Liquid cooling system component loss detection method and system based on liquid cooling distribution module

Abstract

The application relates to the technical field of cooling system control and discloses a liquid cooling system component loss detection method and system based on a liquid cooling distribution module, which comprises the following steps: acquiring a set flow, collecting water pump data on the side of the water pump, calculating a water pump difference value; calculating change data, converting the change data into first frequency domain data; after a use duration, calculating second frequency domain data; calculating a frequency domain difference value; if the frequency domain difference value is greater than a frequency domain set value, a water pump loss warning is given; collecting valve data on the side of the valve; calculating the absolute value of a flow difference value as a flow calculation value, calculating a leakage trend value, and if the leakage trend value is greater than a trend set value, a valve loss warning is given; a wind speed sensor on the side of the fan collects wind speed data, and a wind speed difference value is calculated; the absolute value of the average value of a plurality of wind speed difference values is calculated as a wind speed calculation value; if the wind speed calculation value is greater than a wind speed reference value, a fan loss warning is given, and the loss state of key components of the liquid cooling system can be detected and warned in real time.

Description

Technical Field

[0001] This application relates to the technical field of cooling system control, and in particular to a method and system for detecting the wear of components in a liquid cooling system based on a liquid cooling distribution module. Background Technology

[0002] In recent years, industries such as data centers, high-performance computing, and artificial intelligence have experienced explosive growth, with the computing power of their core equipment continuously increasing, placing higher demands on heat dissipation efficiency and stability. Traditional air cooling technology, limited by its heat dissipation capacity, is prone to localized overheating in high-power-density equipment scenarios, making it difficult to meet the long-term stable operation requirements of the equipment. In contrast, liquid cooling technology, with its significant advantages such as high heat dissipation efficiency, low operating noise, and low energy consumption, can effectively solve the heat dissipation problems of high-power-density equipment and has become the mainstream development direction in the field of heat dissipation, with its application share in various high-computing industries gradually increasing.

[0003] The liquid cooling distribution unit (CDU) is the core control and distribution component of a liquid cooling system. It undertakes key functions such as coolant flow regulation, temperature control, and pressure stabilization, directly affecting the overall operating performance of the liquid cooling system. Precise control of the CDU allows for the rational allocation of coolant resources, effectively improving the heat dissipation efficiency of the liquid cooling system and reducing overall system energy consumption. It is a crucial element in ensuring the stable and efficient operation of the liquid cooling system.

[0004] Currently, traditional CDU control methods are relatively outdated. Their control logic is mostly designed around basic operational requirements, primarily achieving basic functions such as energy saving, stable temperature control, and pressure regulation. They lack the ability to monitor the real-time operating status of critical components in liquid cooling systems. Components in liquid cooling systems, such as pumps, valves, and heat exchangers, are prone to wear and aging during long-term operation. Traditional CDU control methods cannot detect and assess the wear and tear of these components in real time, making it difficult to meet the current demands for intelligent and precise control of liquid cooling systems' operational status monitoring. Summary of the Invention

[0005] In order to enable real-time detection and early warning of the wear status of key components in a liquid cooling system, this application provides a method and system for detecting the wear of components in a liquid cooling system based on a liquid cooling distribution module.

[0006] In a first aspect, this application provides a method for detecting the loss of components in a liquid cooling system based on a liquid cooling distribution module, employing the following technical solution:

[0007] A method for detecting component loss in a liquid cooling system based on a liquid cooling distribution module includes the following steps:

[0008] The system acquires a set flow rate by collecting water pump data from a first flow sensor next to the water pump. It then calculates the water pump difference based on the water pump data and the set flow rate. Within a preset sampling period, it calculates the change in the water pump difference, converting the change data into first frequency domain data using a frequency domain conversion algorithm. After a preset usage period, it calculates second frequency domain data based on the new change data. Finally, it calculates the frequency domain difference between the second and first frequency domain data. If the frequency domain difference exceeds a preset frequency domain setting value, a water pump loss warning is issued.

[0009] A second flow sensor near the valve collects valve data when the flow rate is stable. The distance between the pump and the valve is less than a preset distance. The first and second flow sensors are located in a pipe section of the same diameter. The first flow sensor is located on the side of the pump closer to the valve, and the second flow sensor is located on the side of the valve farther from the pump. The absolute value of the flow rate difference is calculated based on the pump data and the valve data. Multiple flow rate calculations are obtained within a preset collection period, and a leakage trend value is calculated. If the leakage trend value is greater than a preset trend setting value, a valve wear warning is issued.

