Liquid cooling fault processing method and system

Abstract

The present invention provides a liquid cooling fault processing method and system, which construct an emergency fault library, obtain a liquid cooling channel graphic and expand it into a liquid cooling polygon, divide the liquid cooling polygon into grid units, obtain the flow, temperature and pressure parameters in each liquid cooling grid unit and combine them into a liquid cooling channel parameter vector, update the liquid cooling channel parameter vector in real time and store and overwrite it during operation, extract a random liquid cooling channel parameter vector, and perform liquid cooling comparison with the emergency fault parameter range in the emergency fault library to perform emergency fault judgment. If an emergency fault exists, a liquid cooling reasoning model is imported to generate a solution and perform emergency fault processing. If no emergency fault exists, a liquid cooling virtual simulation model is constructed and the random liquid cooling channel parameter vector is input into the liquid cooling virtual simulation model for simulation to generate a liquid cooling simulation result. The flow regulation module is optimized according to the liquid cooling simulation result to improve the accuracy of liquid cooling system fault judgment and the stability of the liquid cooling system.

Description

Technical Field

[0001] The present invention relates to the technical field of liquid cooling fault processing, and in particular to a liquid cooling fault processing method and system. Background Art

[0002] With the rapid development of intelligent operation and maintenance of liquid cooling systems and the growing demand for heat dissipation stability in high-density data centers, liquid cooling fault handling technology faces severe technical challenges. Traditional liquid cooling systems rely primarily on manual experience or preset threshold rules for fault diagnosis and handling, but this has drawbacks in terms of system stability and fault handling accuracy.

[0003] The lag in manual intervention often threatens system stability. When coolant leaks, pump anomalies, or pipe blockages occur, operations and maintenance personnel need to locate the fault point through instrument data backtracking and empirical inference. This process has a response delay of minutes. During this period, the liquid cooling system may trigger cascading failures due to a sudden temperature rise. This passive disposal mode based on subjective judgment is difficult to meet the millisecond-level fault response requirements of modern data centers. Summary of the Invention

[0004] In view of the above-mentioned problems, in combination with the first aspect of the present invention, an embodiment of the present invention provides a liquid cooling fault handling method, the method comprising:

[0005] Build a liquid cooling emergency fault database and obtain the design drawings of the liquid cooling cold plate, and obtain the liquid cooling channel graphics in the liquid cooling cold plate from the design drawings;

[0006] Expanding the liquid-cooling channel graphic into a liquid-cooling polygon in equal proportion, wherein the angle between any two boundaries of the liquid-cooling polygon is a right angle, and performing a meshing operation based on the liquid-cooling polygon, wherein the meshing operation is represented by dividing the liquid-cooling polygon into a plurality of uninterrupted liquid-cooling grid units, and the length of the liquid-cooling channel in each liquid-cooling grid unit is equal;

[0007] Obtaining flow parameters, temperature parameters, and pressure parameters in each liquid-cooling grid unit, and combining the flow parameters, the temperature parameters, and the pressure parameters into a liquid-cooling channel parameter vector;

[0008] During operation, the liquid cooling channel parameter vector is updated in real time every 1 second, the liquid cooling channel parameter vector is stored and overwritten every 30 seconds, and 5 groups of random liquid cooling channel parameter vectors are extracted from the stored liquid cooling channel parameter vector every 30 seconds;

[0009] Performing a liquid cooling comparison operation on the five groups of random liquid cooling channel parameter vectors and the liquid cooling emergency fault parameter range in the liquid cooling emergency fault library, and performing a liquid cooling emergency fault judgment based on the liquid cooling comparison operation;

[0010] If there is an emergency liquid cooling channel fault, the random liquid cooling channel parameter vector is imported as input into the pre-trained liquid cooling inference model, a solution is generated based on the liquid cooling inference model, and the liquid cooling emergency fault is handled;

[0011] If there is no emergency failure of the liquid cooling channel, a liquid cooling virtual simulation model is constructed and a random liquid cooling channel parameter vector is input into the liquid cooling virtual simulation model for simulation, a liquid cooling simulation result is generated based on the liquid cooling simulation model, and the flow regulation module is optimized according to the liquid cooling simulation result.

[0012] As a further solution of the present invention, the liquid cooling channel pattern is proportionally expanded into a liquid cooling polygon, including:

[0013] Proportionally expanding the liquid cooling channel pattern by 1.2 times to obtain an expanded liquid cooling channel pattern, wherein the expanded liquid cooling channel pattern includes a straight line portion and an arc portion, and the arc portion is divided into an inner arc and an outer arc;

[0014] Obtain the tangent line of the outer arc vertex, and extend the straight line portion of the liquid cooling channel graph to intersect with the tangent line of the outer arc vertex to form a straight line of the outer arc polygon;

[0015] Obtain the tangent line of the inner arc vertex, and extend the straight line portion of the liquid cooling channel graph to intersect with the tangent line of the inner arc vertex to form a straight line of the inner arc polygon;

[0016] The liquid cooling polygon is composed of the straight line portion of the liquid cooling channel graphic, the straight line of the outer arc polygon, and the straight line of the inner arc polygon.

[0017] As a further solution of the present invention, constructing a liquid cooling virtual simulation model and inputting a random liquid cooling channel parameter vector into the liquid cooling virtual simulation model for simulation, and generating a liquid cooling simulation result based on the liquid cooling simulation model, includes:

[0018] Based on the pressure parameters and temperature parameters in each liquid-cooled grid unit, the momentum conservation equation and the energy conservation equation in each liquid-cooled grid unit are obtained, and the momentum conservation equation and the energy conservation equation are integrated. The integrated momentum conservation equation and the energy conservation equation are converted into algebraic equations and solved. Based on the solution results, the relationship between the flow parameter and the pressure parameter, and the flow parameter and the temperature parameter are respectively obtained. Based on the relationship between the flow parameter and the pressure parameter, and the flow parameter and the temperature parameter, the liquid-cooled virtual simulation model is constructed;

[0019] Obtain the pressure parameter and temperature parameter range under normal working conditions. If the pressure parameters and temperature parameters in the random liquid cooling channel parameter vector are not within the pressure parameter and temperature parameter range under normal working conditions, remove the set of random liquid cooling channel parameter vectors and import the random liquid cooling channel parameter vector within the pressure parameter and temperature parameter range under normal working conditions as input into the liquid cooling virtual simulation model to obtain the liquid cooling simulation results.

