooling system and the intermediate data corresponding to the basic curves, the historical operating curves of the components under this type are generated.

[0104] By integrating the historical operating curves of the components under each type, the target sub-data model of the components is obtained.

[0105] The device also includes a response module for responding to interval configuration operations, generating corresponding warning intervals on each historical running curve of the target sub-data model.

[0106] The step of inputting the current running data into the target data model to obtain the running result output by the target data model includes:

[0107] The current running data is input into the target data model, and the target data model compares the historical running curve corresponding to the current running data in the corresponding target sub-data model.

[0108] The operating result is determined based on the range of each warning interval in the historical operating curve and the current operating data.

[0109] like Figure 5 As shown, this application provides an electronic device for executing the liquid cooling system protection method of this application. The device includes a memory, a processor, a bus, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the liquid cooling system protection method described above.

[0110] Specifically, the aforementioned memory and processor can be general-purpose memory and processor, without any specific limitations. When the processor runs the computer program stored in the memory, it can execute the aforementioned liquid cooling system protection method.

[0111] Corresponding to the liquid cooling system protection method in this application, this application embodiment also provides a computer-readable storage medium storing a computer program, which is executed by a processor to perform the steps of the above-described liquid cooling system protection method.

[0112] Specifically, the storage medium can be a general-purpose storage medium, such as a removable disk or hard disk. When the computer program on the storage medium is run, it can execute the above-mentioned liquid cooling system protection method.

[0113] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. The system embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0114] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0115] In addition, the functional units in the embodiments provided in this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0116] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0117] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0118] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method for protecting a liquid cooling system, characterized in that, The method includes: For the target liquid cooling system, a target data model of the target liquid cooling system is generated based on the basic curves and historical operating data of each component in the target liquid cooling system; wherein, the basic curves are limited data obtained at the time of factory delivery; the target data model includes more comprehensive data; Monitor the target liquid cooling system that is in operation and acquire the current operating data of the target liquid cooling system; The current running data is input into the target data model to obtain the running results output by the target data model; Based on the operational results, protective measures corresponding to the operational results shall be taken for the target liquid cooling system; The step of generating a target data model for the target liquid cooling system based on the basic curves and historical operating data of each component in the target liquid cooling system includes: Based on the basic curves and historical operating data of each component in the target liquid cooling system, a target sub-data model for each component is generated. The target sub-data models of each component in the target liquid cooling system are integrated to obtain the target data model of the target liquid cooling system. Each component corresponds to multiple types of historical operating data and multiple types of basic curves; the method targets the sub-data model in the following ways, including: Based on the historical operating data of each type of component in the target liquid cooling system, the intermediate data of that type of historical operating data is determined. Based on the basic curves of each component in the target liquid cooling system and the intermediate data corresponding to the basic curves, the historical operating curves of the components under this type are generated. By integrating the historical operating curves of the components under each type, the target sub-data model of the components is obtained.

2. The method according to claim 1, characterized in that, The method further includes: The response interval configuration operation generates corresponding warning intervals on each historical running curve of the target sub-data model.

3. The method according to claim 2, characterized in that, The step of inputting the current running data into the target data model to obtain the running result output by the target data model includes: The current running data is input into the target data model, and the target data model compares the historical running curve corresponding to the current running data in the corresponding target sub-data model. The operating result is determined based on the range of each warning interval in the historical operating curve and the current operating data.

4. A device for protecting a liquid cooling system, characterized in that, The device includes: The generation module is used to generate a target data model for the target liquid cooling system based on the basic curves and historical operating data of each component in the target liquid cooling system; wherein the basic curves are limited data obtained at the time of factory delivery; and the target data model includes more comprehensive data. The acquisition module is used to monitor the target liquid cooling system in operation and acquire the current operating data of the target liquid cooling system in operation; The first processing model is used to input the current running data into the target data model and obtain the running results output by the target data model; The second processing model is used to take protective measures for the target liquid cooling system based on the operating results; The step of generating a target data model for the target liquid cooling system based on the basic curves and historical operating data of each component in the target liquid cooling system includes: Based on the basic curves and historical operating data of each component in the target liquid cooling system, a target sub-data model for each component is generated. The target sub-data models of each component in the target liquid cooling system are integrated to obtain the target data model of the target liquid cooling system. Each component corresponds to multiple types of historical operating data and multiple types of basic curves; the target sub-data model is achieved through the following methods, including: Based on the historical operating data of each type of component in the target liquid cooling system, the intermediate data of that type of historical operating data is determined. Based on the basic curves of each component in the target liquid cooling system and the intermediate data corresponding to the basic curves, the historical operating curves of the components under this type are generated. By integrating the historical operating curves of the components under each type, the target sub-data model of the components is obtained.

5. The apparatus according to claim 4, characterized in that, The generation module is also used to generate target sub-data models for each component based on the basic curves and historical operating data of each component in the target liquid cooling system. The target sub-data models of each component in the target liquid cooling system are integrated to obtain the target data model of the target liquid cooling system.

6. The apparatus according to claim 5, characterized in that, The generation module is further configured to: determine the intermediate data of the historical operating data of each type of component in the target liquid cooling system based on the historical operating data of each type of component. Based on the basic curves of each component in the target liquid cooling system and the intermediate data corresponding to the basic curves, the historical operating curves of the components under this type are generated. By integrating the historical operating curves of the components under each type, the target sub-data model of the components is obtained.

7. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of the liquid cooling system protection method as described in any one of claims 1 to 3.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the method for protecting a liquid cooling system as described in any one of claims 1 to 3.

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