[0010] The system acquires the set wind speed by collecting wind speed data from a wind speed sensor next to the fan when the wind speed is stable. It then calculates the wind speed difference based on the wind speed data and the set wind speed. Within a preset sampling period, the absolute value of the average of multiple wind speed differences is calculated as the wind speed calculation value. If the wind speed calculation value is greater than the preset wind speed reference value, a fan wear warning is issued.

[0011] By adopting the above technical solution, after obtaining the set flow rate, water pump data is collected by the first flow sensor next to the water pump, and the water pump difference is calculated. Change data is obtained within a preset sampling time, converted to first frequency domain data using a frequency domain conversion algorithm, and then used to calculate second frequency domain data and obtain the frequency domain difference after the sampling time. If the difference exceeds the preset frequency domain setting value, a water pump loss warning is triggered, achieving real-time detection and evaluation of water pump loss. When the flow rate is stable, valve data is collected by the second flow sensor next to the valve, and the absolute value of the flow difference is calculated in combination with the water pump data. A leakage trend value is obtained through multiple flow calculations; if the value exceeds the trend setting value, a valve loss warning is issued, achieving real-time detection and evaluation of valve loss. After obtaining the set wind speed, when the wind speed is stable, wind speed data is collected by the wind speed sensor next to the fan, and the wind speed difference is calculated. The absolute value of the average of multiple wind speed differences is calculated; if the value exceeds the wind speed reference value, a fan loss warning is triggered, achieving real-time detection and evaluation of fan loss. This system can comprehensively meet the intelligent and refined control requirements for monitoring the operating status of the liquid cooling system, which is beneficial for ensuring the stable operation of the liquid cooling system.

[0012] Optionally, the method further includes the following steps:

[0013] If the frequency domain difference is less than the frequency domain setpoint, the flow leakage trend value is less than the trend setpoint, and the calculated air volume is less than the wind speed reference value, then a first comparison value is calculated based on the frequency domain difference and the frequency domain setpoint, a second comparison value is calculated based on the flow leakage trend value and the trend setpoint, and a third comparison value is calculated based on the calculated wind speed and the wind speed reference value. The system comparison value is calculated by weighted averaging of the first comparison value, the second comparison value, and the third comparison value. If the system comparison value is greater than the preset system setpoint, then a system loss warning is issued.

[0014] By adopting the above technical solution, when there is no individual loss warning for water pumps, valves, and fans, system-level loss warning can be achieved through system comparison values, which supplements the deficiencies of single component detection and improves the comprehensiveness of the overall operating status monitoring of the liquid cooling system.

[0015] Optionally, the method further includes the following steps:

[0016] Obtain the first flow velocity value in the pipeline where the water pump is located, calculate the first flow velocity comparison value based on the first flow velocity value and the preset standard flow velocity value, and adjust the frequency domain setting value according to the positive correlation of the first flow velocity comparison value.

[0017] Obtain the first pressure value of the fluid outlet side pipeline of the valve, calculate the first pressure comparison value based on the first pressure value and the preset standard pressure value, and adjust the set value according to the positive correlation of the first pressure comparison value.

[0018] Obtain the first temperature value within a preset first distance range around the fan, calculate the first temperature comparison value based on the first temperature value and the preset first standard temperature value, and adjust the wind speed reference value based on the negative correlation of the first temperature comparison value.

[0019] By adopting the above technical solutions, the actual operating conditions of the liquid cooling system are dynamically adapted, making the frequency domain setpoint, trend setpoint, and wind speed reference value more consistent with real-time operating conditions, thereby improving the adaptability of pump, valve, and fan loss detection.

[0020] Optionally, the step of calculating the system comparison value by weighted average of the first comparison value, the second comparison value, and the third comparison value includes the following sub-steps:

[0021] Obtain the second flow velocity value within a preset second distance range around the water pump, calculate the second flow velocity comparison value based on the second flow velocity value and the preset second standard flow velocity value, and adjust the weight coefficient of the first comparison value according to the positive correlation of the second flow velocity comparison value.

[0022] Obtain the second pressure value of the valve fluid outlet side pipeline, calculate the second pressure comparison value based on the second pressure value and the preset standard pressure value, and adjust the weight coefficient of the second comparison value according to the positive correlation of the second pressure comparison value;

[0023] Obtain the outdoor ambient temperature value, calculate the second temperature comparison value based on the ambient temperature value and the preset standard temperature value, and adjust the weight coefficient of the third comparison value according to the negative correlation of the second temperature comparison value.

[0024] The weight coefficients of the first, second, and third comparison values ​​are normalized.