[0020] As a further solution of the present invention, the flow regulating module is optimized according to the liquid cooling simulation result, including:

[0021] The liquid cooling simulation results are represented as multiple sets of simulation flow parameters. The optimal simulation flow parameters are obtained based on the multiple sets of simulation flow parameters. The flow regulation module regulates the flow of the liquid cooling channel based on the optimal simulation flow parameters.

[0022] As a further solution of the present invention, the construction of a liquid-cooled emergency fault library includes:

[0023] Obtain the existing liquid cooling channel emergency faults and liquid cooling emergency fault parameter ranges, wherein the liquid cooling emergency fault parameter ranges include the flow parameter range, temperature parameter range and pressure parameter range corresponding to the liquid cooling channel emergency faults, and construct a liquid cooling emergency fault library based on the liquid cooling channel emergency faults and emergency liquid cooling emergency fault parameter ranges.

[0024] As a further solution of the present invention, the method of obtaining the flow parameter, temperature parameter, and pressure parameter in each liquid-cooled grid unit and combining the flow parameter, the temperature parameter, and the pressure parameter into a liquid-cooled channel parameter vector includes:

[0025] The flow rate of the liquid cooling channel in the liquid cooling cold plate in each liquid cooling grid unit is collected based on the collection module to obtain the flow rate parameters of each liquid cooling grid unit;

[0026] The acquisition module collects the temperature of the liquid cooling channel in the liquid cooling cold plate in each liquid cooling grid unit to obtain the temperature parameters of each liquid cooling grid unit, wherein the temperature parameters include the temperature of the liquid cooling grid unit inlet and the temperature of the liquid cooling grid unit outlet;

[0027] The pressure of the liquid cooling channel in the liquid cooling cold plate in each liquid cooling grid unit is collected based on the collection module to obtain the pressure parameters of each liquid cooling grid unit, wherein the pressure parameters include the pressure at the inlet and the pressure at the outlet of the liquid cooling grid unit;

[0028] The flow parameters, temperature parameters and pressure parameters in each liquid cooling grid unit are combined into a liquid cooling channel parameter vector;

[0029] The liquid cooling channel parameter vector is expressed as: [flow, temp, pres], where flow represents a flow parameter, temp represents a temperature parameter, and pres represents a pressure parameter.

[0030] As a further solution of the present invention, the liquid cooling comparison operation is performed on the five groups of random liquid cooling channel parameter vectors and the liquid cooling emergency fault parameter range in the liquid cooling emergency fault library, and the liquid cooling emergency fault judgment is performed based on the liquid cooling comparison operation, including:

[0031] If the flow parameters, temperature parameters and pressure parameters in the random liquid cooling channel parameter vector are not within the liquid cooling emergency fault parameter range of the flow parameters, temperature parameters and pressure parameters in the liquid cooling emergency fault library, it means that there is no liquid cooling emergency fault in the liquid cooling channel;

[0032] If any of the flow parameters, temperature parameters, and pressure parameters in the random liquid cooling channel parameter vector is within the liquid cooling emergency fault parameter range of the flow parameters, temperature parameters, and pressure parameters in the liquid cooling emergency fault library, it indicates that a liquid cooling emergency fault exists in the liquid cooling channel.

[0033] As a further solution of the present invention, if there is an emergency liquid cooling channel fault, a random liquid cooling channel parameter vector is imported as input into a pre-trained liquid cooling inference model, a solution is generated based on the liquid cooling inference model, and liquid cooling emergency fault processing is performed, including:

[0034] Based on the liquid cooling inference model, a short-term plan and a long-term plan are generated. The short-term plan represents the emergency measures immediately executed for the liquid cooling emergency failure, and the long-term plan represents the long-term optimization executed after the short-term plan is completed. The liquid cooling channel fault is handled collaboratively based on the short-term plan and the long-term plan.

[0035] As a further solution of the present invention, generating a short-term solution and a long-term solution based on the liquid-cooled inference model includes:

[0036] The liquid cooling inference model is constructed based on the MCTS algorithm. Based on the liquid cooling inference model, response actions corresponding to emergency failures of the liquid cooling channel are generated, and the response actions are quickly deduced to obtain response action combinations. Short-term and long-term solutions are generated based on the response action combinations.

[0037] In another aspect, an embodiment of the present invention further provides a liquid cooling fault handling system, comprising:

[0038] A division module, wherein the division module divides the liquid cooling channel into a plurality of uninterrupted liquid cooling grid units, and the length of the liquid cooling channel in each liquid cooling grid unit is equal;

[0039] An acquisition module, comprising a first acquisition module and a second acquisition module;

[0040] A first acquisition module, the first acquisition module is used to collect flow parameters, temperature parameters and pressure parameters of the liquid cooling channel in the liquid cooling grid unit;

[0041] a second acquisition module, the second acquisition module being configured to acquire an existing liquid cooling channel emergency fault and a liquid cooling emergency fault parameter range, acquire a design drawing of a liquid cooling cold plate, acquire a graphic of a liquid cooling channel in the liquid cooling cold plate in the design drawing, and acquire a pre-trained liquid cooling inference model;

[0042] A construction module, wherein the construction module is used to construct a liquid cooling emergency fault library and a liquid cooling virtual simulation model;

[0043] An update module, which is used to update the liquid cooling channel parameter vector in real time every 1 second, store and overwrite the liquid cooling channel parameter vector every 30 seconds, and extract 5 groups of random liquid cooling channel parameter vectors every 30 seconds;

[0044] a processing module, the processing module being used to compare the random liquid cooling channel parameter vector with the liquid cooling emergency fault parameter range in the liquid cooling emergency fault library, generate a solution and perform liquid cooling emergency fault processing, input the random liquid cooling channel parameter vector into the liquid cooling virtual simulation model for simulation, and generate a liquid cooling simulation result;

[0045] A flow regulating module, which can regulate the flow of the liquid-cooled cooling channel based on the optimal simulation flow parameters.

