Heat-proof intelligent control software for computer case

Abstract

The invention relates to the technical field of equipment heat management, in particular to computer case heat-proof intelligent control software which comprises a heat source state monitoring module, a local sampling dynamic adjustment module, a sudden change risk trend identification module, a regional heat flow load analysis module and a cooling resource distribution control module. According to the invention, the sampling frequency is enhanced in time when the temperature rise rate exceeds the standard, the change trend of a heat source is captured more accurately, and the high heat change unit is preferentially sampled and subjected to sudden change early warning analysis, so that when the equipment is faced with a sudden overheating condition, the equipment can be quickly intervened, and the stability and reliability of the system are guaranteed; according to heat flow density changes of different areas, through heat flow density analysis and monitoring, distribution of heat dissipation resources is optimized, and it is ensured that the temperature in the case is effectively controlled under the high-load condition, so that the stability of equipment under the high-load condition is improved, unnecessary energy consumption is reduced while the heat dissipation efficiency is improved, and the service life of the equipment is prolonged. The service life of equipment is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment thermal management, and in particular to intelligent control software for thermal protection of a computer chassis. Background Art

[0002] Equipment thermal management technology involves the structural design and control of internal temperature control systems within chassis. This area focuses on combining hardware components with software control logic to achieve real-time temperature monitoring, intelligent analysis, and dynamic response adjustment during electronic equipment operation. This prevents temperature anomalies that can lead to hardware performance degradation, system stability impairment, or device failure. This technical area encompasses hardware structure optimization, thermal flow modeling and analysis, and intelligent control algorithm design, emphasizing the optimization of thermal management system performance indicators in terms of response speed, energy consumption control, and device life extension.

[0003] The computer chassis heat protection intelligent control software is a thermal management solution for computer equipment. When the internal chassis temperature rises, it intelligently adjusts the operating state of the cooling device to ensure that all electronic components within the chassis operate within a safe temperature range. Its uses include preventing high-heat components such as the processor, graphics processor, and motherboard chipset from overheating, leading to frequency throttling, reboots, and damage. This extends the overall lifespan of the computer and improves the stability and reliability of the device under high-load operating conditions. Through intelligent control, it reduces unnecessary heat dissipation energy consumption and achieves energy efficiency optimization.

[0004] Traditional control software relies on temperature threshold settings, activating cooling devices when a component reaches a set temperature. This ignores the complex thermal interactions and transient changes between components within the system. For example, CPUs and GPUs generate a large amount of heat rapidly under high load conditions. Traditional software fails to efficiently identify and prioritize the cooling needs of high-load components, resulting in an imbalanced distribution of cooling resources. In addition, the temperature control mechanism of traditional software responds slowly to sudden temperature rises and fails to predict the risk of overheating of the equipment through timely temperature rise rate analysis. This can cause a delayed response when the temperature is abnormal, affecting the stability and reliability of the entire equipment. Traditional software's cooling strategy fails to fully utilize the synergistic effects of the various cooling devices within the chassis, and fails to dynamically adjust for different areas and load conditions, resulting in a certain amount of energy waste and insufficient cooling efficiency, affecting the energy efficiency and service life of the equipment. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a computer case heat protection intelligent control software.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a computer chassis heat protection intelligent control software, the software comprising:

[0007] The heat source status monitoring module obtains the operating data of the components inside the chassis, detects the instantaneous change amplitude of the power supply current of each component, compares and analyzes the change amplitude of the power supply current with the temperature change rate, screens the active heat generating units at the current stage, and obtains a list of the current active heat generating units;

[0008] The local sampling dynamic adjustment module compares the difference in magnitude between the actual temperature change rate and the reference temperature rise rate based on the current list of active heating units, determines whether the change rate exceeds the temperature change rate threshold, and if so, increases the sampling frequency level of the corresponding unit to generate a priority sampling list for units with high thermal change;

[0009] The mutation risk trend identification module determines whether the increase in the current change rate is accompanied by an increase in the temperature rise change rate based on the priority sampling list of the high thermal change units, selects units that meet the synchronous increase conditions, establishes mutation warning records, and generates a local temperature rise mutation warning list;

[0010] The regional heat flux load analysis module calls the heat flux density detection data in the chassis area based on the local temperature rise mutation warning list, screens the areas where the accumulated heat flux exceeds the set heat flux density warning value, and generates a list of high heat flux density load areas.

[0011] As a further solution of the present invention, the current list of active heating units specifically includes unit identification numbers, real-time power supply current thresholds, instantaneous temperature rise rates and physical space locations; the high heat change unit priority sampling list includes priority identification codes, adjusted sampling frequencies, change rate level intervals and sampling node indexes; the local temperature rise mutation warning list specifically includes warning unit numbers, power supply current change amplitudes, synchronous temperature rise change amplitudes and warning trigger timestamps; the high heat flux density load area list specifically refers to area numbers, heat flux density integral values, heat flux density change trends and cumulative heat accumulation amounts.

[0012] As a further solution of the present invention, the heat source status monitoring module includes:

[0013] The operation data extraction submodule obtains the operation data of the components inside the chassis, detects the power supply current and temperature of the central processing unit (CPU), the power supply current and temperature of the graphics processing unit (GPU), the power supply current and temperature of the memory module, and calls the physical location coordinates of the CPU, graphics processing unit, and memory module in the chassis layout diagram to generate a basic component operation data list;

[0014] The power supply current change detection submodule collects two consecutive current values of the power supply current of the central processing unit, graphics processing unit, and memory module based on the basic operation data list of the components, calculates the instantaneous change amplitude of the power supply current, collects the temperature change rate of the central processing unit, graphics processing unit, and memory module in the corresponding time period, establishes paired data of the power supply current change amplitude and temperature change rate of the components, and generates a power supply and temperature rise change matching data set;

[0015] The heat unit screening and identification submodule compares the matching degree between the power supply current change amplitude and the temperature change rate of each component based on the power supply and temperature rise change matching data set, screens component units whose power supply current change amplitude exceeds the baseline change threshold and whose temperature change rate increases synchronously, calls the physical position coordinates to confirm the position of the screened components, obtains the screened component unit information, and establishes a list of currently active heat units.