[0025] By adopting the above technical solution, the weights of the operators in the weighted average calculation are dynamically adjusted by combining the second flow rate value of the water pump, the second pressure value of the valve, and the outdoor ambient temperature value. After normalization processing, the overshoot of the system comparison value is prevented. This makes the calculation of the system comparison value more in line with the real-time operating conditions and helps to reduce the evaluation deviation caused by fixed weights.

[0026] Optionally, the step of collecting water pump data may also include the following sub-steps:

[0027] Obtain the water pump power and calculate the first rate of increase in water pump power;

[0028] If the initial increase rate is greater than the preset first set rate, start collecting water pump data;

[0029] After the water pump data collection begins, if the first increase rate is less than the preset second set rate, the water pump data collection will stop after a preset first waiting period; wherein the first set rate is greater than the second set rate.

[0030] Within the first waiting period, a first speed comparison value is calculated based on the first increasing speed and the second set speed, and the remaining time of the first waiting period is adjusted according to the positive correlation of the first speed comparison value.

[0031] By adopting the above technical solution, the timing of water pump data collection can be accurately determined, avoiding ineffective data collection and wasting resources. The remaining time of the first waiting period can be dynamically adjusted to better match the real-time status of the water pump, which helps to improve the accuracy of the collected data.

[0032] Optionally, the step of collecting valve data when the flow rate is stable may also include the following sub-steps:

[0033] Obtain the flow rate value from the second flow sensor and calculate the second rate of increase in the flow rate value;

[0034] If the second increase rate is less than the preset third set rate, after a preset second waiting time, the flow rate value will be used as valve data;

[0035] During the second waiting period, a second speed comparison value is calculated based on the second increase speed and the third set speed, and the remaining time of the second waiting period is adjusted according to the positive correlation of the second speed comparison value.

[0036] By adopting the above technical solution, the valve data acquisition node can be accurately controlled according to the rate of flow change, eliminating data interference when the flow is unstable, which helps to ensure the authenticity and reliability of the acquired valve data; the remaining time of the second waiting time can be dynamically adjusted to provide adaptive data support for valve loss assessment.

[0037] Optionally, the step of collecting valve data when the flow rate is stable may also include the following sub-steps:

[0038] Obtain multiple completed second waiting times, and calculate the average waiting time based on these multiple second waiting times;

[0039] The waiting time is calculated based on the average waiting time and the initial second waiting time. The third set speed is then adjusted based on the negative correlation between the waiting time and the calculated waiting time.

[0040] By adopting the above technical solution, the third set speed is adjusted according to the waiting calculation value, so that the flow stability judgment is more in line with the actual working conditions, which helps to reduce the deviation caused by the fixed setting.

[0041] Optionally, the step of collecting wind speed data when the wind speed is stable may also include the following sub-steps:

[0042] Acquire multiple wind speed values ​​from the wind speed sensor and divide the multiple wind speed values ​​into multiple wind speed groups according to the time sequence;

[0043] Calculate the average wind speed value in multiple wind speed groups to obtain multiple average wind speed values;

[0044] Calculate the fluctuation value of multiple average wind speeds. If the fluctuation value is less than the preset value, the latest average wind speed will be used as the wind speed data.

[0045] By adopting the above technical solution, and by calculating the average value of wind speed values ​​in groups and judging the degree of fluctuation, the interference of instantaneous abnormal wind speed can be filtered out, making the collected wind speed data more stable and reliable.

[0046] Optionally, the step of calculating the fluctuation value of multiple wind speed averages may further include the following sub-steps:

[0047] Collect the average wind speeds of multiple wind speeds within the target time period, and denote this as the first dataset;

[0048] Remove the maximum and minimum values ​​from the first dataset to obtain the second dataset;

[0049] The average value is calculated based on all elements in the second dataset and recorded as the baseline value.

[0050] Calculate the sum of squared deviations of all elements in the second dataset, calculate the sample variance based on the sum of squared deviations, calculate the sample standard deviation based on the sample variance, and use the sample standard deviation as the fluctuation value.

[0051] By adopting the above technical solution, and by removing extreme values ​​and using the sample standard deviation as the fluctuation value, the true state of the average wind speed fluctuation can be reflected more accurately, the interference of outliers can be reduced, and the reliability of fluctuation judgment can be improved.

[0052] Secondly, this application provides a liquid cooling system component loss detection system based on a liquid cooling distribution module, employing the following technical solution:

[0053] A liquid cooling system component loss detection system based on a liquid cooling distribution module includes a processor, wherein the processor executes the steps of the liquid cooling system component loss detection method based on a liquid cooling distribution module as described in any one of the above claims.