[0046] Based on the above aspects, the embodiment of the present application first obtains the design drawings of the liquid-cooled cold plate, obtains the graphics of the liquid-cooled cold channel in the liquid-cooled cold plate in the design drawings, expands the liquid-cooled cold channel graphics into liquid-cooled polygons in proportion, and divides the liquid-cooled polygons into multiple uninterrupted liquid-cooled grid units, and the lengths of the liquid-cooled cold channels in each liquid-cooled grid unit are equal. The topological interference of irregular surfaces can be eliminated through the grid division operation, and the flow time of the coolant in the equal-length cold channels is made the same. When there is an emergency fault in the liquid-cooled cold channel, the random liquid-cooled cold channel parameter vector is imported as input into the pre-trained liquid-cooled inference model, and a short-term solution and a long-term solution are generated based on the liquid-cooled inference model to deal with the liquid-cooled emergency fault. The liquid cooling inference model can be used to directly locate and handle liquid cooling emergency faults, meet the needs of modern data centers for millisecond-level fault response, and improve the accuracy of fault judgment. When there is no liquid cooling channel emergency fault, a liquid cooling virtual simulation model is constructed and the random liquid cooling channel parameter vector is input into the liquid cooling virtual simulation model for simulation. Liquid cooling simulation results are generated based on the liquid cooling simulation model. The flow regulation module is optimized according to the liquid cooling simulation results. The flow parameters are adjusted by temperature parameters and pressure parameters to obtain the optimal flow parameters. The flow regulation module can adjust the flow of the liquid cooling channel based on the optimal flow parameters to improve the stability of the liquid cooling system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic diagram of the execution flow of a liquid cooling fault handling method provided by an embodiment of the present invention.

[0048] Figure 2 It is a schematic diagram of expanding a liquid cooling channel in a liquid cooling fault handling method provided by an embodiment of the present invention.

[0049] Figure 3 It is a schematic diagram of the transformation of the liquid cooling channel in a liquid cooling fault processing method provided by an embodiment of the present invention.

[0050] Figure 4 This is a schematic diagram of meshing of liquid cooling channels in a liquid cooling fault handling method provided by an embodiment of the present invention.

[0051] Figure 5 Schematic diagram of a liquid cooling fault handling system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The present invention will be described in detail below with reference to the accompanying drawings. Figure 1 This is a schematic diagram of the execution flow of a liquid cooling fault processing method provided by an embodiment of the present invention. Figure 2 Schematic diagram of liquid cooling channel expansion in a liquid cooling fault handling method provided by an embodiment of the present invention. Figure 3Schematic diagram of liquid cooling channel conversion in a liquid cooling fault handling method provided by an embodiment of the present invention. Figure 4 This is a schematic diagram of liquid cooling channel division in a liquid cooling fault handling method provided by an embodiment of the present invention. The liquid cooling fault handling method is introduced in detail below.

[0053] Step S1: construct a liquid cooling emergency fault library and obtain a design drawing of a liquid cooling cold plate, and obtain a graphic of a liquid cooling channel in the liquid cooling cold plate from the design drawing.

[0054] Obtain the existing liquid cooling channel emergency faults and liquid cooling emergency fault parameter ranges, wherein the liquid cooling emergency fault parameter ranges include the flow parameter range, temperature parameter range and pressure parameter range corresponding to the liquid cooling channel emergency faults, and construct a liquid cooling emergency fault library based on the liquid cooling channel emergency faults and emergency liquid cooling emergency fault parameter ranges.

[0055] Specifically, the existing liquid cooling channel emergency failures and liquid cooling emergency failure parameter ranges are obtained by searching the liquid cooling system operation history records and relevant information. For example, liquid cooling channel emergency failures include coolant leakage, pipe blockage, and main circulation pump failure. The corresponding flow parameter range for coolant leakage is 0-3 L / min, the temperature parameter range is expressed as the inlet and outlet temperature difference of the liquid cooling grid unit inlet and outlet is greater than or equal to 15°C, and the pressure parameter range is 0-0.24 MPa; the corresponding flow parameter range for pipe blockage is 10-14 L / min, the temperature parameter range is expressed as the inlet and outlet temperature difference upstream and downstream of the blockage point is greater than or equal to 8°C, and the pressure parameter range is greater than or equal to 0.6 MPa; the corresponding flow parameter range for main circulation pump failure is 3-10 L / min, the temperature parameter range is expressed as the cold channel outlet temperature rises greater than or equal to 2°C per minute, and the pressure parameter range is expressed as pressure fluctuation greater than 0.05MPa.

[0056] Step S2: Proportionally expand the liquid-cooling channel graphic into a liquid-cooling polygon, wherein the angles between any two boundaries of the liquid-cooling polygon are right angles; and perform a meshing operation based on the liquid-cooling polygon. The meshing operation is represented by dividing the liquid-cooling polygon into a plurality of uninterrupted liquid-cooling grid units, and the lengths of the liquid-cooling channels in each liquid-cooling grid unit are equal.

[0057] In this embodiment, step S2 includes:

[0058] Step S21, proportionally expanding the liquid cooling channel pattern by 1.2 times to obtain an expanded liquid cooling channel pattern, wherein the expanded liquid cooling channel pattern includes a straight line portion and an arc portion, and the arc portion is divided into an inner arc and an outer arc;

[0059] Specifically, the graph of the liquid cooling channel is divided into the existence of a curved cooling channel and the non-existence of a curved cooling channel. If the liquid cooling channel is the non-existence of a curved cooling channel, it is directly enlarged proportionally and then the meshing operation is performed. If the curved cooling channel exists, the center point of the liquid cooling channel graph is first found, and the liquid cooling channel graph is proportionally enlarged by 1.2 times through the center point of the liquid cooling channel graph to obtain the enlarged liquid cooling channel graph. The enlarged liquid cooling channel graph is divided into a straight line part and an arc part, and the arc part is divided into an inner arc and an outer arc. For example, Figure 2 It represents a proportional enlargement of the liquid cooling channel. The dotted line part of the figure represents the obtained liquid cooling channel figure, and the solid line part of the figure represents the proportionally enlarged figure.

[0060] Step S22, obtaining the tangent line of the outer arc vertex, and extending the straight line portion of the liquid cooling channel graph to intersect with the tangent line of the outer arc vertex to form a straight line of the outer arc polygon;

[0061] In this embodiment, the vertex of the outer arc is found, and a tangent is drawn based on the vertex of the outer arc. The straight line portion and the tangent of the outer arc vertex are respectively extended and made to intersect. The tangent of the outer arc vertex, the straight line portion and the extension line of the straight line portion together constitute the boundary of the outer arc portion of the liquid-cooled polygon.