[0016] As a further solution of the present invention, the local sampling dynamic adjustment module includes:

[0017] The temperature change rate extraction submodule obtains the current active heating unit list, collects two consecutive temperature values measured for each heating unit, monitors the time interval between temperature value changes, calculates the ratio of the two temperature measurement results to the time interval as the temperature change rate, and establishes a continuous temperature change rate list;

[0018] The change rate amplitude comparison submodule uses the standard temperature rise rate as a comparison benchmark based on the continuous temperature change rate list, compares the amplitude difference between the actual temperature change rate of each unit and the standard temperature rise rate, calculates the temperature change rate offset, and compares it with the temperature change rate threshold. The unit with the offset greater than the threshold is selected to generate a list of units with over-threshold temperature changes;

[0019] The sampling frequency adjustment submodule extracts the offset level of each unit based on the above-threshold temperature change unit list, calls the initial setting value of the unit sampling frequency, adjusts the sampling frequency value according to the sampling frequency adjustment ratio corresponding to the offset level, records the frequency adjustment level and the corresponding unit index, and establishes a priority sampling list for high thermal change units.

[0020] As a further solution of the present invention, the formula for calculating the temperature change rate offset is:

[0021]

[0022] Where, ΔR i Represents the temperature change rate offset of the i-th unit, T i1 Represents the first temperature value measured by the i-th unit, T i2 Represents the second measured temperature value of the i-th unit, t i1 represents the first measurement time, ti2 Represents the second measurement time, S i Represents the standard temperature rise rate of the i-th unit, T max is the maximum temperature difference allowed by the representative unit.

[0023] As a further solution of the present invention, the mutation risk trend identification module includes:

[0024] The current change rate acquisition submodule obtains the priority sampling list of the high thermal change units, collects two consecutive power supply current values within a time window of each unit, detects the time interval between power supply current changes, calculates the power supply current change rate of each unit within the corresponding time interval, obtains the current change rate data of each unit, and establishes a power supply current change rate sequence set;

[0025] The temperature rise change rate acquisition submodule collects two consecutive temperature values within the corresponding unit time window based on the power supply current change rate sequence set, detects the time interval of temperature change, calculates the temperature rise change rate of each unit within the corresponding time interval, and generates a corresponding set of power supply and temperature rise change rates based on the unit index in the power supply current change rate sequence set;

[0026] The synchronous change screening submodule calculates the amplitude difference between the power supply current change rate and the temperature rise change rate of each unit based on the corresponding set of power supply and temperature rise change rates, screens out units whose amplitude difference is less than the synchronous change threshold, calls the unit identifier recorded in the high thermal change unit priority sampling list, establishes the screened unit synchronous change record, and generates a local temperature rise mutation warning list.

[0027] As a further solution of the present invention, the regional heat flow load analysis module includes:

[0028] The heat flux density data acquisition submodule, based on the local temperature rise mutation warning list, calls the heat flux density detection data in the chassis area, obtains the change in heat flux density per unit time in each sub-area, records the heat flux density data of each sub-area, and generates a heat flux density data set per unit time;

[0029] The heat flux density calculation submodule performs cumulative calculation on the heat flux density variation collected in each sub-region based on the heat flux density data set per unit time, calculates the heat flux density accumulation per unit area of each sub-region, and generates a sub-region heat flux density accumulation list;

[0030] The high heat flux area screening submodule screens out sub-areas whose heat flux accumulation exceeds a set heat flux warning value according to the sub-area heat flux accumulation list, records the sub-area information that meets the conditions, and generates a high heat flux load area list.

[0031] As a further solution of the present invention, the formula for calculating the cumulative heat flux density per unit area of each sub-region is:

[0032]

[0033] Among them, H acc is the cumulative heat flux of the kth sub-region, A k is the normalized value of the area of the kth sub-region, q j is the normalized value of the heat flux per unit time measured in the kth sub-area during the jth time period, Δt j is the normalized value of the length of the jth time interval, n k is the number of time intervals in the kth sub-region, T erf is the normalized value of the maximum allowable temperature difference, t0 is the reference time constant, and λ1 is the logarithmic adjustment coefficient.

[0034] As a further embodiment of the present invention, the system further comprises:

[0035] The cooling resource allocation control module calls the cooling fan air volume output and the coolant flow rate data of the liquid cooling device in the local cooling resource pool according to the list of high heat flux density load areas, selects the cooling units in the resource pool whose cooling response time is less than the set response threshold, matches the air volume adjustment amplitude or the liquid flow adjustment amplitude according to the heat flux density load ranking order, forms a local cooling adjustment plan, and generates local cooling control allocation information;

[0036] The local cooling control allocation information includes a target area number, an allocated air volume interval, an allocated flow rate interval, and a heat dissipation unit execution priority.

[0037] As a further solution of the present invention, the cooling resource allocation control module includes:

[0038] The cooling resource data acquisition submodule, based on the list of high heat flux density load areas, calls the cooling fan air volume output data in the local cooling resource pool and the coolant flow rate data of the liquid cooling device, obtains the air volume and liquid flow rate information of each cooling unit, and establishes a cooling resource data set;

[0039] The cooling response time screening submodule screens the cooling units in the resource pool whose cooling response time is less than a set response threshold based on the cooling resource data set, records the information of the cooling units that meet the conditions, and generates a list of cooling units with low response time;

[0040] The cooling resource allocation submodule adjusts the local cooling parameters based on the low response time cooling unit list and the heat flux load ranking order in the high heat flux load area list, thereby generating local cooling control allocation information.