[0054] In summary, this application includes at least one of the following beneficial technical effects: A liquid cooling system component loss detection scheme based on a liquid cooling distribution module effectively compensates for the shortcomings of traditional CDUs in real-time detection of key components, comprehensively improving the accuracy and intelligence level of system monitoring. In pump detection, by controlling the timing of data acquisition and dynamically adjusting the waiting time, invalid acquisition is avoided, ensuring data reliability and providing high-quality support for pump loss assessment. In valve detection, the acquisition nodes are adjusted according to flow rate changes, and the set value is optimized by combining the average waiting time, filtering out unstable data interference and improving the accuracy of valve loss detection. In fan detection, by calculating the average wind speed in groups, removing extreme values, and judging fluctuations based on the sample standard deviation, instantaneous abnormal interference is reduced, enhancing the reliability of wind speed data and helping to improve the accuracy of fan loss assessment. In system-level assessment, the weight coefficients are dynamically adjusted and normalized, making the overall loss assessment more consistent with actual working conditions and reducing misjudgments and omissions. The overall solution achieves accurate loss monitoring of individual components such as pumps, valves, and fans, as well as the entire system, meeting the needs of intelligent, refined, and real-time detection and early warning for liquid cooling systems. Attached Figure Description

[0055] Figure 1 This is a flowchart illustrating a method for detecting component loss in a liquid cooling system based on a liquid cooling distribution module. Detailed Implementation

[0056] The embodiments of this application are described in detail below, and examples of the embodiments are shown in the accompanying drawings.

[0057] In the description of this specification, the references to "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples" refer to specific features, structures, materials, or characteristics described in connection with the described embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0058] This application discloses a method for detecting the loss of components in a liquid cooling system based on a liquid cooling distribution module, referring to... Figure 1 It includes the following steps:

[0059] The set flow rate is obtained from the control center of the liquid cooling system. This set flow rate is the operating flow rate that the control center requires the water pumps in the liquid cooling system to reach. Before the water pumps reach the operating flow rate, the flow rate changes gradually. During this gradual flow rate change, the water pump power changes even more rapidly. Water pump data is collected based on the first flow sensor located next to the water pump.

[0060] The process of collecting water pump data includes the following steps: Real-time acquisition of water pump power; calculation of the first rate of increase in water pump power; if the water pump power changes from p1 to p2 within a short time t, then the first rate of increase = (p2 - p1) / t. If the first rate of increase is greater than a preset first set speed, water pump data collection begins, that is, the flow data generated by the first flow sensor is used as water pump data. After starting water pump data collection, if the first rate of increase is less than a preset second set speed, water pump data collection stops after a preset first waiting period. Since the first set speed is greater than the second set speed, water pump data is obtained when the water pump power increases rapidly, and no new water pump data is obtained when the water pump power increases or decreases slowly.

[0061] Within the first waiting period, a first speed comparison value is calculated using a ratio algorithm based on the first increasing speed and the second set speed. This ratio algorithm is a division operation. The remaining time of the first waiting period is adjusted according to the positive correlation between the first speed comparison value and the remaining time. A larger first speed comparison value results in a longer remaining time, and a smaller value results in a shorter remaining time. If the pump power remains high, the remaining time is longer; if the rate of change in pump power decreases, the remaining time is shortened. This method accurately determines the timing of pump data collection, avoids ineffective data collection and resource waste, and dynamically adjusts the remaining time of the first waiting period to better reflect the real-time status of the pump, thus improving the accuracy of the collected data.

[0062] The pump difference is calculated based on pump data and a set flow rate. The pump difference can be positive or absolute, and it decreases as the pump data increases. The change in the pump difference is calculated within a preset sampling period. The sampling period can be shorter than the total time for collecting pump data, and the change can be positive or absolute, ensuring the trend is from large to small.

[0063] The changing data is converted into first frequency domain data using a frequency domain transformation algorithm, which can be a Fast Fourier Transform (FFT) algorithm. The first frequency domain data includes multiple preset frequency bands and their corresponding energy values. After a preset usage period, second frequency domain data is calculated based on the new changing data. This usage period is much longer than the sampling period and the total time for collecting water pump data. The frequency domain difference is calculated based on the second and first frequency domain data, which have the same data format. Weighting parameters are matched to the frequency bands, and then a weighted average is calculated with the energy value to obtain the frequency domain value. The first frequency domain value is calculated from the first frequency domain data, and the second frequency domain value is calculated from the second frequency domain data. The difference between the first and second frequency domain values ​​is the frequency domain difference. If the frequency domain difference is greater than a preset frequency domain setting value, a water pump loss warning is issued.

