Liquid cooling heat dissipation method for tower-type computer host

Abstract

The invention relates to the technical field of computer heat dissipation, and discloses a liquid cooling heat dissipation method for a tower-type computer host, which comprises the following steps: step 1, a high-strength composite material pipeline is adopted to construct a liquid cooling circulation path, the pipeline comprises an inner layer, a middle layer and an outer layer, the inner layer is made of a polytetrafluoroethylene material, and a fiber bragg grating sensor is embedded in the middle layer; a Kevlar fiber net wraps the outer layer, a double-layer sealing structure is arranged at the cold head and the connector of the pipeline, the inner layer is a high-temperature-resistant silica gel sealing ring, and the outer layer is sealed in a magnetic attraction butt joint mode. And 2, a flow velocity sensor, a pressure sensor and a temperature sensor are installed between a cold row and a cold head of the composite material pipeline. By embedding the fiber bragg grating sensor in the liquid cooling pipeline, the strain change of the pipeline is monitored in real time, the precise monitoring of the mechanical stress concentration area and the long-term fatigue state of the pipeline is realized, the effect of predicting the potential fatigue failure risk of the pipeline in advance is obtained, and the long-term reliability of the liquid cooling system is effectively improved.

Description

Technical Field

[0001] The invention relates to the technical field of computer heat dissipation, in particular to a liquid cooling heat dissipation method for a tower computer host. Background Art

[0002] Tower computer hosts have increasingly stringent requirements for heat dissipation performance in high-performance computing and gaming scenarios. Traditional air cooling methods have limited heat dissipation capacity and cannot meet the stability and safety requirements of high-power components. Therefore, liquid cooling systems have gradually become one of the mainstream heat dissipation solutions.

[0003] The liquid cooling system dissipates heat from the cooling radiator in the computer hardware through liquid circulation, which has the advantages of high heat dissipation efficiency and low noise. However, the existing liquid cooling technology has the following problems:

[0004] The pipes in the liquid cooling system are subject to mechanical stress and thermal cycle fatigue caused by the circulation of coolant due to long-term operation, and are very likely to fail in stress concentration areas and material aging points, leading to leakage accidents. Currently, there is a lack of real-time and effective monitoring methods to determine whether there is a potential risk of fatigue failure in the pipes.

[0005] In existing liquid cooling systems, if the fluid is unevenly distributed and the temperature of a part of the pipeline rises abnormally, it is impossible to detect the problem in time through traditional monitoring methods. The flow rate, pressure and temperature changes in the liquid cooling system are complex, and the existing technology lacks an overall analysis method that can reflect the fluid state and heat distribution state inside the pipeline in real time, and cannot achieve accurate prediction of leakage risks.

[0006] Existing liquid cooling systems are usually unable to respond quickly and isolate effectively when leaks occur. Coolant leaks can directly damage the motherboard and graphics card hardware, and traditional designs lack a reliable emergency response mechanism, increasing the probability of hardware damage.

[0007] The cold head and joints of the liquid cooling system have become high-risk areas for leakage due to long-term exposure to high pressure and high temperature. The sealing design of existing technologies mostly relies on single-layer sealing materials. After long-term use, the sealing performance deteriorates due to aging, material failure and improper installation, and cannot effectively guarantee the long-term operation safety of the liquid cooling system.

[0008] Therefore, those skilled in the art provide a liquid cooling method for a tower computer host to solve the above-mentioned problems. Summary of the invention

[0009] In view of the deficiencies of the prior art, the present invention provides a liquid cooling method for a tower computer host to solve the problems raised in the above background technology.

[0010] To achieve the above objectives, the present invention is implemented through the following technical solutions: A liquid cooling method for a tower computer host, comprising:

[0011] Step 1: Use high-strength composite material pipelines to construct a liquid cooling circulation path. The pipeline includes an inner layer, a middle layer and an outer layer. The inner layer is made of polytetrafluoroethylene material, the middle layer is embedded with a fiber Bragg grating sensor, and the outer layer is covered with a Kevlar fiber mesh. A double-layer sealing structure is set at the cold head and joint of the pipeline. The inner layer is a high-temperature resistant silicone sealing ring, and the outer layer adopts a magnetic docking seal;