[0041] Compared with the prior art, the advantages and positive effects of the present invention are:

[0042] In the present invention, by intelligently monitoring component operation data and analyzing the power supply current and temperature changes of each component, the active heat source area inside the chassis can be identified in real time, thereby realizing dynamic monitoring and adjustment, being able to efficiently locate overheating components, quickly respond to temperature changes, and avoid system frequency reduction, restart or damage due to local overheating. Combined with the comparison of temperature change rate and current change amplitude, the ability to accurately judge abnormal temperature rise conditions is improved. When the temperature rise rate exceeds the standard, the sampling frequency is timely increased to more accurately capture the changing trend of the heat source. By giving priority to sampling and sudden change warning analysis of high heat change units, it is ensured that when the equipment faces sudden overheating, it can intervene quickly to ensure system stability and reliability. According to the changes in heat flux density in different areas, the allocation of heat dissipation resources is optimized through heat flux density analysis and monitoring, ensuring that the temperature inside the chassis is effectively controlled under high load conditions, thereby improving the stability of the equipment under high load conditions, reducing unnecessary energy consumption while improving heat dissipation efficiency, and extending the service life of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 is a software flow chart of the present invention;

[0045] Figure 2 Schematic diagram of the software framework of the present invention;

[0046] Figure 3 This is a flow chart of the heat source status monitoring module of the present invention;

[0047] Figure 4 This is a flow chart of the local sampling dynamic adjustment module of the present invention;

[0048] Figure 5 This is a flow chart of the mutation risk trend identification module of the present invention;

[0049] Figure 6 This is a flow chart of the regional heat flow load analysis module of the present invention;

[0050] Figure 7 This is a flow chart of the cooling resource allocation control module of the present invention. DETAILED DESCRIPTION

[0051] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0052] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0053] In the embodiments of the present invention, the terms "image" and "picture" may be used interchangeably. It should be noted that, when the distinction between them is not emphasized, their intended meanings are the same. The terms "of," "corresponding," and "corresponding" may be used interchangeably. It should be noted that, when the distinction between them is not emphasized, their intended meanings are the same.

[0054] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0055] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0056] See also Figure 1 , a computer chassis heat protection intelligent control software, the software includes:

[0057] The heat source status monitoring module obtains the operating data of the components inside the chassis, including the power supply current of the central processing unit, the graphics processing unit, the memory module, and the temperature measured by the corresponding temperature sensor. It detects the instantaneous change amplitude of the power supply current of each component, collects the temperature change rate of the corresponding time period, calls the physical location coordinates of each component in the chassis layout, compares and analyzes the power supply current change amplitude and the temperature change rate, and selects the active heat generating units in the current stage to obtain a list of the current active heat generating units.

[0058] The local sampling dynamic adjustment module collects two consecutive temperature change rates of each unit based on the current list of active heating units, calls the preset standard temperature rise rate, compares the amplitude difference between the actual temperature change rate and the benchmark temperature rise rate, and determines whether the change rate exceeds the temperature change rate threshold. If so, the sampling frequency level of the corresponding unit is increased, the change amplitude level is recorded, and a priority sampling list for high thermal change units is generated;

[0059] The mutation risk trend identification module, based on a prioritized sampling list of high-heat-change units, collects the supply current change rate and local temperature rise change rate within the corresponding unit time window. It then calculates the amplitude difference between the two to determine whether an increase in the current change rate is accompanied by an increase in the temperature rise change rate. It then selects units that meet the synchronous increase condition, establishes a mutation warning record, and generates a local temperature rise mutation warning list.

[0060] The regional heat flux load analysis module uses the local temperature rise mutation warning list to call the heat flux density detection data in the chassis area, collect the heat flux density change per unit time, calculate the cumulative heat flux density per unit area of each sub-area, screen out areas where the heat flux cumulative value exceeds the set heat flux density warning value, and generate a list of high heat flux load areas;

[0061] The cooling resource allocation control module uses the list of high heat flux density load areas to call the cooling fan air volume output and the coolant flow rate data of the liquid cooling equipment in the local cooling resource pool. It selects the cooling units in the resource pool whose cooling response time is less than the set response threshold. It matches the air volume adjustment range or liquid flow adjustment range according to the heat flux density load ranking order, forms a local cooling adjustment plan, and generates local cooling control allocation information.

[0062] The current list of active heating units specifically includes the unit identification number, real-time power supply current threshold, instantaneous temperature rise rate and physical space location. The priority sampling list of high heat change units includes the priority identification code, adjusted sampling frequency, change rate level range and sampling node index. The local temperature rise mutation warning list specifically includes the warning unit number, power supply current change amplitude, synchronous temperature rise change amplitude and warning trigger timestamp. The high heat flux density load area list specifically refers to the area number, heat flux density integral value, heat flux density change trend and cumulative heat accumulation. The local cooling control allocation information includes the target area number, allocated air volume range, allocated flow rate range and heat dissipation unit execution priority.

[0063] See also Figure 2 and Figure 3 ,The heat source status monitoring module includes an operation data extraction submodule, a power supply current change detection submodule, and a heating unit screening and identification submodule;

[0064] The operation data extraction submodule obtains the operation data of the components inside the chassis, detects the power supply current and temperature of the central processing unit (CPU), the power supply current and temperature of the graphics processing unit (GPU), the power supply current and temperature of the memory module, and calls the physical location coordinates of the CPU, graphics processing unit, and memory module in the chassis layout diagram to generate a basic component operation data list;