[0064] The system acquires the initial flow velocity value in the pipeline where the water pump is located. Based on this initial flow velocity value and a preset standard flow velocity value, a ratio algorithm is used to calculate a first flow velocity comparison value. The frequency domain setpoint is adjusted according to the positive correlation between the first flow velocity comparison value and the standard standard flow velocity value: the larger the first flow velocity comparison value, the larger the frequency domain setpoint; conversely, the smaller the first flow velocity comparison value, the smaller the frequency domain setpoint. This dynamically adapts to the actual operating conditions of the liquid cooling system, making the frequency domain setpoint more closely match real-time operating conditions and improving the adaptability of water pump loss detection.

[0065] A second flow sensor located near the valve collects valve data when the flow rate is stable. The distance between the pump and the valve is less than a preset distance, which can be 3-10 meters. The first and second flow sensors are located in a pipe section of the same diameter, with the first flow sensor located on the pump side closer to the valve and the second flow sensor located on the valve side further away from the pump. The flow rate value from the second flow sensor is obtained, and the second rate of increase in the flow rate is calculated.

[0066] The steps for determining flow stability are as follows: If the second increase rate is less than the preset third set rate, after a preset second waiting period, the flow value of the second flow sensor is used as the valve data. Within the second waiting period, a second speed comparison value is calculated using a ratio algorithm based on the second increase rate and the third set rate. The remaining time of the second waiting period is adjusted according to the positive correlation between the second speed comparison value and the third set rate; the larger the second speed comparison value, the longer the remaining time of the second waiting period, and vice versa. This allows for precise control of the valve data acquisition node based on the flow rate change, eliminating data interference when the flow is unstable, ensuring the accuracy and reliability of the acquired valve data, and dynamically adjusting the remaining time of the second waiting period to provide adaptive data support for valve wear assessment.

[0067] To reduce calculation time: The system acquires the most recent complete second waiting times (which may vary). The average waiting time is calculated based on these multiple complete second waiting times. A ratio algorithm is then used to calculate the waiting time value between the average waiting time and the initial second waiting time. The third set speed is adjusted based on a negative correlation with this waiting time value: a larger waiting time value results in a slower third set speed, and vice versa. Adjusting the third set speed based on the waiting time value makes the flow stability assessment more closely reflect actual operating conditions, reducing deviations caused by fixed settings.

[0068] The absolute value of the flow rate difference calculated from pump and valve data is the calculated flow rate value. Under relatively stable flow conditions (i.e., minimal flow fluctuations), the pump data should not be less than the valve data. However, within a set distance, the portion where the pump data is higher than the valve data may indicate valve leakage. Multiple calculated flow rates are obtained within a preset data acquisition period, and a leakage trend value is calculated. If the leakage trend value exceeds a preset trend setting, a valve wear warning is issued.

[0069] Based on a pressure sensor pre-installed on the pipeline and located at the valve's fluid outlet, a first pressure value is acquired in the pipeline at the valve's fluid outlet. A first pressure comparison value is calculated using a ratio algorithm based on this first pressure value and a pre-set standard pressure value. A trend setting value is then adjusted according to a positive correlation with this first pressure comparison value: the larger the first pressure comparison value, the larger the trend setting value; conversely, the smaller the first pressure comparison value, the smaller the trend setting value. This dynamically adapts to the actual operating conditions of the liquid cooling system, making the trend setting value more closely match real-time operating conditions and improving the adaptability of valve wear detection.

[0070] The set wind speed is obtained from the control center of the liquid cooling system. This set wind speed is the operating wind speed that the control center requires the fans in the liquid cooling system to reach. Before the fans reach their operating wind speed, the wind speed produced by the fans changes gradually. During this gradual change in wind speed, the fan power changes even more rapidly. However, due to the presence of turbulence, the wind speed fluctuates significantly at the wind speed sensor.

[0071] Wind speed data is collected using a wind speed sensor located near the fan when the wind speed is stable. Multiple wind speed values ​​are acquired from the sensor and grouped into multiple wind speed groups according to time sequence. The average wind speed value is calculated for each group. The fluctuation level of these average wind speed values ​​is then calculated. Multiple average wind speed values ​​for a target time period are collected and denoted as the first dataset.