[0012] Step 2: Install a flow rate sensor, a pressure sensor, and a temperature sensor between the cold row and the cold head of the composite material pipeline, and monitor the key physical parameters of the liquid cooling system in real time in combination with the strain data obtained by the fiber Bragg grating sensor. Based on the monitored flow rate and pressure data, analyze whether the fluid state of the coolant in the pipeline is normal, and combine the strain changes monitored by the fiber Bragg grating sensor to determine whether there are mechanical stress concentration areas and material fatigue risks in the pipeline;

[0013] Step 3: Analyze the heat conduction characteristics and temperature distribution of the coolant in the pipeline based on the acquired flow rate, pressure and temperature data and the temperature change collected by the temperature sensor. Identify the abnormal areas in the pipeline based on the flow rate and pressure monitoring results to form a real-time temperature, flow rate and pressure distribution model of the liquid cooling passage.

[0014] Step 4: Input the liquid cooling distribution model constructed based on flow rate, pressure, temperature and strain data into the digital twin model of the liquid cooling system. Update the fluid distribution and heat distribution information in the model through real-time monitoring. Predict the high stress concentration areas and temperature abnormal areas inside the pipeline based on the digital twin model. Combined with real-time data analysis, determine whether there is a risk of coolant leakage and locate the leakage area.

[0015] Step 5. When it is determined that there is a potential leakage in the liquid cooling system, the system control unit shuts down the water pump through an active response mechanism to stop the circulation of the coolant, and activates the air-cooled heat dissipation module of the radiator as a temporary heat dissipation solution, and records the flow rate, pressure, temperature and strain data of the fiber Bragg grating sensor to the system log, and provides the user with a diagnostic report of the leakage location and related data through the operating system interface.

[0016] Preferably, in step 1, the inner layer of the pipeline is made of polytetrafluoroethylene material, wherein the thickness t satisfies the following relationship:

[0017]

[0018] Where, t is the pipe wall thickness, P is the working pressure of the coolant, r is the inner radius of the pipe, σ max is the maximum allowable stress of the pipeline material.

[0019] Preferably, the fiber Bragg grating sensor in step 1 monitors the strain change of the pipeline in real time, and the wavelength drift Δλ and the strain ∈ satisfy the following relationship:

[0020] Δλ=K·∈,

[0021] Among them, Δλ is the grating wavelength drift, K is the fiber sensitivity constant, and ∈ is the strain of the pipeline.

[0022] Preferably, in step 2, the flow rate v of the coolant is measured by a flow rate sensor, wherein the calculation formula is:

[0023]

[0024] Where v is the flow rate of the coolant, L is the distance between the ultrasonic sensors, and Δt is the time difference of ultrasonic propagation.

[0025] Preferably, the pressure data P and the flow rate data v monitored by the pressure sensor are combined to calculate the fluid state of the coolant using the Bernoulli equation:

[0026]

[0027] Where P is the static pressure of the fluid, ρ is the coolant density, v is the flow velocity, g is the acceleration due to gravity, and h is the height of the fluid.

[0028] Preferably, the temperature data T collected by the temperature sensor in step 3 satisfies the following heat conduction equation:

[0029]

[0030] Where T is the temperature, t is the tube wall thickness, α is the thermal diffusion coefficient,

[0031]

[0032] Where k is the thermal conductivity of the coolant, ρ is the density of the coolant, and c is the specific heat capacity of the coolant.

[0033] Preferably, the flow velocity and temperature distribution model is combined, and the digital twin technology is used to dynamically update the fluid distribution and heat distribution information in the pipeline to predict high stress concentration areas and temperature abnormality areas.

[0034] Preferably, the digital twin model uses a support vector machine algorithm to classify and predict flow rate, pressure, temperature and strain data, and the decision function is:

[0035]

[0036] Among them, x is the input feature vector, yi is the sample classification label, K(x i , x) is the kernel function, b is the bias, α i is the support vector weight.

[0037] Preferably, if a potential leakage risk is predicted, the water pump is actively turned off to stop the coolant circulation, and the exhaust air cooling mode is started as a temporary heat dissipation solution.

[0038] Preferably, the system records flow rate, pressure, temperature and strain data, generates a diagnostic report, and provides diagnostic information of the leak location and related data to the user through the operating system interface.