[0065] When obtaining the operating data of the components inside the chassis, the power supply channel monitoring interface of the central processing unit, graphics processing unit, and memory module is first called to read the power supply current value I of the central processing unit in real time. cpu , Graphics processing unit power supply current value I gpu 、Memory module power supply current value I mem , synchronously call the internal temperature sensor of the chassis at the corresponding time to read the temperature value T of the CPU cpu , Graphics processing unit temperature value T gpu 、Memory module temperature value T mem , for example, at a certain moment I cpu =45A, T cpu =65℃、I gpu =38A, T gpu =61℃、I mem =12A, T mem =55℃, after the monitoring is completed, the chassis layout file is called according to the chassis structure design drawing, and the physical position of the central processor (x cpu ,y cpu ,z cpu ), Graphics Processing Unit Physical Location (x gpu ,y gpu ,z gpu ), memory module physical location (x mem ,y mem ,z mem ), such as the CPU position (120, 200, 50) mm, the GPU position (150, 180, 50) mm, and the memory module position (100, 220, 50) mm. After the collection is completed, the power supply current value and temperature value of each component are combined to form preliminary operation data entries, and the timestamp and location coordinate information are annotated for each entry. By storing the above operation data entry set in a structured manner, a basic component operation data list is established;

[0066] The power supply current change detection submodule collects two consecutive current values of the CPU, GPU, and memory module's power supply current based on the basic component operation data list, calculates the instantaneous change amplitude of the power supply current, collects the temperature change rate of the CPU, GPU, and memory module within the corresponding time period, establishes paired data of the component's power supply current change amplitude and temperature change rate, and generates a matching data set for power supply and temperature rise changes;

[0067] Based on the basic operation data list of the components, first collect the power supply current values I of the CPU, GPU, and memory module at two consecutive moments. cpu1 ,I cpu2 , I gpu1 ,I gpu2 , I mem1,I mem2 , and record the corresponding time interval Δt at the same time. For example, the CPU measures I cpu1 =45A, I cpu2 =48A, the time interval is 5 seconds, and then use the formula Calculate the instantaneous change of the power supply current and substitute it into the CPU current change rate ΔI cpu =0.6A / s, and perform the same operation on the graphics processing unit and memory module in turn, and then collect the temperature change values T1 and T2 in the same time period, such as T cpu1 =65℃、T cpu2 =68℃, calculate the temperature rise rate ΔT cpu =0.6℃ / s, forming paired data of the supply current change amplitude and temperature rise rate of each component. For the paired data of different components, add index tags and timestamps to establish a matching data set of power supply and temperature rise changes;

[0068] The heat-generating unit screening and identification submodule compares the degree of match between the supply current change amplitude and the temperature change rate of each component based on the power supply and temperature rise change matching data set. It then screens out components whose supply current change amplitude exceeds the baseline change threshold and whose temperature change rate increases simultaneously. It then uses the physical location coordinates to confirm the location of the screened components, obtains the screened component unit information, and creates a list of currently active heat-generating units.

[0069] Based on the power supply and temperature rise matching dataset, we first compare the matching degree of the power supply current change amplitude ΔI and the temperature rise change rate ΔT of each component. We set the power supply current change baseline threshold to 0.5A / s and the temperature rise synchronization increase baseline value to 0.5℃ / s. When setting the threshold, we use the actual power consumption and temperature response in a typical high-performance chassis as a reference. For example, for ΔI cpu =0.6A / s and ΔT cpu =0.6℃ / s, it is determined that the two are synchronously improved and the current change exceeds the reference change threshold, and the central processing unit is marked as a candidate unit. For the graphics processing unit ΔI gpu =0.3A / s, ΔT gpu =0.4℃ / s, it is determined that the standard is not met and no screening is performed. All qualified component units are screened out through item-by-item comparison. Then, the physical location coordinate information of the corresponding components in the chassis layout is called to confirm the specific physical location of the screened components, such as the central processing unit location (120,200,50)mm, to form a screening result entry. All the screened component unit entries are collected to establish a list of currently active heating units;

[0070] See also Figure 2 and Figure 4,The local sampling dynamic adjustment module includes a temperature change rate extraction ,submodule, a change rate amplitude comparison submodule, and a sampling frequency ,adjustment submodule;

[0071] The temperature change rate extraction submodule obtains the current list of active heating units, collects two consecutive temperature values of each heating unit, monitors the time interval between temperature changes, calculates the ratio of the two temperature measurement results to the time interval as the temperature change rate, and establishes a continuous temperature change rate list;

[0072] When obtaining the current active heating unit list, first retrieve the index of each heating unit and the corresponding historical operation record, collect the temperature values of each heating unit measured twice in a row, and set the temperature of unit A at time t1 = 100s to T A1 = 65℃, at time t2 = 160s the temperature is T A2 =72℃, the time interval for monitoring temperature change Δt=t2-t1=60s, for each heating unit, the temperature change rate is calculated based on the two collected temperature measurement values and the corresponding time interval, using the formula Substituting the above data, we can get the temperature change rate of unit A: Perform the same measurement and calculation process on all heating units in turn, and set T B1 =64℃、T B2 =66℃, t1=200s, t2=260s, then The collected data must uniformly record the timestamp, temperature value, and change rate value, and mark the unit index for subsequent list collection and organization. The temperature change rate of all heating units is stored in a structured form in the data list to establish a continuous temperature change rate list;

[0073] The rate-of-change magnitude comparison submodule uses the standard temperature rise rate as a comparison benchmark based on the continuous temperature change rate list. It compares the magnitude difference between the actual temperature change rate of each unit and the standard temperature rise rate, calculates the temperature change rate offset, and compares it with the temperature change rate threshold. It then filters out units with offsets greater than the threshold and generates a list of units with over-threshold temperature changes.

[0074] The formula for calculating the temperature change rate offset is:

[0075]

[0076] Where, ΔR i Represents the temperature change rate offset of the i-th unit, T i1 Represents the first temperature value measured by the i-th unit, T i2 Represents the second measured temperature value of the i-th unit, t i1 represents the first measurement time, t i2 Represents the second measurement time, Si Represents the standard temperature rise rate of the i-th unit, T max is the maximum temperature difference allowed by the representative unit;

[0077] Temperature rate offset measures the difference between a component's actual temperature rate of change and a set standard. If the difference exceeds a set threshold, it may indicate that the component is experiencing excessive thermal load and requires appropriate thermal management measures.

