Intelligent adjusting method and system for cooling fan of computer

Abstract

The invention discloses an intelligent adjustment method and system for a computer cooling fan, and relates to the technical field of computer fan adjustment, a computer host temperature area is divided, a defined area set is output, the defined area set is collected, the temperature of each temperature area is obtained, and first temperature data is output; defining a global target temperature; establishing a model to obtain a global fan control signal and a weighted average temperature; calculating a total cooling speed after secondary acquisition; comparing the total cooling speed with an ideal value; by accurately dividing and monitoring the temperature area of the computer host and intelligently adjusting the rotating speed and angle of the fan, the heat dissipation efficiency is remarkably improved, the local temperature is prevented from being too high, the internal components of the equipment are protected, the service life is prolonged, the performance and stability of the equipment under high load are improved, the operation cost is reduced, and the service life of the equipment is prolonged. And the method accords with the green and energy-saving development trend and has an important application value.

Description

Technical Field

[0001] The present invention relates to the technical field of computer fan adjustment, and in particular to an intelligent adjustment method and system for a computer cooling fan. Background Art

[0002] With the rapid development of modern electronic technology, high-density electronic devices such as high-performance computer hosts, data center servers, and high-performance computing clusters are playing an increasingly important role in daily life and industrial production. These devices integrate a large number of high-performance components, such as CPUs, GPUs, memory modules, hard disk drives, and power supply units, which generate a lot of heat during operation. If this heat cannot be dissipated in a timely and effective manner, the internal temperature of the device will rise sharply, affecting the performance and stability of the device, and may even cause hardware failures, resulting in data loss or system crashes.

[0003] At present, the Chinese invention patent with application number CN202010728794.9 discloses a computer heat dissipation control system based on BIOS real-time monitoring. It is necessary to write and store the code for real-time monitoring of temperature and control of fan speed in the BIOS chip. The real-time temperature monitoring is mainly to make the BIOS temperature detection function have real-time monitoring and early warning. Then, after the code is written and the computer is started, the BIOS completes the code startup and initialization, and starts real-time monitoring and control of the fan speed after executing the code. In order to better facilitate users to control the heat dissipation system and adjust the fan speed, a menu of a real-time heat dissipation monitoring system is added to the BIOS setting interface, and a control program for manually adjusting the fan gear is added at the operating system level. The BIOS is very accurate in directly detecting the hardware situation. Therefore, using the BIOS to detect the CPU temperature in real time and intelligently adjust the fan speed can greatly improve the computer's own heat dissipation regulation and avoid abnormal computer freezes and blue screens caused by excessive temperature.

[0004] The above technology makes it difficult to individually adjust the local temperature according to the local cooling effect after the overall cooling, and it is difficult to evenly cool all equipment, resulting in excessive local temperature. Summary of the invention

[0005] The technical problem solved by the present invention is that it is difficult to individually adjust the local temperature according to the local cooling effect after the overall cooling by the above technology, and it is difficult to evenly cool all the equipment, resulting in excessively high local temperature.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] A computer cooling fan intelligent adjustment method comprises the following steps:

[0008] Step S1, dividing the temperature area of ​​the computer host and outputting it as a defined area set, collecting the defined area set once, obtaining the temperature of each temperature area in the defined area set, outputting it as first temperature data, establishing a first corresponding relationship between each temperature area and the first temperature data, and outputting it as a first area temperature set;

[0009] Step S2, defining global target temperature data, establishing a dynamic temperature weighted model, inputting the first area temperature set into the dynamic temperature weighted model, and obtaining a global fan control signal and a first weighted average temperature data;

[0010] Step S3, inputting the global fan control signal to the fan control terminal, performing secondary collection on the defined area set after a preset time interval, obtaining the temperature of each temperature area in the defined area set, outputting it as second temperature data, establishing a second corresponding relationship between each temperature area and the second temperature data, and outputting it as a second area temperature set;

[0011] Step S4, inputting the second area temperature set into the dynamic temperature weighted average model, obtaining the second weighted average temperature data, calculating the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, outputting the current total cooling rate data, comparing the current total cooling rate data with the preset ideal total cooling rate data, and outputting the first comparison result;