[0039] The present invention provides a liquid cooling method for a tower computer host, which has the following beneficial effects:

[0040] 1. The present invention embeds a fiber Bragg grating sensor in the liquid cooling pipeline to monitor the strain changes of the pipeline in real time, thereby realizing accurate monitoring of the mechanical stress concentration area and long-term fatigue state of the pipeline, achieving the effect of predicting the potential fatigue failure risk of the pipeline in advance, and effectively improving the long-term reliability of the liquid cooling system.

[0041] 2. The present invention constructs a digital twin model of the liquid cooling system, combines the flow rate, pressure, temperature and strain data collected in real time, dynamically updates the fluid distribution and heat distribution information, and realizes accurate prediction of high stress concentration areas and abnormal temperature areas inside the pipeline, so as to accurately judge the potential leakage hazards of the liquid cooling system and quickly locate the leakage area, thereby greatly improving the system's fault prevention capabilities.

[0042] 3. The present invention designs an active response mechanism. When a potential leakage is detected in the liquid cooling system, the system control unit can quickly shut down the water pump and stop the coolant circulation, and activate the air-cooled heat dissipation module of the radiator as a temporary heat dissipation solution, thereby quickly isolating the leakage point and maintaining safe heat dissipation of the hardware, effectively reducing the risk of hardware damage and significantly improving the system's emergency handling capabilities.

[0043] 4. The present invention adopts a double-layer sealing structure at the cold head and the joint. The inner layer is a high-temperature resistant silicone sealing ring, and the outer layer adopts a magnetic docking seal to achieve a long-term stable sealing effect under high pressure and high temperature conditions, which significantly reduces the risk of leakage at the pipe joints and improves the sealing reliability of the liquid cooling system, providing important guarantee for the safe operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0045] In order to make the technical personnel in the technical field understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in combination with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a partial embodiment of the present invention, not a complete embodiment. Based on the embodiment of the present invention, other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present invention.

[0046] The present invention is described in detail below in conjunction with the accompanying drawings:

[0047] Example:

[0048] Please refer to the attached Figure 1 The embodiment of the present invention provides a liquid cooling method for a tower computer host, comprising:

[0049] Step 1: Use high-strength composite material pipelines to construct a liquid cooling circulation path. The pipeline includes an inner layer, a middle layer and an outer layer. The inner layer is made of polytetrafluoroethylene material, the middle layer is embedded with a fiber Bragg grating sensor, and the outer layer is covered with a Kevlar fiber mesh. A double-layer sealing structure is set at the cold head and joint of the pipeline. The inner layer is a high-temperature resistant silicone sealing ring, and the outer layer adopts a magnetic docking seal;

[0050] Step 2: Install a flow rate sensor, a pressure sensor, and a temperature sensor between the cold row and the cold head of the composite material pipeline, and monitor the key physical parameters of the liquid cooling system in real time in combination with the strain data obtained by the fiber Bragg grating sensor. Based on the monitored flow rate and pressure data, analyze whether the fluid state of the coolant in the pipeline is normal, and combine the strain changes monitored by the fiber Bragg grating sensor to determine whether there are mechanical stress concentration areas and material fatigue risks in the pipeline;

[0051] Step 3: Analyze the heat conduction characteristics and temperature distribution of the coolant in the pipeline based on the acquired flow rate, pressure and temperature data and the temperature change collected by the temperature sensor. Identify the abnormal areas in the pipeline based on the flow rate and pressure monitoring results to form a real-time temperature, flow rate and pressure distribution model of the liquid cooling passage.

[0052] Step 4: Input the liquid cooling distribution model constructed based on flow rate, pressure, temperature and strain data into the digital twin model of the liquid cooling system. Update the fluid distribution and heat distribution information in the model through real-time monitoring. Predict the high stress concentration areas and temperature abnormal areas inside the pipeline based on the digital twin model. Combined with real-time data analysis, determine whether there is a risk of coolant leakage and locate the leakage area.

[0053] Step 5. When it is determined that there is a potential leakage in the liquid cooling system, the system control unit shuts down the water pump through an active response mechanism to stop the circulation of the coolant, and activates the air-cooled heat dissipation module of the radiator as a temporary heat dissipation solution, and records the flow rate, pressure, temperature and strain data of the fiber Bragg grating sensor to the system log, and provides the user with a diagnostic report of the leakage location and related data through the operating system interface.