[0072] The first dataset is divided into two datasets. The maximum and minimum values ​​are removed from the first dataset to obtain the second dataset. The average value of all elements in the second dataset is calculated and set as the baseline. The sum of squared deviations of all elements in the second dataset is calculated. The sample variance is calculated from the sum of squared deviations, and the sample standard deviation is calculated from the sample variance. The sample standard deviation is used as the fluctuation level value. By removing extreme values ​​and using the sample standard deviation as the fluctuation level value, the true state of the average wind speed fluctuation can be more accurately reflected, outlier interference can be reduced, and the reliability of fluctuation level judgment can be improved. If the fluctuation level value is less than a preset level value, the latest average wind speed is used as the wind speed data. By grouping wind speed values, calculating the average value, and judging the fluctuation level, instantaneous abnormal wind speed interference can be filtered out, making the collected wind speed data more stable and reliable.

[0073] The wind speed difference is calculated using an interpolation algorithm based on wind speed data and a set wind speed. The wind speed difference can be a positive value or an absolute value. The average of multiple wind speed differences is calculated within a preset sampling period, and the absolute value of the average is taken as the calculated wind speed value. If the calculated wind speed value is greater than a preset wind speed reference value, a fan wear warning is issued.

[0074] The system acquires a first temperature value within a preset first distance range around the fan. This first distance range can be 3-10 meters, indirectly reflecting the temperature around the unit's equipment. A first temperature comparison value is calculated using a ratio algorithm based on this first temperature value and a preset first standard temperature value. The fan speed reference value is then adjusted according to this negative correlation: a smaller first temperature comparison value corresponds to a larger fan speed reference value, and vice versa. This dynamic adaptation to the actual operating conditions of the liquid cooling system ensures the fan speed reference value better reflects real-time operating conditions, improving the adaptability of fan wear detection.

[0075] If the frequency domain difference is less than the frequency domain setpoint, the flow leakage trend value is less than the trend setpoint, and the calculated air volume is less than the wind speed reference value, then the first comparison value is calculated using a ratio algorithm based on the frequency domain difference and the frequency domain setpoint; the second comparison value is calculated using a ratio algorithm based on the flow leakage trend value and the trend setpoint; and the third comparison value is calculated using a ratio algorithm based on the calculated wind speed and the wind speed reference value. The system comparison value is calculated by weighted averaging the first, second, and third comparison values. If the system comparison value is greater than the preset system setpoint, then a system loss warning is issued.

[0076] The system acquires a second flow velocity value within a preset second distance range around the water pump. This second distance range can be 10-20 meters. The flow velocity value within this second distance range can indirectly provide feedback on the power status of the water pump or pump set. A second flow velocity comparison value is calculated using a ratio algorithm based on the second flow velocity value and a preset second standard flow velocity value. The weighting coefficient of the first comparison value is adjusted according to a positive correlation between the second and second flow velocity comparison values: the larger the second flow velocity comparison value, the larger the weighting coefficient of the first comparison value; conversely, the smaller the second flow velocity comparison value, the smaller the weighting coefficient of the first comparison value. The weighting coefficient of the first comparison value is adaptively adjusted based on the power status of the water pump or pump set, allowing the system's loss warning to be adapted to the on-site conditions.

[0077] The system acquires a second pressure value from the valve's fluid outlet pipe. Based on this second pressure value and a preset standard pressure value, a second pressure comparison value is calculated using a ratio algorithm. The weighting coefficient of the second pressure comparison value is adjusted according to a positive correlation: the larger the second pressure comparison value, the larger the weighting coefficient; conversely, the smaller the second pressure comparison value, the smaller the weighting coefficient. This adaptive adjustment of the weighting coefficient based on the pressure conditions in the valve's fluid outlet pipe ensures that the system's loss warning is adapted to the actual field conditions.

[0078] The system acquires the outdoor ambient temperature value, which must be at least 30 meters away and represents the temperature in its natural environment. A second temperature comparison value is calculated using a ratio algorithm based on the ambient temperature value and a preset standard temperature value. The weighting coefficient of the third comparison value is adjusted according to the negative correlation between the second and third temperature comparison values: the larger the second comparison value, the smaller the weighting coefficient of the third comparison value; conversely, the smaller the second comparison value, the larger the weighting coefficient of the third comparison value. The weighting coefficients of the first, second, and third comparison values ​​are then normalized. The weights of the operators in the weighted average calculation are dynamically adjusted based on the second flow rate value of the water pump, the second pressure value of the valve, and the outdoor ambient temperature value, and then normalized again to prevent overshooting of the system comparison value. This ensures that the system comparison value calculation more closely reflects real-time operating conditions and helps reduce evaluation bias caused by fixed weights.