[0062] Step S23, obtaining the tangent line of the inner arc vertex, and extending the straight line portion of the liquid cooling channel graph to intersect with the tangent line of the inner arc vertex to form a straight line of the inner arc polygon;

[0063] In this embodiment, the vertex of the inner arc is found, and a tangent is drawn based on the vertex of the inner arc. The straight line portion and the tangent of the inner arc vertex are respectively extended and made to intersect. The tangent of the inner arc vertex, the straight line portion and the extension line of the straight line portion together constitute the boundary of the inner arc portion of the liquid-cooled polygon.

[0064] Step S24 , forming a liquid cooling polygon based on the straight line portion of the liquid cooling channel pattern, the straight line of the outer arc polygon, and the straight line of the inner arc polygon.

[0065] In this embodiment, a liquid-cooling polygon is formed according to the straight portion, the boundary of the outer arc portion of the liquid-cooling polygon, and the boundary of the inner arc portion of the liquid-cooling polygon, and the angles between every two adjacent sides of the obtained liquid-cooling polygon are right angles. The liquid-cooling channel with a curved surface is converted into a regular liquid-cooling polygon, which can eliminate the topological interference of the irregular curved surface, more accurately mesh the liquid-cooling channel, and reduce the amount of calculation. At the same time, the length of the liquid-cooling channel in each liquid-cooling grid unit is equal, so that the flow time of the coolant in the equal-length channels is the same, and the obtained flow parameters, pressure parameters, and temperature parameters are more illustrative. For example, Figure 3 It represents the transformation of the enlarged liquid cooling channel. The dotted line part of the figure represents the enlarged liquid cooling channel figure, and the solid line part of the figure represents the transformed figure. Figure 4It represents the mesh division of the liquid cooling channel after the transformation, the dotted line part represents the mesh division grid, and the solid line part represents the transformed figure.

[0066] Step S3: Obtain the flow parameter, temperature parameter, and pressure parameter in each liquid-cooling grid unit, and combine the flow parameter, temperature parameter, and pressure parameter into a liquid-cooling channel parameter vector.

[0067] In this embodiment, step S3 includes:

[0068] Step S31 : Based on the collection module, the flow of the liquid-cooled cold channel in the liquid-cooled cold plate in each liquid-cooled grid unit is collected to obtain the flow parameters of each liquid-cooled grid unit.

[0069] Step S32: Based on the acquisition module, the temperature of the liquid cooling channel in the liquid cooling cold plate in each liquid cooling grid unit is collected to obtain the temperature parameters of each liquid cooling grid unit, wherein the temperature parameters include the temperature at the inlet and outlet of the liquid cooling grid unit.

[0070] Step S33: Based on the acquisition module, the pressure of the liquid cooling channel in the liquid cooling cold plate in each liquid cooling grid unit is collected to obtain the pressure parameters of each liquid cooling grid unit, wherein the pressure parameters include the pressure at the inlet and outlet of the liquid cooling grid unit.

[0071] In step S34, the flow parameters, temperature parameters, and pressure parameters in each liquid-cooled grid unit are combined into a liquid-cooled channel parameter vector. The liquid-cooled channel parameter vector is expressed as: [flow, temp, pres], where flow represents the flow parameter, temp represents the temperature parameter, and pres represents the pressure parameter.

[0072] For example, the flow rate of a liquid cooling grid unit obtained by the acquisition module is 24 L / min.

[0073] According to the acquisition module, the inlet temperature of a liquid-cooled grid unit is 30°C, and the outlet temperature is 35°C. According to the acquisition module, the inlet pressure of a liquid-cooled grid unit is 0.3 MPa, and the outlet pressure is 0.31 MPa. These are combined into a liquid-cooled channel parameter vector: [24 L / min, 30°C, 35°C, 0.3 MPa, 0.31 MPa].

[0074] Step S4: During operation, the liquid cooling channel parameter vector is updated in real time every 1 second, the liquid cooling channel parameter vector is stored and overwritten every 30 seconds, and 5 groups of stored random liquid cooling channel parameter vectors are extracted every 30 seconds.

[0075] Specifically, during operation, due to the flow of coolant, the flow parameters, temperature parameters and pressure parameters in the liquid-cooling channel are changing in real time. Therefore, the liquid-cooling channel parameter vector is updated in real time every second, and 30 seconds of liquid-cooling channel parameter vectors, that is, 30 groups of liquid-cooling channel parameter vectors are stored. At the same time, the next 30 groups of liquid-cooling channel parameter vectors are generated and the previous 30 groups of liquid-cooling channel parameter vectors are overwritten. At the same time, 5 groups of random liquid-cooling channel parameter vectors are extracted from the stored 30 groups of liquid-cooling channel parameter vectors every 30 seconds.

[0076] Furthermore, under full load, the coolant temperature change rate is usually 0.1-0.3℃ / second, and a 30-second delay only causes a deviation of 3-9℃. The system redundancy design range generally allows a fluctuation of ±15℃, which is still within the system redundancy design range. Liquid cooling emergency failures such as main circulation pump failure and coolant leakage have a buffer period from the initial abnormality to the initiation of irreversible hardware damage. For example, when the main pump suddenly stops, the coolant flow returns to zero, causing the cold plate temperature to rise at a rate of 2-3℃ / minute. The overheating protection threshold of the liquid cooling system is usually set at 85-90℃, indicating that it takes at least 2 minutes and 30 seconds from the pump failure to the temperature breaking the safety critical point. The data 30 seconds ago can still capture the early characteristics of liquid cooling emergency failures. Whether it is data acquisition or liquid cooling emergency failure judgment, the use of historical data 30 seconds ago for analysis can still provide effective support.

[0077] Step S5: performing a liquid cooling comparison operation on the five groups of random liquid cooling channel parameter vectors and a liquid cooling emergency fault parameter range in a liquid cooling emergency fault library, and performing a liquid cooling emergency fault judgment based on the liquid cooling comparison operation.

[0078] In this embodiment, step S5 includes:

[0079] In step S51, if the flow parameters, temperature parameters and pressure parameters in the random liquid cooling channel parameter vector are not within the liquid cooling emergency fault parameter range of the flow parameters, temperature parameters and pressure parameters in the liquid cooling emergency fault library, it indicates that there is no liquid cooling emergency fault in the liquid cooling channel.