[0078] Based on the continuous temperature change rate list, call the standard temperature rise rate S preset for different heating units k As a comparison benchmark, set the standard temperature rise rate of unit A to S A =0.08℃ / s, unit B is S B =

[0079] 0.05℃ / s, compare the amplitude difference between the actual measured temperature change rate of each unit and the standard temperature rise rate, using the formula:

[0080]

[0081] Substitute data into unit A. If T max =50℃, then Set the temperature change rate offset threshold to 0.04, and compare ΔR A =0.06>0.04, the offset of unit A is determined to be beyond the threshold and marked as an abnormal unit. For unit B, set ΔR B =0.02, ΔR B =0.02<0.04, do not mark as abnormal, filter all cells with offset greater than the threshold, and record them with cell index, temperature change rate, standard temperature rise rate, and offset, and put them into the abnormal cell screening list to generate a list of cells with over-threshold temperature change;

[0082] The sampling frequency adjustment submodule extracts the offset level of each unit based on the list of units with super-threshold temperature changes, calls the initial setting value of the unit sampling frequency, adjusts the sampling frequency value according to the sampling frequency adjustment ratio corresponding to the offset level, records the frequency adjustment level and the corresponding unit index, and establishes a priority sampling list for high thermal change units;

[0083] Based on the list of over-threshold temperature change units, extract the temperature change rate offset corresponding to each unit, and divide the level interval according to the offset size. For example, set the offset level to: 0.04<ΔR k ≤0.08 is the first level, 0.08<ΔR k ≤0.12 is the second level, ΔR k >0.12 is level 3, unit A offset ΔR A=0.06, belonging to the first level offset level, calling the initial setting value of the unit sampling frequency, setting the initial sampling frequency of unit A to f 0A =1Hz, the adjustment ratio is based on the offset level, and the first level offset corresponds to a 20% increase, that is, the adjusted frequency is f A =1.2Hz, record the adjusted frequency value, offset level and unit index, perform the same process on each over-threshold unit in turn to form a complete frequency adjustment information table, summarize all adjustment information to form a priority ranking, and establish a priority sampling list for high thermal change units;

[0084] See also Figure 2 and Figure 5 ,The mutation risk trend identification module includes the current change rate acquisition submodule, the temperature rise change rate acquisition submodule, and the synchronous change screening submodule;

[0085] The current change rate acquisition submodule obtains a priority sampling list of high-heat change units, collects two consecutive power supply current values within each unit's time window, detects the time interval between power supply current changes, calculates the power supply current change rate of each unit within the corresponding time interval, obtains the current change rate data of each unit, and establishes a power supply current change rate sequence set;

[0086] When obtaining the priority sampling list of high thermal change units, first extract the unit number and the corresponding operating time window, and collect the power supply current value of each unit twice in the time window. For example, for unit C, the power supply current at t1 = 10s is I C1 =12A, when t2=20s, the supply current is I C2 =14A, monitor the change time interval between two power supply current values Δt=t2-t1=10s, calculate the power supply current change rate based on the collected current data and time interval, using the formula Substitute the values into the current change rate of unit C For other units, the power supply current change rate is also collected and calculated. For example, the value collected by unit D is I D1 =8A, I D2 =9.5A, time interval t2-t1=5s, then 0.3A / s, the supply current change rate of all units and the related timestamps and unit indexes are recorded one by one, organized into a unified entry list, and structured storage forms a data sequence, and finally a supply current change rate sequence set is established;

[0087] The temperature rise change rate acquisition submodule collects two consecutive temperature values within the corresponding unit time window based on the power supply current change rate sequence set, detects the time interval of temperature change, calculates the temperature rise change rate of each unit within the corresponding time interval, and generates a corresponding set of power supply and temperature rise change rates based on the unit index in the power supply current change rate sequence set;

[0088] Based on the supply current change rate sequence set, each unit is further processed to collect two consecutive temperature measurement values within the corresponding time window. For unit C, the temperature is T at t1 = 10s. C1 =60℃, when t2=20s, the temperature is T C2 =66℃, the time interval between two temperature measurements is Δt=10s, and the formula is used. Calculate the temperature rise rate of change and substitute it into the unit C temperature rise rate of change For unit D, set T D1 =58℃、T D2 =59.5℃, time interval 5s, calculated During the acquisition process, the unit indexes in the power supply current change rate sequence set are uniformly associated, that is, unit C corresponds to ΔI C , ΔT C , unit D corresponds to ΔI D , ΔT D ,All corresponding data entries record indexes, timestamps, power supply current change rates, and temperature rise change rates, and are organized into a structured form to establish a corresponding set of power supply and temperature rise change rates;

[0089] The synchronous change screening submodule calculates the amplitude difference between the power supply current change rate and the temperature rise change rate of each unit based on the corresponding set of power supply and temperature rise change rates, screens units with amplitude differences less than the synchronous change threshold, calls the unit identifiers recorded in the high thermal change unit priority sampling list, creates synchronous change records for the screened units, and generates a local temperature rise mutation warning list;

[0090] According to the corresponding set of power supply and temperature rise change rates, the amplitude difference between the power supply current change rate and the temperature rise change rate is calculated for each unit, using the formula ΔV k =|ΔI k -ΔT k |, where ΔV k The difference between the current change rate and the temperature rise change rate of unit k is substituted into the unit C data to obtain ΔV C =|0.2-0.6|=0.4, substitute the data of unit D to get ΔV D =|0.3-0.3|=0, set the synchronous change threshold to 0.2, if the unit difference is less than 0.2, it is determined to be a synchronous change unit. D =0<0.2, the determination unit D is a synchronous change unit, for ΔV C=0.4>0.2, it is not determined to be a synchronous change. The units that meet the synchronous change conditions are screened, the unit identifiers recorded in the high thermal change unit priority sampling list are called, the synchronous change determination results are recorded, and the index, power supply current change rate, temperature rise change rate, and difference data of the synchronous change unit are uniformly sorted to form a screening table, and finally a local temperature rise mutation warning list is generated;