[0054] Benefits of step 1: The inner layer is made of polytetrafluoroethylene material, which has high temperature resistance, corrosion resistance and low friction characteristics, significantly improving the long-term reliability of the pipeline. The fiber Bragg grating sensor embedded in the middle layer can monitor the mechanical strain of the pipeline in real time and identify potential fatigue failure areas in advance. The outer layer is coated with Kevlar fiber mesh to provide the pipeline with high-strength pressure resistance and mechanical damage resistance. At the same time, the double-layer sealing structure effectively prevents the risk of leakage under high pressure and high temperature conditions.

[0055] Benefits of step 2: The flow rate sensor and pressure sensor obtain the flow rate and pressure data of the coolant in real time, accurately analyze the fluid state of the coolant based on the Bernoulli equation, and quickly identify abnormalities. Combined with the strain data monitored by the fiber Bragg grating sensor, it can accurately determine whether there are mechanical stress concentration areas and material fatigue risks in the pipeline. By comprehensively monitoring the key physical parameters in the liquid cooling system, the stability and reliability of the liquid cooling system during operation are ensured.

[0056] Benefits of step 3: Use temperature sensors to collect temperature data, and combine the heat conduction equation to analyze the heat conduction characteristics and temperature distribution of the coolant in the pipeline to detect temperature anomalies in a timely manner. By combining the flow rate and pressure monitoring results, the abnormal areas in the pipeline can be quickly identified. A real-time temperature, flow rate and pressure distribution model of the liquid cooling path is formed to provide reliable basic data for subsequent prediction and prevention and control.

[0057] Benefits of step 4: By inputting the liquid cooling distribution model into the digital twin model, the fluid distribution and heat distribution information are dynamically updated to accurately predict the operating status of the liquid cooling system. Based on real-time analysis of high stress concentration areas and temperature abnormality areas, it is possible to quickly determine whether there is a risk of coolant leakage and accurately locate the leakage area. The digital twin model can identify fault risk areas in advance, provide a reliable basis for pipeline maintenance and system optimization, and enhance the prevention capability of the liquid cooling system.

[0058] Benefits of step 5: When a leak is discovered, the active response mechanism quickly shuts down the water pump to stop the coolant circulation and activates the exhaust air cooling module as a temporary cooling solution to avoid further damage to the hardware. The flow rate, pressure, temperature and strain data are recorded in real time, and a detailed system log is generated. A diagnostic report of the leak location and related data is provided to the user through the operating system interface, which facilitates the user to quickly repair and analyze the problem. The active response mechanism and detailed data records significantly reduce the damage to computer hardware caused by leaks, providing users with higher safety and maintenance convenience.

[0059] In step 1, the inner layer of the pipeline is made of polytetrafluoroethylene material, wherein the thickness t satisfies the following relationship:

[0060]

[0061] Where, t is the pipe wall thickness, P is the working pressure of the coolant, r is the inner radius of the pipe, σ max is the maximum allowable stress of the pipeline material.

[0062] The fiber Bragg grating sensor in step 1 monitors the strain change of the pipeline in real time, and the wavelength drift Δλ and the strain ∈ satisfy the following relationship:

[0063] Δλ=K·∈,

[0064] Among them, Δλ is the grating wavelength drift, K is the fiber sensitivity constant, and ∈ is the strain of the pipeline.

[0065] Optimize the pipe wall thickness according to the working pressure of the coolant and the pipe diameter to avoid mechanical failure of the pipe under high pressure conditions. Through thickness design, the stress of the material is always controlled within the maximum allowable stress range to avoid rupture and leakage caused by high pressure. Reasonable distribution of pipe thickness reduces the long-term fatigue accumulation effect and improves the reliability and stability of the liquid cooling system.

[0066] By collecting the optical fiber wavelength drift in real time, the strain state of the pipeline can be reflected and whether the pipeline is subjected to excessive mechanical stress can be determined. By monitoring the wavelength drift trend, high stress concentration areas and fatigue aging parts in the pipeline can be identified in advance to prevent fatigue failure. The embedded design of the optical fiber sensor is non-interfering and fast in response. It can provide the system with efficient and accurate fatigue warning, greatly improving the safety of the liquid cooling system.