[0079] After obtaining the set flow rate, the system collects water pump data using the first flow sensor next to the water pump and calculates the water pump difference. Within a preset sampling time, the system obtains changing data, converts it to first frequency domain data using a frequency domain conversion algorithm, calculates second frequency domain data after the specified time, and obtains the frequency domain difference. If the difference exceeds the preset frequency domain value, a water pump loss warning is triggered, achieving real-time detection and assessment of water pump loss. When the flow rate is stable, the system uses the second flow sensor next to the valve to collect valve data, combines it with the water pump data to calculate the absolute value of the flow difference, and obtains a leakage trend value through multiple flow calculations. If the value exceeds the trend setting value, a valve loss warning is triggered, achieving real-time detection and assessment of valve loss. After obtaining the set wind speed, when the wind speed is stable, the system uses the wind speed sensor next to the fan to collect wind speed data, calculates the wind speed difference, and calculates the absolute value of the average of multiple wind speed differences. If the value exceeds the wind speed reference value, a fan loss warning is triggered, achieving real-time detection and assessment of fan loss. When there are no individual loss warnings for the water pump, valve, or fan, system-level loss warnings are achieved through system comparison values, supplementing the deficiencies of single-component detection and improving the comprehensiveness of the overall operating status monitoring of the liquid cooling system. It can meet the intelligent and precise control requirements for monitoring the operating status of liquid cooling systems, which helps to ensure the stable operation of liquid cooling systems.

[0080] This application also discloses a liquid cooling system component loss detection system based on a liquid cooling distribution module, including a processor, wherein the processor executes the steps of the liquid cooling system component loss detection method based on a liquid cooling distribution module as described in any of the above embodiments.

[0081] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for detecting wear of components of a liquid cooling system based on a liquid cooling distribution module, characterized in that, The method comprises the following steps: Obtaining a set flow rate, collecting water pump data based on a first flow rate sensor beside the water pump, calculating a water pump difference value based on the water pump data and the set flow rate, calculating a change data of the water pump difference value within a preset sampling time length, converting the change data into first frequency domain data through a frequency domain conversion algorithm, calculating second frequency domain data based on new change data after a preset use time length, and calculating a frequency domain difference value based on the second frequency domain data and the first frequency domain data; If the frequency domain difference value is greater than a preset frequency domain set value, a water pump loss warning is performed; Collecting valve data based on a second flow rate sensor beside the valve when the flow rate is stable, wherein the distance between the water pump and the valve is less than a preset set distance, the first flow rate sensor and the second flow rate sensor are located in the same pipe diameter pipe section, the first flow rate sensor is located on the side of the water pump close to the valve, and the second flow rate sensor is located on the side of the valve away from the water pump; calculating an absolute value of a flow rate difference value as a flow rate calculation value based on the water pump data and the valve data, obtaining a plurality of flow rate calculation values within a preset collection time length and calculating a leakage trend value, and if the leakage trend value is greater than a preset trend set value, a valve loss warning is performed; Obtaining a set wind speed, collecting wind speed data based on a wind speed sensor beside the fan when the wind speed is stable, calculating a wind speed difference value based on the wind speed data and the set wind speed, and calculating an absolute value of an average of a plurality of wind speed difference values as a wind speed calculation value within a preset sampling time length; if the wind speed calculation value is greater than a preset wind speed reference value, a fan loss warning is performed.

2. The liquid cooling system component wear detection method based on a liquid cooling distribution module according to claim 1, characterized in that, The method further comprises the following steps: If the frequency domain difference value is less than the frequency domain set value, the flow rate leakage trend value is less than the trend set value, and the air volume calculation value is less than the wind speed reference value, a first comparison value is calculated based on the frequency domain difference value and the frequency domain set value, a second comparison value is calculated based on the flow rate leakage trend value and the trend set value, a third comparison value is calculated based on the wind speed calculation value and the wind speed reference value, a system comparison value is calculated by weighted average based on the first comparison value, the second comparison value, and the third comparison value, and if the system comparison value is greater than a preset system set value, a system loss warning is performed.

3. The liquid cooling system component loss detection method based on a liquid cooling distribution module according to claim 1 or 2, characterized in that, Obtaining a first flow rate value of a pipe where the water pump is located, calculating a first flow rate comparison value based on the first flow rate value and a preset standard flow rate value, and positively correlating the first flow rate comparison value to adjust the frequency domain set value; Obtaining a first pressure value of a pipe on the outlet side of the valve, calculating a first pressure comparison value based on the first pressure value and a preset standard pressure value, and positively correlating the first pressure comparison value to adjust the trend set value; Obtaining a first temperature value within a preset first distance range around the fan, calculating a first temperature comparison value based on the first temperature value and a preset first standard temperature value, and negatively correlating the first temperature comparison value to adjust the wind speed reference value.