[0091] See also Figure 2 and Figure 6 ,The regional heat flux load analysis module includes a heat flux density data acquisition submodule, a heat flux density calculation submodule, and a high heat flux area screening submodule;

[0092] The heat flux density data acquisition submodule uses the local temperature rise mutation warning list to call the heat flux density detection data in the chassis area, obtain the change in heat flux density per unit time in each sub-area, record the heat flux density data of each sub-area, and generate a heat flux density data set per unit time;

[0093] Based on the local temperature rise mutation warning list, the sub-area index that needs to be monitored for heat flux is first selected, and the heat flux density detection node embedded in the chassis is called to extract the heat flux density measurement data per unit time corresponding to each sub-area number. For each sub-area, the heat flux density change is obtained more than twice within the set monitoring period. For example, sub-area X measures q at t1=0s. X1 =250W / m 2 , q is measured at t2=60s X2 =280W / m 2 , then the heat flux change per unit time is q diffX =q X2 -q X1 =30W / m 2 , record the timestamp, sub-region number, sampling times and change amount, for sub-region Y if q Y1 =220W / m 2 ,q Y2 =235W / m 2 , then the change is q diffY =15W / m 2 , uniformly archive each monitoring result, merge the change amount and time interval data of each sub-area within the time interval into a structured record table, clearly mark the sub-area ID, time period number, change amount, and measurement time of each data, form a standardized storage format, and finally form a complete unit time heat flux density change data set, that is, unit time heat flux density data set;

[0094] The heat flux calculation submodule accumulates the heat flux changes collected in each sub-region based on the heat flux data set per unit time, calculates the heat flux accumulation per unit area of each sub-region, and generates a list of heat flux accumulations for each sub-region.

[0095] The formula for calculating the cumulative heat flux density per unit area of each sub-region is:

[0096]

[0097] Among them, H acc is the cumulative heat flux of the kth sub-region, A k is the normalized value of the area of the kth sub-region, q j is the normalized value of the heat flux per unit time measured in the kth sub-area during the jth time period, Δt j is the normalized value of the length of the jth time interval, n k is the number of time intervals in the kth sub-region, T erf is the normalized value of the maximum allowable temperature difference, t0 is the reference time constant, and λ1 is the logarithmic adjustment coefficient;

[0098] Based on the heat flux density data set per unit time, all heat flux change data during the monitoring period are extracted for each sub-region, and a cumulative operation is performed item by item. First, the normalized value A of the sub-region area is confirmed. k For example, let the area of sub-region X be A X =0.5m 2 , then the normalized area A X =1 (normalized based on itself), the change per unit time q within the calling time period j and the length of the corresponding time period Δt j , using the formula:

[0099]

[0100] Calculate the cumulative heat flux density, assuming T erf =50℃, λ1=0.1, t0=60s, and substitute the first segment data q in sub-area X X1 =30W / m 2 , Δt1=60s, we get:

[0101]

[0102] The unit is the normalized heat flux accumulation. The same accumulation process is performed on all time periods of each sub-region in turn, and the heat flux changes of each sub-region are accumulated. The corresponding sub-region number, accumulated heat flux value, and accumulated time window number are recorded, and unified into an entry-type record to generate a sub-region heat flux accumulation form, that is, a sub-region heat flux accumulation list;

[0103] The high heat flux area screening submodule selects sub-areas whose heat flux accumulation exceeds the set heat flux warning value based on the sub-area heat flux accumulation list, records the sub-area information that meets the conditions, and generates a high heat flux load area list;

[0104] According to the sub-region heat flux accumulation list, set the unified heat flux warning value H alert , for example, let H alert =30 (normalized unit), read the cumulative heat flux H of each sub-area one by one acc Compare, if H acc >H alert , it is determined to be a high heat flux load sub-region, for example, the cumulative amount H in sub-region X accX =36>30, meet the screening conditions, record the sub-area ID, cumulative value, and the amplitude exceeding the warning value. Otherwise, if the sub-area Y cumulative value H accY =28<30, no record will be made. For the heat flux accumulation in different intervals, the interval division rule is adopted: 30 <H acc ≤40 is marked as a first-level warning, 40 <H acc ≤50 is marked as Level 2 warning, H acc A value >50 is a Level 3 warning. The screening results are recorded and categorized into a unified screening table. The entries include the sub-area number, cumulative level, and whether the warning mark is exceeded. Finally, a statistical table of areas with excessive high heat flux density is generated, i.e., a list of areas with high heat flux density load.

[0105] See also Figure 2 and Figure 7 ,The cooling resource allocation control module includes a cooling resource data acquisition submodule, a cooling response time screening submodule, and a cooling resource allocation submodule;

[0106] The cooling resource data acquisition submodule, based on the list of high heat flux density load areas, calls the cooling fan air volume output data in the local cooling resource pool and the coolant flow rate data of the liquid cooling equipment to obtain the air volume and liquid flow rate information of each cooling unit and establish a cooling resource data set;

[0107] Based on the list of high heat flux density load areas, first obtain the identifiers of all sub-areas in the heat flux load monitoring state and map them to the corresponding heat dissipation resource pool items. According to the heat dissipation resource configuration table, call the fan device and liquid cooling device associated with the physical location of the area, and obtain the real-time fan air volume output value and the coolant flow rate value of the liquid cooling device through the hardware interface. The instantaneous air volume F output by the current fan is collected in units of seconds. x and the instantaneous flow rate of the coolant L x For example, for sub-area Z, the fan air volume read is F Z=120CFM, liquid flow rate is L Z =0.35L / min, bind the corresponding equipment number, equipment type, and equipment physical installation location information, and record the sampling time, operating status, and control parameters. Each collected value is written into a data table according to the structured data record template. The fields in the table include: sub-area number, fan number, air volume value, sampling time, fan identification status, liquid cooling equipment number, liquid flow value, control voltage, current output frequency, fluid medium temperature, etc. Then, set the collection group number for the sampling frequency of different types of equipment to facilitate subsequent classification and control. Finally, organize the structure by unit, summarize and form a complete data structure record file, and generate a cooling resource data set;