[0080] For example, the five groups of random liquid cooling channel parameter vectors extracted are [24L / min, 35.1℃, 40℃, 0.48MPa, 0.49MPa], [24.5L / min, 35.2℃, 40.2℃, 0.51 MPa, 0.52MPa], [24.3L / min, 35.4℃, 40.2℃, 0.51 MPa, 0.52MPa], [24.2L / min, 35.5℃, 40.6℃, 0.49 MPa, 0.5MPa], [24.1L / min, 35℃, 40.4℃, 0.47 MPa, 0.48MPa], the flow parameters are normal, the inlet and outlet temperature difference is normal, the pressure parameters are normal, and the random liquid cooling channel parameter vector [24.5L / min, 35.2℃, 40.2℃, 0.51 MPa, 0.52MPa], and the temperature difference between the inlet and outlet is also normal within two minutes, indicating that there is no emergency liquid cooling failure in the liquid cooling channel.

[0081] In step S52, if any of the flow parameters, temperature parameters, and pressure parameters in the random liquid cooling channel parameter vector is within the liquid cooling emergency fault parameter range of the flow parameters, temperature parameters, and pressure parameters in the liquid cooling emergency fault library, it indicates that a liquid cooling emergency fault exists in the liquid cooling channel.

[0082] For example, the extracted random liquid cooling channel parameter vector is [24L / min, 35.1℃, 40℃, 0.2MPa, 0.2MPa], and the pressure parameter in the random liquid cooling channel parameter vector is detected to be within the liquid cooling emergency fault parameter range of the pressure parameter in the liquid cooling emergency fault library, indicating that there is a liquid cooling emergency fault in the liquid cooling channel, and the liquid cooling emergency fault is a coolant leakage. If the extracted random liquid cooling channel parameter vector is [2L / min, 35.1℃, 40℃, 0.5MPa, 0.51MPa], and the flow parameter in the random liquid cooling channel parameter vector is detected to be within the liquid cooling emergency fault parameter range of the flow parameter in the liquid cooling emergency fault library, it indicates that there is a liquid cooling emergency fault in the liquid cooling channel, and the liquid cooling emergency fault is a failure of the main circulation pump.

[0083] Step S6: If there is an emergency fault in the liquid cooling channel, the random liquid cooling channel parameter vector is imported as input into a pre-trained liquid cooling inference model, a solution is generated based on the liquid cooling inference model, and the liquid cooling emergency fault processing is performed.

[0084] Based on the liquid cooling inference model, a short-term plan and a long-term plan are generated. The short-term plan represents the emergency measures immediately executed for the liquid cooling emergency failure, and the long-term plan represents the long-term optimization executed after the short-term plan is completed. The liquid cooling channel fault is handled collaboratively based on the short-term plan and the long-term plan.

[0085] Specifically, the liquid cooling inference model uses the MCTS algorithm to generate a short-term solution. The short-term solution can immediately respond to liquid cooling emergency failures, but it cannot achieve a radical cure. It then generates a long-term solution, which is an optimization of the short-term solution and can solve liquid cooling emergency failures from the source.

[0086] Furthermore, a short-term solution is used to immediately respond to emergency liquid cooling failures so that the liquid cooling system can continue to operate and maintain the continuity of the liquid cooling system's operation. A long-term solution is used to fundamentally resolve the liquid cooling failure and ensure that the liquid cooling failure is fundamentally resolved. At the same time, short-term and long-term solutions are used to collaboratively handle liquid cooling channel failures. The collaborative processing method can not only achieve immediate protection, but also achieve future optimization, thereby improving the stability and efficiency of the liquid cooling system.

[0087] Based on the liquid cooling inference model, response actions corresponding to emergency failures in the liquid cooling channel are generated. The response actions are quickly deduced based on the MCTS algorithm to obtain response action combinations. Short-term and long-term solutions are generated based on the response action combinations.

[0088] Monte Carlo Tree Search (MCTS) evaluates the potential value of actions by simulating decision paths. In liquid cooling system fault handling, the goal of MCTS is to quickly generate optimal short-term emergency actions and long-term maintenance strategies while balancing the reliability, energy consumption, and cost of the liquid cooling system.

[0089] Step S7: If there is no emergency failure of the liquid cooling channel, a liquid cooling virtual simulation model is constructed and a random liquid cooling channel parameter vector is input into the liquid cooling virtual simulation model for simulation, a liquid cooling simulation result is generated based on the liquid cooling simulation model, and the flow regulation module is optimized according to the liquid cooling simulation result.

[0090] In this embodiment, step S7 includes:

[0091] Step S71, based on the pressure parameters and temperature parameters in each liquid-cooled grid unit, obtain the momentum conservation equation and energy conservation equation in each liquid-cooled grid unit, and integrate the momentum conservation equation and energy conservation equation, convert the integrated momentum conservation equation and energy conservation equation into algebraic equations and solve them, and based on the solution results, obtain the relationship between the flow parameter and the pressure parameter, and the flow parameter and the temperature parameter, and construct the liquid cooling virtual simulation model based on the relationship between the flow parameter and the pressure parameter, and the flow parameter and the temperature parameter.

[0092] Specifically, the density of the coolant, the flow rate of the coolant, the dynamic viscosity of the coolant, the specific heat capacity of the coolant, and the thermal conductivity of the liquid cooling channel material are obtained by obtaining the module or consulting the data, and the momentum conservation equation in each liquid cooling grid unit is obtained as follows: ,in, Expressed as the density of the coolant, Expressed as the density of the coolant, Expressed as pressure, Expressed as the dynamic viscosity of the coolant, It is expressed as the convective acceleration of the coolant due to the velocity gradient, It is expressed as the momentum generated by the pressure difference driving the coolant movement, Expressed as the momentum generated by the coolant drag.

[0093] The energy conservation equation in each liquid cooling grid unit is obtained as ,in, Expressed as the specific heat capacity of the coolant, Expressed as the coolant temperature, Expressed as the thermal conductivity of the liquid cooling channel material, Expressed as the temperature gradient, It is represented as a divergence operator.

[0094] Furthermore, the momentum conservation equation and the energy conservation equation in each grid unit are integrated. Taking the momentum conservation equation as an example, the momentum conservation equation is volume integrated, and Gauss's theorem is applied to convert the volume integral into an area integral and discretize it into the sum of the fluxes of adjacent surfaces to obtain a discretized momentum equation. The discretized momentum equation is solved, and the pressure parameter is iteratively updated according to the solution result. The flow rate is obtained by solving the integral of the flow velocity cross section, and the inlet and outlet pressure drop is obtained by the pressure difference between the inlet and outlet after the iterative update, and the relationship between the flow rate and the inlet and outlet pressure drop is fitted; similarly, the temperature parameter is iteratively updated by the integration operation, and the inlet and outlet temperature difference is obtained according to the inlet and outlet temperature after the iterative update, and the relationship between the flow rate and the inlet and outlet temperature difference is fitted. The above process involves a large number of mathematical calculations, and the specific calculation process is obtained by a computer.