[0067] In summary, through the thickness design of polytetrafluoroethylene materials and real-time monitoring of fiber Bragg grating sensors, step 1 significantly improves the reliability and operational safety of the liquid cooling pipeline. Specifically:

[0068] The optimized design of pipe wall thickness ensures that the pipeline can operate stably for a long time under high pressure and high strength conditions, avoiding mechanical damage and leakage problems caused by high pressure.

[0069] Fiber Bragg grating sensors monitor the strain state of the pipeline in real time, achieve accurate identification and early warning of mechanical fatigue failure, and ensure that there are no potential risks during the operation of the system.

[0070] Combining the advantages, the liquid cooling system has pressure resistance, fatigue monitoring and safety prevention capabilities during operation, providing strong guarantees for the stability and reliability of liquid cooling technology.

[0071] Through the above design, the present invention achieves innovative breakthroughs in material design and real-time monitoring, ensuring the long-term safe operation and extended service life of the liquid cooling system of the tower computer host.

[0072] In step 2, the flow rate v of the coolant is measured by a flow rate sensor, where the calculation formula is:

[0073]

[0074] Where v is the flow rate of the coolant, L is the distance between the ultrasonic sensors, and Δt is the time difference of ultrasonic propagation.

[0075] Combining the pressure data P and flow rate data v monitored by the pressure sensor, the Bernoulli equation is used to calculate the fluid state of the coolant:

[0076]

[0077] Where P is the static pressure of the fluid, ρ is the coolant density, v is the flow velocity, g is the acceleration due to gravity, and h is the height of the fluid.

[0078] The ultrasonic time difference method can measure the flow rate of the coolant in the pipeline in real time with high precision to avoid the decrease in heat dissipation efficiency due to abnormal flow rate. Changes in coolant flow rate are early signs of leakage and pipeline blockage. Real-time measurement can quickly identify reduced and abnormally increased flow rates, providing timely feedback for system protection. Ultrasonic sensors are highly sensitive to small changes in flow rate and can capture subtle changes in coolant under complex flow conditions, improving the accuracy of liquid cooling system operation monitoring.

[0079] The Bernoulli equation takes into account the static pressure, flow velocity and height of the fluid, and can comprehensively analyze the flow state of the coolant in the pipeline to ensure the stable operation of the cooling system.

[0080] If leakage occurs in the pipeline, the flow rate increases and the static pressure decreases. The abnormal characteristics can be accurately identified through the Bernoulli equation, which helps to quickly locate the abnormal area.

[0081] Through dynamic monitoring of the fluid state, areas with excessive coolant flow resistance and insufficient flow can be identified, the liquid cooling pipeline design can be optimized, and the overall heat dissipation efficiency of the system can be improved.

[0082] In summary, the flow rate and pressure state of the coolant are monitored in real time through the flow rate sensor and the pressure sensor, and the fluid state is analyzed in combination with the Bernoulli equation. Step 2 provides significant advantages for the liquid cooling system:

[0083] The flow rate sensor achieves high-sensitivity real-time flow rate measurement based on the ultrasonic time difference method, and the pressure sensor further supplements the changes in fluid pressure in the system, providing a reliable basis for accurate monitoring of fluid status.

[0084] Comprehensive analysis of the dynamic changes of static pressure and flow velocity through the Bernoulli equation can quickly identify potential leaks, blockages and fluid abnormalities in the pipeline to ensure system stability.

[0085] Dynamically monitor and analyze key parameters such as fluid static pressure, flow rate, and height to improve the design optimization capabilities and operational efficiency of the liquid cooling system.

[0086] Through the real-time monitoring and fluid analysis of step 2, the present invention can effectively prevent flow anomalies and malfunctions in the liquid cooling system, and provide strong technical support for the safety, reliability and efficient heat dissipation performance of the liquid cooling system.

[0087] The temperature data T collected by the temperature sensor in step 3 satisfies the following heat conduction equation:

[0088]

[0089] Where T is the temperature, t is the tube wall thickness, α is the thermal diffusion coefficient,

[0090]

[0091] Where k is the thermal conductivity of the coolant, ρ is the density of the coolant, and c is the specific heat capacity of the coolant.