[0108] The cooling response time screening submodule screens the cooling units in the resource pool whose cooling response time is less than the set response threshold based on the cooling resource data set, records the information of the cooling units that meet the conditions, and generates a list of cooling units with low response time;

[0109] Based on the cooling resource dataset, the real-time response parameters of all cooling unit fans and liquid cooling devices are extracted. The response time is defined as the time from the triggering of the control instruction to the target flow reaching 90% of the set value. The response time t of each group of devices is recorded. resp , convert the sampling value into seconds. For example, for device F1, the response time is t resp1 =0.6s, device F2 is t resp2 =1.8s, set the response threshold to t th =1.2s, according to the judgment logic, if t resp <t th , it is marked as compliant with the response time. If the response time exceeds the threshold, it is marked as unavailable. According to this standard, all device data are traversed and judgment operations are performed respectively to extract the fan and liquid cooling unit information that meet the conditions. The screening logic also needs to match whether the current status of the device is in an adjustable state. When the mark field is "active", it is considered an available device. If the current status of the device is "standby" or "offline", it is excluded from the screening range. At the same time, combined with the device location coordinates, a data set of heat dissipation devices that meet the fast cooling response conditions is generated. The output fields should include device number, response time, device type, device control accuracy level and physical area identification to form a structured screening entry and generate a list of low response time cooling units;

[0110] The cooling resource allocation submodule adjusts local cooling parameters based on the list of low-response-time cooling units and the order of heat flux load ranking in the list of high-heat flux load areas, matching the air volume adjustment range or liquid flow adjustment range in sequence, and generates local cooling control allocation information.

[0111] Based on the low response time cooling unit list, first read the heat flux density cumulative value of each area in the high heat flux density load area list, sort them in descending order according to the value, and build a regional heat flux density ranking sequence. Set the cumulative amount of area A to 42, B to 37, and C to 31, then the arrangement order is ABC, and call the fans or liquid cooling devices in the available cooling units respectively. Corresponding to the matching control range, set the air volume adjustment range zoning rules: the first-level load area (heat flux accumulation greater than 40) matches the air volume increase by 20%, the second-level load area (30-40) matches the air volume increase by 10%, and the low If no adjustment is made at 30, for example, if the initial fan air volume for area A is 120 CFM, the adjustment value is 120 × (1 + 0.2) = 144 CFM. If it is a liquid cooling device, the same step-by-step adjustment ratio is set based on the set liquid flow rate. At the same time, the adjusted output value, the pre-adjustment set value, the device number, and the adjusted sub-area number are recorded. All adjustment items are filed in a dynamic control table and marked with the control number and execution timestamp. Finally, according to the matching rule processing results, a structured form is generated as the control output file to generate the local cooling control allocation information.

[0112] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0113] In this disclosure, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0114] It should be understood that in various 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.

[0115] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0116] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0117] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of the device or unit, which can be electrical, mechanical or other forms.

[0118] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0119] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0120] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0121] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A computer chassis heat protection intelligent control software, characterized in that: The software includes: The heat source status monitoring module obtains the operating data of the components inside the chassis, detects the instantaneous change amplitude of the power supply current of each component, compares and analyzes the change amplitude of the power supply current with the temperature change rate, screens the active heat generating units at the current stage, and obtains a list of the current active heat generating units; The local sampling dynamic adjustment module compares the difference in magnitude between the actual temperature change rate and the reference temperature rise rate based on the current list of active heating units, determines whether the change rate exceeds the temperature change rate threshold, and if so, increases the sampling frequency level of the corresponding unit to generate a priority sampling list for units with high thermal change; The mutation risk trend identification module determines whether the increase in the current change rate is accompanied by an increase in the temperature rise change rate based on the priority sampling list of the high thermal change units, selects units that meet the synchronous increase conditions, establishes mutation warning records, and generates a local temperature rise mutation warning list; The regional heat flux load analysis module calls the heat flux density detection data in the chassis area based on the local temperature rise mutation warning list, screens the areas where the accumulated heat flux exceeds the set heat flux density warning value, and generates a list of high heat flux density load areas.

2. The computer chassis heat protection intelligent control software according to claim 1, characterized in that: The current list of active heating units specifically includes the unit identification number, real-time power supply current threshold, instantaneous temperature rise rate and physical space location; the high heat change unit priority sampling list includes the priority identification code, adjusted sampling frequency, change rate level interval and sampling node index; the local temperature rise mutation warning list specifically includes the warning unit number, power supply current change amplitude, synchronous temperature rise change amplitude and warning trigger timestamp; the high heat flux density load area list specifically refers to the area number, heat flux density integral value, heat flux density change trend and cumulative heat accumulation.

3. The computer chassis heat protection intelligent control software according to claim 2, characterized in that: The heat source status monitoring module includes: The operation data extraction submodule obtains the operation data of the components inside the chassis, detects the power supply current and temperature of the central processing unit (CPU), the power supply current and temperature of the graphics processing unit (GPU), the power supply current and temperature of the memory module, and calls the physical location coordinates of the CPU, graphics processing unit, and memory module in the chassis layout diagram to generate a basic component operation data list; The power supply current change detection submodule collects two consecutive current values of the power supply current of the central processing unit, graphics processing unit, and memory module based on the basic operation data list of the components, calculates the instantaneous change amplitude of the power supply current, collects the temperature change rate of the central processing unit, graphics processing unit, and memory module in the corresponding time period, establishes paired data of the power supply current change amplitude and temperature change rate of the components, and generates a power supply and temperature rise change matching data set; The heat unit screening and identification submodule compares the matching degree between the power supply current change amplitude and the temperature change rate of each component based on the power supply and temperature rise change matching data set, screens component units whose power supply current change amplitude exceeds the baseline change threshold and whose temperature change rate increases synchronously, calls the physical position coordinates to confirm the position of the screened components, obtains the screened component unit information, and establishes a list of currently active heat units.