[0095] Step S72, obtain the pressure parameter and temperature parameter range under normal working conditions. If the pressure parameter and temperature parameter in the random liquid cooling channel parameter vector are not within the pressure parameter and temperature parameter range under normal working conditions, the group of random liquid cooling channel parameter vectors are eliminated, and the random liquid cooling channel parameter vector within the pressure parameter and temperature parameter range under normal working conditions is imported as input into the liquid cooling virtual simulation model to obtain the liquid cooling simulation results.

[0096] Specifically, the pressure parameter and temperature parameter range under normal working conditions are obtained to judge the pressure parameters and temperature parameters in the random liquid cooling channel parameter vector. If it is not in normal working condition, the abnormal random liquid cooling channel parameter vector is eliminated, and the remaining random liquid cooling channel parameter vectors in normal working condition are imported into the liquid cooling virtual simulation model for simulation to obtain the liquid cooling simulation results.

[0097] Furthermore, the liquid cooling simulation results obtained by simulation are expressed as the relationship between flow rate and inlet and outlet pressure drop and the relationship between flow rate and inlet and outlet temperature. Different liquid cooling channel parameter vectors obtain different relationships between flow rate and inlet and outlet pressure drop and the relationship between flow rate and inlet and outlet temperature. For example, the relationship between flow rate and inlet and outlet pressure drop is , the relationship between flow rate and inlet and outlet temperature difference is obtained as ,in, Expressed as the pressure drop between the inlet and outlet, Expressed as the temperature difference between the inlet and outlet, Expressed as flow rate, the inlet and outlet pressure drop and inlet and outlet temperature difference are obtained through the pressure parameters and temperature parameters in the liquid cooling channel parameter vector, and the obtained inlet and outlet pressure drop and inlet and outlet temperature difference are substituted into the liquid cooling virtual simulation model for analysis to obtain the simulated flow parameters. If the obtained pressure parameters and temperature parameters are in normal working state, then the simulated flow parameters obtained by the pressure parameters and temperature parameters through the liquid cooling virtual simulation model are also in normal working state.

[0098] In step S73 , the liquid cooling simulation results are represented as multiple sets of simulation flow parameters. Optimal simulation flow parameters are obtained based on the multiple sets of simulation flow parameters. The flow regulation module regulates the flow of the liquid cooling channel based on the optimal simulation flow parameters.

[0099] In this embodiment, the random liquid cooling channel parameter vector is represented as multiple groups of liquid cooling channel parameter vectors. By substituting them into the virtual simulation model, multiple groups of simulation flow parameters can be obtained. The average of the multiple groups of simulation flow parameters is calculated, and the average value is the optimal simulation flow parameter. The obtained optimal simulation flow parameter is substituted into the liquid cooling channel. By adjusting the flow of coolant in the liquid cooling channel, the temperature and pressure of the liquid cooling system are more stable during operation.

[0100] Figure 4 A schematic diagram of a liquid cooling fault handling system provided by some embodiments of the present application that can implement the concept of the present application is shown.

[0101] Specifically, a liquid cooling fault handling system includes:

[0102] A dividing module divides the liquid cooling channel into a plurality of uninterrupted liquid cooling grid units, and the length of the liquid cooling channel in each liquid cooling grid unit is equal.

[0103] The acquisition module includes a first acquisition module and a second acquisition module.

[0104] The first acquisition module is used to collect flow parameters, temperature parameters and pressure parameters of the liquid cooling channel in the liquid cooling grid unit.

[0105] a second acquisition module, the second acquisition module being configured to acquire an existing liquid cooling channel emergency fault and a liquid cooling emergency fault parameter range, acquire a design drawing of a liquid cooling cold plate, acquire a graphic of a liquid cooling channel in the liquid cooling cold plate in the design drawing, and acquire a pre-trained liquid cooling inference model;

[0106] A construction module is used to construct a liquid cooling emergency fault library and a liquid cooling virtual simulation model.

[0107] An update module is used to update the liquid cooling channel parameter vector in real time every 1 second, store and overwrite the liquid cooling channel parameter vector every 30 seconds, and extract 5 sets of stored random liquid cooling channel parameter vectors every 30 seconds.

[0108] A processing module is provided, wherein the processing module is used to compare the random liquid cooling channel parameter vector with the liquid cooling emergency fault parameter range in the liquid cooling emergency fault library, and can also generate a solution and perform liquid cooling emergency fault processing, input the random liquid cooling channel parameter vector into the liquid cooling virtual simulation model for simulation, and generate a liquid cooling simulation result.

[0109] A flow regulating module, which can regulate the flow of the liquid-cooled cooling channel based on the optimal simulation flow parameters.

[0110] The specific usage and function of this embodiment are described below:

[0111] First, a liquid cooling emergency fault library is constructed and the design drawings of the liquid cooling cold plate are obtained. The graphics of the liquid cooling channel in the liquid cooling cold plate in the design drawings are obtained, and the liquid cooling channel graphics are proportionally expanded into liquid cooling polygons. The angles between any two boundaries of the liquid cooling polygons are right angles. A grid division operation is performed based on the liquid cooling polygon. The grid division operation is represented by dividing the liquid cooling polygon into multiple uninterrupted liquid cooling grid units, and the lengths of the liquid cooling channels in each liquid cooling grid unit are equal. Through the grid division method, the obtained liquid cooling channel lengths are made consistent to ensure that the data obtained later can be used in the same way. The flow parameters, temperature parameters and pressure parameters in each liquid cooling grid unit are obtained, and the flow parameters, temperature parameters and pressure parameters are combined into a liquid cooling channel parameter vector. During operation, the liquid cooling channel parameter vector is updated in real time every 1 second, the liquid cooling channel parameter vector is stored and overwritten every 30 seconds, and 5 sets of stored random liquid cooling channel parameters are extracted every 30 seconds. Vector, using historical data 30 seconds ago for analysis can still provide effective support and will not affect the final result. Then, the 5 groups of random liquid cooling channel parameter vectors are compared with the liquid cooling emergency fault parameter range in the liquid cooling emergency fault library. Liquid cooling emergency fault judgment is performed based on the liquid cooling comparison operation. If a liquid cooling channel emergency fault exists, the random liquid cooling channel parameter vector is imported as input into the pre-trained liquid cooling inference model, and a solution is generated based on the liquid cooling inference model and liquid cooling emergency fault processing is performed. The liquid cooling emergency fault can be directly located through the liquid cooling inference model to improve accuracy. If there is no liquid cooling channel emergency fault, a liquid cooling virtual simulation model is constructed and the random liquid cooling channel parameter vector is input into the liquid cooling virtual simulation model for simulation. The optimal flow parameters are generated based on the liquid cooling simulation model, and the flow regulation module is optimized according to the optimal flow parameters. The flow regulation module can adjust the flow of the liquid cooling channel based on the optimal flow parameters to improve the stability of the liquid cooling system.