4. The liquid cooling system component wear detection method based on a liquid cooling distribution module according to claim 2, characterized by, In the step of calculating a system comparison value by weighted average based on the first comparison value, the second comparison value, and the third comparison value, the following sub-steps are included: Obtaining a second flow rate value within a preset second distance range around the water pump, calculating a second flow rate comparison value based on the second flow rate value and a preset second standard flow rate value, and positively correlating the second flow rate comparison value to adjust the weight coefficient of the first comparison value. Obtaining a second pressure value of the valve fluid outlet side pipeline, calculating a second pressure comparison value according to the second pressure value and a preset standard pressure value, and adjusting a weight coefficient of the second comparison value in a positive correlation according to the second pressure comparison value; Obtaining an environmental temperature value of the outdoor environment, calculating a second temperature comparison value according to the environmental temperature value and a preset standard temperature value, and adjusting a weight coefficient of the third comparison value in a negative correlation according to the second temperature comparison value; Normalizing the weight coefficient of the first comparison value, the weight coefficient of the second comparison value and the weight coefficient of the third comparison value.

5. The liquid cooling system component wear detection method based on a liquid cooling distribution module according to claim 1, 2 or 4, characterized in that, The step of collecting the water pump data further includes the following sub-steps: Obtaining a water pump power, and calculating a first increasing speed of the water pump power; If the first increasing speed is greater than a preset first setting speed, starting to collect the water pump data; After starting to collect the water pump data, if the first increasing speed is less than a preset second setting speed, stopping to collect the water pump data after a preset first waiting duration; wherein the first setting speed is greater than the second setting speed; Within the first waiting duration, calculating a first speed comparison value according to the first increasing speed and the second setting speed, and adjusting a remaining time of the first waiting duration in a positive correlation according to the first speed comparison value.

6. The liquid cooling system component loss detection method based on a liquid cooling distribution module according to claim 1 or 2, characterized by, The step of collecting the valve data when the flow is stable further includes the following sub-steps: Obtaining a flow value of the second flow sensor, and calculating a second increasing speed of the flow value; If the second increasing speed is less than a preset third setting speed, taking the flow value as the valve data after a preset second waiting duration; Within the second waiting duration, calculating a second speed comparison value according to the second increasing speed and the third setting speed, and adjusting a remaining time of the second waiting duration in a positive correlation according to the second speed comparison value.

7. The liquid cooling system component wear detection method based on a liquid cooling distribution module according to claim 6, characterized in that, The step of collecting the valve data when the flow is stable further includes the following sub-steps: Obtaining a plurality of completed second waiting durations, and calculating an average waiting duration according to the plurality of second waiting durations; Calculating a waiting calculation value according to the average waiting duration and an initial second waiting duration, and adjusting the third setting speed in a negative correlation according to the waiting calculation value.

8. The liquid cooling system component wear detection method based on a liquid cooling distribution module according to claim 1, 2 or 4, characterized by, The step of collecting the wind speed data when the wind speed is stable further includes the following sub-steps: Obtaining a plurality of wind speed values of the wind speed sensor, and dividing the plurality of wind speed values into a plurality of wind speed groups according to time sequence; Calculating an average value of the wind speed values in the plurality of wind speed groups to obtain a plurality of wind speed average values; Calculating a fluctuation degree value of the plurality of wind speed average values, and taking a latest wind speed average value as the wind speed data if the fluctuation degree value is less than a preset setting degree value.

9. The liquid cooling system component wear detection method based on a liquid cooling distribution module according to claim 8, characterized in that, The step of calculating the fluctuation degree value of the plurality of wind speed average values further includes the following sub-steps: Collecting a plurality of wind speed average values in a target period, denoted as a first data set; Removing a maximum value and a minimum value in the first data set to obtain a second data set; Calculating an average value according to all elements in the second data set, denoted as a reference value; Calculating a sum of squared deviations of all elements in the second data set, calculating a sample variance according to the sum of squared deviations, and taking the sample standard deviation as the fluctuation degree value.

10. A liquid cooling system component wear detection system based on a liquid cooling distribution module, characterized by, The processor executes the steps of the liquid cooling system component wear detection method based on the liquid cooling distribution module according to any one of claims 1-9.

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