4. The computer chassis heat protection intelligent control software according to claim 3, characterized in that: The local sampling dynamic adjustment module includes: The temperature change rate extraction submodule obtains the current active heating unit list, collects two consecutive temperature values measured for each heating unit, monitors the time interval between temperature value changes, calculates the ratio of the two temperature measurement results to the time interval as the temperature change rate, and establishes a continuous temperature change rate list; The change rate amplitude comparison submodule uses the standard temperature rise rate as a comparison benchmark based on the continuous temperature change rate list, compares the amplitude difference between the actual temperature change rate of each unit and the standard temperature rise rate, calculates the temperature change rate offset, and compares it with the temperature change rate threshold. The unit with the offset greater than the threshold is selected to generate a list of units with over-threshold temperature changes; The sampling frequency adjustment submodule extracts the offset level of each unit based on the above-threshold temperature change unit list, calls the initial setting value of the unit sampling frequency, adjusts the sampling frequency value according to the sampling frequency adjustment ratio corresponding to the offset level, records the frequency adjustment level and the corresponding unit index, and establishes a priority sampling list for high thermal change units.

5. The computer chassis heat protection intelligent control software according to claim 4, characterized in that: The formula for calculating the temperature change rate offset is: Where, ΔR i Represents the temperature change rate offset of the i-th unit, T i1 Represents the first temperature value measured by the i-th unit, T i2 Represents the second measured temperature value of the i-th unit, t i1 represents the first measurement time, t i2 Represents the second measurement time, S i Represents the standard temperature rise rate of the i-th unit, T max is the maximum temperature difference allowed by the representative unit.

6. The computer chassis heat protection intelligent control software according to claim 5, characterized in that: The mutation risk trend identification module includes: The current change rate acquisition submodule obtains the priority sampling list of the high thermal change units, collects two consecutive power supply current values within a time window of each unit, detects the time interval between power supply current changes, calculates the power supply current change rate of each unit within the corresponding time interval, obtains the current change rate data of each unit, and establishes a power supply current change rate sequence set; The temperature rise change rate acquisition submodule collects two consecutive temperature values within the corresponding unit time window based on the power supply current change rate sequence set, detects the time interval of temperature change, calculates the temperature rise change rate of each unit within the corresponding time interval, and generates a corresponding set of power supply and temperature rise change rates based on the unit index in the power supply current change rate sequence set; The synchronous change screening submodule calculates the amplitude difference between the power supply current change rate and the temperature rise change rate of each unit based on the corresponding set of power supply and temperature rise change rates, screens out units whose amplitude difference is less than the synchronous change threshold, calls the unit identifier recorded in the high thermal change unit priority sampling list, establishes the screened unit synchronous change record, and generates a local temperature rise mutation warning list.

7. The computer chassis heat protection intelligent control software according to claim 6, characterized in that: The regional heat flow load analysis module includes: The heat flux density data acquisition submodule, based on the local temperature rise mutation warning list, calls the heat flux density detection data in the chassis area, obtains the change in heat flux density per unit time in each sub-area, records the heat flux density data of each sub-area, and generates a heat flux density data set per unit time; The heat flux density calculation submodule performs cumulative calculation on the heat flux density variation collected in each sub-region based on the heat flux density data set per unit time, calculates the heat flux density accumulation per unit area of each sub-region, and generates a sub-region heat flux density accumulation list; The high heat flux area screening submodule screens out sub-areas whose heat flux accumulation exceeds a set heat flux warning value according to the sub-area heat flux accumulation list, records the sub-area information that meets the conditions, and generates a high heat flux load area list.

8. The computer chassis heat protection intelligent control software according to claim 7, characterized in that: The formula for calculating the cumulative heat flux density per unit area of each sub-region is: Among them, H acc is the cumulative heat flux of the kth sub-region, A k is the normalized value of the area of the kth sub-region, q j is the normalized value of the heat flux per unit time measured in the kth sub-area during the jth time period, Δt j is the normalized value of the length of the jth time interval, n k is the number of time intervals in the kth sub-region, T erf is the normalized value of the maximum allowable temperature difference, t0 is the reference time constant, and λ1 is the logarithmic adjustment coefficient.

9. The computer chassis heat protection intelligent control software according to claim 8, characterized in that: The software also includes: The cooling resource allocation control module calls the cooling fan air volume output and the coolant flow rate data of the liquid cooling device in the local cooling resource pool according to the list of high heat flux density load areas, selects the cooling units in the resource pool whose cooling response time is less than the set response threshold, matches the air volume adjustment amplitude or the liquid flow adjustment amplitude according to the heat flux density load ranking order, forms a local cooling adjustment plan, and generates local cooling control allocation information; The local cooling control allocation information includes a target area number, an allocated air volume interval, an allocated flow rate interval, and a heat dissipation unit execution priority.

10. The computer chassis heat protection intelligent control software according to claim 9, characterized in that: The cooling resource allocation control module includes: The cooling resource data acquisition submodule, based on the list of high heat flux density load areas, calls the cooling fan air volume output data in the local cooling resource pool and the coolant flow rate data of the liquid cooling device, obtains the air volume and liquid flow rate information of each cooling unit, and establishes a cooling resource data set; The cooling response time screening submodule screens the cooling units in the resource pool whose cooling response time is less than a set response threshold based on the cooling resource data set, records the information of the cooling units that meet the conditions, and generates a list of cooling units with low response time; The cooling resource allocation submodule adjusts the local cooling parameters based on the low response time cooling unit list and the heat flux load ranking order in the high heat flux load area list, thereby generating local cooling control allocation information.

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