[0112] In addition, an embodiment of the present invention further provides an electronic device, including:

[0113] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method proposed in the first embodiment of the present invention.

[0114] The following is a detailed introduction to the various components of electronic equipment:

[0115] The term "processor" is the control center of an electronic device and can be a single processor or a collective term for multiple processing elements. For example, the processor can be one or more central processing units (CPUs), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the first embodiment of the present invention, such as one or more digital signal processors (DSPs) or one or more field programmable gate arrays (FPGAs).

[0116] The processor can execute various functions of the electronic device by running or executing software programs stored in the memory and calling data stored in the memory.

[0117] The memory is used to store the software program for executing the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can refer to the above method embodiment and will not be repeated here.

[0118] The memory may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. The memory may be integrated with the processor or exist independently and be coupled to the processor via an interface circuit of the electronic device, and this is not specifically limited in the embodiments of the present invention.

[0119] The above embodiments can be implemented in whole or in part via software, hardware (e.g., circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present invention are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wireless communication (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer, or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0120] It should be understood that the term "and / or" as used herein simply describes an association between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent the existence of A alone, the existence of both A and B, or the existence of B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the related objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0121] It should be understood that in the embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0122] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A liquid cooling fault handling method, characterized in that: The method comprises: Build a liquid cooling emergency fault database and obtain the design drawings of the liquid cooling cold plate, and obtain the liquid cooling channel graphics in the liquid cooling cold plate from the design drawings; Expanding the liquid-cooling channel graphic into a liquid-cooling polygon in equal proportion, wherein the angle between any two boundaries of the liquid-cooling polygon is a right angle, and performing a meshing operation based on the liquid-cooling polygon, wherein the meshing operation is represented by dividing the liquid-cooling polygon into a plurality of uninterrupted liquid-cooling grid units, and the length of the liquid-cooling channel in each liquid-cooling grid unit is equal; Obtaining flow parameters, temperature parameters, and pressure parameters in each liquid-cooling grid unit, and combining the flow parameters, the temperature parameters, and the pressure parameters into a liquid-cooling channel parameter vector; During operation, the liquid cooling channel parameter vector is updated in real time every 1 second, the liquid cooling channel parameter vector is stored and overwritten every 30 seconds, and 5 groups of random liquid cooling channel parameter vectors are extracted from the stored liquid cooling channel parameter vector every 30 seconds; Performing a liquid cooling comparison operation on the five groups of random liquid cooling channel parameter vectors and the liquid cooling emergency fault parameter range in the liquid cooling emergency fault library, and performing a liquid cooling emergency fault judgment based on the liquid cooling comparison operation; If there is an emergency liquid cooling channel fault, the random liquid cooling channel parameter vector is imported as input into the pre-trained liquid cooling inference model, a solution is generated based on the liquid cooling inference model, and the liquid cooling emergency fault is handled; Based on the pressure parameters and temperature parameters in each liquid-cooled grid unit, the momentum conservation equation and the energy conservation equation in each liquid-cooled grid unit are obtained, and the momentum conservation equation and the energy conservation equation are integrated. The integrated momentum conservation equation and the energy conservation equation are converted into algebraic equations and solved. Based on the solution results, the relationship between the flow parameter and the pressure parameter, and the flow parameter and the temperature parameter are respectively obtained. Based on the relationship between the flow parameter and the pressure parameter, and the flow parameter and the temperature parameter, the liquid-cooled virtual simulation model is constructed; Obtain the pressure parameter and temperature parameter range under normal working conditions. If the pressure parameter and temperature parameter in the random liquid cooling channel parameter vector are not within the pressure parameter and temperature parameter range under normal working conditions, remove the set of random liquid cooling channel parameter vectors. Import the random liquid cooling channel parameter vectors within the pressure parameter and temperature parameter range under normal working conditions as input into the liquid cooling virtual simulation model to obtain the liquid cooling simulation results. If there is no emergency failure of the liquid cooling channel, a liquid cooling virtual simulation model is constructed and a random liquid cooling channel parameter vector is input into the liquid cooling virtual simulation model for simulation, a liquid cooling simulation result is generated based on the liquid cooling simulation model, and the flow regulation module is optimized according to the liquid cooling simulation result.

2. A liquid cooling fault handling method according to claim 1, characterized in that: The step of proportionally expanding the liquid cooling channel pattern into a liquid cooling polygon includes: Proportionally expanding the liquid cooling channel pattern by 1.2 times to obtain an expanded liquid cooling channel pattern, wherein the expanded liquid cooling channel pattern includes a straight line portion and an arc portion, and the arc portion is divided into an inner arc and an outer arc; Obtain the tangent line of the outer arc vertex, and extend the straight line portion of the liquid cooling channel graph to intersect with the tangent line of the outer arc vertex to form a straight line of the outer arc polygon; Obtain the tangent line of the inner arc vertex, and extend the straight line portion of the liquid cooling channel graph to intersect with the tangent line of the inner arc vertex to form a straight line of the inner arc polygon; The liquid cooling polygon is composed of the straight line portion of the liquid cooling channel graphic, the straight line of the outer arc polygon, and the straight line of the inner arc polygon.

3. A liquid cooling fault handling method according to claim 1, characterized in that: Optimizing the flow regulation module according to the liquid cooling simulation result includes: The liquid cooling simulation results are represented as multiple sets of simulation flow parameters. The optimal simulation flow parameters are obtained based on the multiple sets of simulation flow parameters. The flow regulation module regulates the flow of the liquid cooling channel based on the optimal simulation flow parameters.