[0092] Combining the flow velocity and temperature distribution models, digital twin technology is used to dynamically update the fluid distribution and thermal distribution information in the pipeline, and to predict areas of high stress concentration and abnormal temperature.

[0093] The support vector machine algorithm is used in the digital twin model to classify and predict the flow rate, pressure, temperature and strain data. The decision function is:

[0094]

[0095] Among them, x is the input feature vector, y i is the sample classification label, K(x i , x) is the kernel function, b is the bias, α i is the support vector weight.

[0096] If a potential leakage is predicted, the water pump will be turned off to stop the coolant circulation and the exhaust air cooling mode will be started as a temporary heat dissipation solution.

[0097] The system records flow rate, pressure, temperature and strain data, generates a diagnostic report, and provides the user with diagnostic information on the leak location and related data through the operating system interface.

[0098] The temperature change trend is dynamically analyzed through the heat conduction equation to fully reflect the heat diffusion characteristics and thermal efficiency of the coolant in the pipeline.

[0099] The temperature gradient collected by the temperature sensor is combined with the heat conduction equation to quickly discover areas with abnormally high temperatures in the pipeline, which is a precursor to insufficient heat dissipation or material aging.

[0100] Based on dynamic monitoring of temperature distribution, it is possible to identify areas with poor coolant heat conduction performance and optimize pipeline design to improve overall heat dissipation efficiency.

[0101] Digital twin technology dynamically updates the fluid and heat distribution model based on real-time collected data, and can accurately reflect the working conditions of the liquid cooling system under different operating conditions.

[0102] Through comprehensive analysis of flow velocity, pressure and temperature distribution, areas of high stress concentration and abnormal temperature can be accurately identified, and potential leakage risks can be quickly located.

[0103] If a leak is predicted, the system will automatically shut down the water pump, stop the coolant circulation, and start the exhaust air cooling mode as a temporary cooling solution. At the same time, it will record the flow rate, pressure, temperature and strain data, generate a diagnostic report, and provide the user with diagnostic information on the leak location and related data through the operating system interface.

[0104] Actively shutting down the water pump and stopping the coolant circulation can quickly isolate the leak risk area and prevent further spread of the coolant.

[0105] Start the radiator air cooling mode as a temporary cooling solution to ensure safe cooling of computer hardware and avoid hardware damage due to cooling interruption.

[0106] By recording and analyzing data in real time and generating detailed fault reports, users can quickly locate problem areas and take repair measures, reducing maintenance difficulty and time costs.

[0107] In summary, through the data collection of temperature sensors and the analysis of heat conduction equations, combined with digital twin technology and support vector machine algorithm, step 3 provides significant advantages for the liquid cooling system:

[0108] Based on the heat conduction equation and real-time data, it can accurately analyze the thermal diffusion characteristics and temperature distribution of the coolant, quickly identify abnormal temperature areas, and improve heat dissipation efficiency.

[0109] Digital twin technology is used to dynamically update fluid and heat distribution models, and the support vector machine algorithm is used to accurately predict leakage hazards and locate hazard areas, significantly improving fault prevention capabilities.

[0110] By proactively shutting down the water pump, starting the air cooling mode, and generating detailed fault diagnosis reports, the problem area can be quickly isolated, hardware safety can be ensured, and the maintenance process can be optimized.

[0111] Through the complete design of step 3, the present invention realizes comprehensive functional optimization in real-time monitoring, fault prediction and hidden danger response of the liquid cooling system, and provides an efficient, safe and intelligent solution for the liquid cooling system of the tower computer host.