4. A liquid cooling fault handling method according to claim 1, characterized in that: The construction of the liquid-cooled emergency fault library includes: Obtain the existing liquid cooling channel emergency faults and liquid cooling emergency fault parameter ranges, wherein the liquid cooling emergency fault parameter ranges include the flow parameter range, temperature parameter range and pressure parameter range corresponding to the liquid cooling channel emergency faults, and construct a liquid cooling emergency fault library based on the liquid cooling channel emergency faults and emergency liquid cooling emergency fault parameter ranges.

5. A liquid cooling fault handling method according to claim 1, characterized in that: The obtaining of the flow parameters, temperature parameters, and pressure parameters in each liquid-cooling grid unit, and combining the flow parameters, the temperature parameters, and the pressure parameters into a liquid-cooling channel parameter vector, includes: The flow rate of the liquid cooling channel in the liquid cooling cold plate in each liquid cooling grid unit is collected based on the collection module to obtain the flow rate parameters of each liquid cooling grid unit; The acquisition module collects the temperature of the liquid cooling channel in the liquid cooling cold plate in each liquid cooling grid unit to obtain the temperature parameters of each liquid cooling grid unit, wherein the temperature parameters include the temperature of the liquid cooling grid unit inlet and the temperature of the liquid cooling grid unit outlet; The pressure of the liquid cooling channel in the liquid cooling cold plate in each liquid cooling grid unit is collected based on the collection module to obtain the pressure parameters of each liquid cooling grid unit, wherein the pressure parameters include the pressure at the inlet and the pressure at the outlet of the liquid cooling grid unit; The flow parameters, temperature parameters and pressure parameters in each liquid cooling grid unit are combined into a liquid cooling channel parameter vector; The liquid cooling channel parameter vector is expressed as: ,in, Expressed as flow parameter, Expressed as a temperature parameter, Expressed as a pressure parameter.

6. A liquid cooling fault handling method according to claim 1, characterized in that: The step of performing a liquid cooling comparison operation on the five groups of random liquid cooling channel parameter vectors and a liquid cooling emergency fault parameter range in a liquid cooling emergency fault library, and performing a liquid cooling emergency fault judgment based on the liquid cooling comparison operation, includes: If the flow parameters, temperature parameters and pressure parameters in the random liquid cooling channel parameter vector are not within the liquid cooling emergency fault parameter range of the flow parameters, temperature parameters and pressure parameters in the liquid cooling emergency fault library, it means that there is no liquid cooling emergency fault in the liquid cooling channel; If any of the flow parameters, temperature parameters, and pressure parameters in the random liquid cooling channel parameter vector is within the liquid cooling emergency fault parameter range of the flow parameters, temperature parameters, and pressure parameters in the liquid cooling emergency fault library, it indicates that a liquid cooling emergency fault exists in the liquid cooling channel.

7. A liquid cooling fault handling method according to claim 1, characterized in that: If there is an emergency liquid cooling channel fault, a random liquid cooling channel parameter vector is imported as input into a pre-trained liquid cooling inference model, a solution is generated based on the liquid cooling inference model, and liquid cooling emergency fault processing is performed, including: Based on the liquid cooling inference model, a short-term plan and a long-term plan are generated. The short-term plan represents the emergency measures immediately executed for the liquid cooling emergency failure, and the long-term plan represents the long-term optimization executed after the short-term plan is completed. The liquid cooling channel fault is handled collaboratively based on the short-term plan and the long-term plan.

8. A liquid cooling fault handling method according to claim 7, characterized in that: Generating a short-term solution and a long-term solution based on the liquid-cooled inference model includes: The liquid cooling inference model is constructed based on the MCTS algorithm. Based on the liquid cooling inference model, response actions corresponding to emergency failures of the liquid cooling channel are generated, and the response actions are quickly deduced to obtain response action combinations. Short-term and long-term solutions are generated based on the response action combinations.

9. A liquid cooling fault handling system, characterized in that: include: A division module, wherein the division module divides the liquid cooling channel into a plurality of uninterrupted liquid cooling grid units, and the length of the liquid cooling channel in each liquid cooling grid unit is equal; An acquisition module, comprising a first acquisition module and a second acquisition module; A first acquisition module, the first acquisition module is used to collect flow parameters, temperature parameters and pressure parameters of the liquid cooling channel in the liquid cooling grid unit; a second acquisition module, the second acquisition module being configured to acquire an existing liquid cooling channel emergency fault and a liquid cooling emergency fault parameter range, acquire a design drawing of a liquid cooling cold plate, acquire a graphic of a liquid cooling channel in the liquid cooling cold plate in the design drawing, and acquire a pre-trained liquid cooling inference model; A construction module, wherein the construction module is used to construct a liquid cooling emergency fault library and a liquid cooling virtual simulation model; An update module, which is used to update the liquid cooling channel parameter vector in real time every 1 second, store and overwrite the liquid cooling channel parameter vector every 30 seconds, and extract 5 groups of random liquid cooling channel parameter vectors every 30 seconds; a processing module, the processing module being used to compare the random liquid cooling channel parameter vector with the liquid cooling emergency fault parameter range in the liquid cooling emergency fault library, generate a solution and perform liquid cooling emergency fault processing, input the random liquid cooling channel parameter vector into the liquid cooling virtual simulation model for simulation, and generate a liquid cooling simulation result; Based on the pressure parameters and temperature parameters in each liquid-cooled grid unit, the momentum conservation equation and the energy conservation equation in each liquid-cooled grid unit are obtained, and the momentum conservation equation and the energy conservation equation are integrated. The integrated momentum conservation equation and the energy conservation equation are converted into algebraic equations and solved. Based on the solution results, the relationship between the flow parameter and the pressure parameter, and the flow parameter and the temperature parameter are respectively obtained. Based on the relationship between the flow parameter and the pressure parameter, and the flow parameter and the temperature parameter, the liquid-cooled virtual simulation model is constructed; Obtain the pressure parameter and temperature parameter range under normal working conditions. If the pressure parameter and temperature parameter in the random liquid cooling channel parameter vector are not within the pressure parameter and temperature parameter range under normal working conditions, remove the set of random liquid cooling channel parameter vectors. Import the random liquid cooling channel parameter vectors within the pressure parameter and temperature parameter range under normal working conditions as input into the liquid cooling virtual simulation model to obtain the liquid cooling simulation results. A flow regulating module, which can regulate the flow of the liquid-cooled cooling channel based on the optimal simulation flow parameters.

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