[0112] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A liquid cooling method for a tower computer host, characterized in that: include: Step 1: Use high-strength composite material pipelines to construct a liquid cooling circulation path. The pipeline includes an inner layer, a middle layer and an outer layer. The inner layer is made of polytetrafluoroethylene material, the middle layer is embedded with a fiber Bragg grating sensor, and the outer layer is covered with a Kevlar fiber mesh. A double-layer sealing structure is set at the cold head and joint of the pipeline. The inner layer is a high-temperature resistant silicone sealing ring, and the outer layer adopts a magnetic docking seal; Step 2: Install a flow rate sensor, a pressure sensor, and a temperature sensor between the cold row and the cold head of the composite material pipeline, and monitor the key physical parameters of the liquid cooling system in real time in combination with the strain data obtained by the fiber Bragg grating sensor. Based on the monitored flow rate and pressure data, analyze whether the fluid state of the coolant in the pipeline is normal, and combine the strain changes monitored by the fiber Bragg grating sensor to determine whether there are mechanical stress concentration areas and material fatigue risks in the pipeline; Step 3: Analyze the heat conduction characteristics and temperature distribution of the coolant in the pipeline based on the acquired flow rate, pressure and temperature data and the temperature change collected by the temperature sensor. Identify the abnormal areas in the pipeline based on the flow rate and pressure monitoring results to form a real-time temperature, flow rate and pressure distribution model of the liquid cooling passage. Step 4: Input the liquid cooling distribution model constructed based on flow rate, pressure, temperature and strain data into the digital twin model of the liquid cooling system. Update the fluid distribution and heat distribution information in the model through real-time monitoring. Predict the high stress concentration areas and temperature abnormal areas inside the pipeline based on the digital twin model. Combined with real-time data analysis, determine whether there is a risk of coolant leakage and locate the leakage area. Step 5. When it is determined that there is a potential leakage risk in the liquid cooling system, the system control unit shuts down the water pump through an active response mechanism to stop the circulation of the coolant, and activates the air-cooled heat dissipation module of the radiator as a temporary heat dissipation solution, and records the flow rate, pressure, temperature and strain data of the fiber Bragg grating sensor to the system log, and provides the user with a diagnostic report of the leakage location and related data through the operating system interface.

2. The liquid cooling method for tower computer host according to claim 1, characterized in that: In step 1, the inner layer of the pipeline is made of polytetrafluoroethylene material, wherein the thickness t satisfies the following relationship: Where, t is the pipe wall thickness, P is the working pressure of the coolant, r is the inner radius of the pipe, σ max is the maximum allowable stress of the pipeline material.

3. The liquid cooling method for tower computer host according to claim 2, characterized in that: The fiber Bragg grating sensor in step 1 monitors the strain change of the pipeline in real time, and the wavelength drift Δλ and the strain ∈ satisfy the following relationship: Δλ=K·∈, Among them, Δλ is the grating wavelength drift, K is the fiber sensitivity constant, and ∈ is the strain of the pipeline.

4. The liquid cooling method for tower computer host according to claim 1, characterized in that: In step 2, the flow rate v of the coolant is measured by a flow rate sensor, wherein the calculation formula is: Where v is the flow rate of the coolant, L is the distance between the ultrasonic sensors, and Δt is the time difference of ultrasonic propagation.

5. The liquid cooling method for tower computer host according to claim 4, characterized in that: The pressure data P and flow rate data v monitored by the pressure sensor are combined to calculate the fluid state of the coolant using the Bernoulli equation: Where P is the static pressure of the fluid, ρ is the coolant density, v is the flow velocity, g is the acceleration due to gravity, and h is the height of the fluid.

6. The liquid cooling method for tower computer host according to claim 1, characterized in that: The temperature data T collected by the temperature sensor in step 3 satisfies the following heat conduction equation: Where T is the temperature, t is the tube wall thickness, α is the thermal diffusion coefficient, Where k is the thermal conductivity of the coolant, ρ is the density of the coolant, and c is the specific heat capacity of the coolant.

7. The liquid cooling method for tower computer host according to claim 6, characterized in that: The combined flow velocity and temperature distribution model utilizes digital twin technology to dynamically update the fluid distribution and heat distribution information in the pipeline, and predict high stress concentration areas and temperature abnormality areas.

8. The liquid cooling method for tower computer host according to claim 7, characterized in that: The digital twin model uses the support vector machine algorithm to classify and predict the flow rate, pressure, temperature and strain data, and the decision function is: Among them, x is the input feature vector, y i is the sample classification label, K(x i , x) is the kernel function, b is the bias, α i is the support vector weight.

9. The liquid cooling method for tower computer host according to claim 8, characterized in that: If a leakage hazard is predicted, the water pump is actively shut down to stop the coolant circulation, and the exhaust air cooling mode is started as a temporary heat dissipation solution.

10. The liquid cooling method for tower computer host according to claim 9, characterized in that: The system records flow rate, pressure, temperature and strain data, generates a diagnostic report, and provides diagnostic information of the leak location and related data to the user through the operating system interface.

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