[0012] Step S5, obtaining the first temperature data and the second temperature data corresponding to the same temperature area in the first area temperature set and the second area temperature set according to the first comparison result, calculating the cooling speed, outputting it as the current area cooling speed data, establishing a corresponding relationship between the current area cooling speed data and the corresponding temperature area, outputting it as a cooling speed set, comparing the current area cooling speed data in the cooling speed set with the preset ideal area cooling speed data, and outputting a second comparison result;

[0013] Step S6, inputting the second comparison result into a preset adjustment control comparison set, wherein the adjustment control comparison set includes the temperature zone, the corresponding adjustable fan position and the adjustable fan angle, obtaining the adjustment parameter signal and inputting it into the fan control terminal.

[0014] Preferably, the step S1 includes the following sub-steps:

[0015] Step S101, dividing the temperature regions of the computer host and outputting them as a defined region set, wherein the names of the temperature regions in the defined region set include CPU, GPU, memory module, hard disk drive and power supply unit;

[0016] Step S102, collect data for the defined area set, obtain the temperature of each temperature area in the defined area set, output it as first temperature data, establish a first corresponding relationship between each temperature area and the first temperature data, and output it as a first area temperature set.

[0017] Preferably, step S2 includes the following sub-steps:

[0018] Step S201, define global target temperature data and establish a dynamic temperature weighted model. The logic of the dynamic temperature weighted model is:

[0019] Receive the regional temperature set and calculate the weighted average temperature data according to the regional weight, where the regional weight is:

[0020] CPU: 0.4, GPU: 0.3, memory module: 0.15, hard disk drive: 0.1, power supply unit: 0.05;

[0021] The mathematical expression of weighted average temperature data is:

[0022] T avg =W 1 ×T 1 +W 2 ×T 2 +W 3 ×T 3 +W 4 ×T 4 +W 5 ×T 5

[0023] Among them, T avg is the weighted average temperature data, W 1 is the regional weight corresponding to the temperature region CPU, T 1 is the first temperature data corresponding to the temperature zone CPU, W 2 is the regional weight corresponding to the temperature region GPU, T 2 is the first temperature data corresponding to the temperature area GPU, W 3 is the regional weight corresponding to the temperature region memory module, T 3 is the first temperature data corresponding to the temperature region memory module, W 4 is the regional weight corresponding to the hard disk drive in the temperature region, T 4 is the first temperature data corresponding to the temperature zone hard disk drive, W 5 is the regional weight corresponding to the temperature regional power supply unit, T 5 The first temperature data corresponding to the temperature zone power supply unit;

[0024] Calculate the difference between the weighted average temperature data and the global target temperature data, and output it as first difference data;

[0025] If the first difference data is within the preset first threshold interval or is smaller than the preset first threshold interval, no global fan control signal is output;

[0026] If the first difference data is within the preset second threshold interval, the global fan control signal is output as the first wind speed data and the first wind volume data;

[0027] If the first difference data is within a preset third threshold interval, the global fan control signal is output as the second wind speed data and the second wind volume data;

[0028] If the first difference data is greater than a preset second threshold range, a fan failure warning signal is output.

[0029] Preferably, the step S2 further includes a step S202, inputting the first area temperature set into a dynamic temperature weighted model, acquiring a fan control signal and weighted average temperature data, and outputting a global fan control signal and first weighted average temperature data.

[0030] Preferably, step S3 includes the following sub-steps:

[0031] Step S301, inputting a global fan control signal to a fan control terminal for a preset time interval;

[0032] Step S302, after a time interval, perform secondary collection on the defined area set, obtain the temperature of each temperature area in the defined area set, output as second temperature data, establish a second corresponding relationship between each temperature area and the second temperature data, and output as a second area temperature set.

[0033] Preferably, step S4 includes the following sub-steps:

[0034] Step S401, inputting the second region temperature set into a dynamic temperature weighted average model, obtaining weighted average temperature data, and outputting the data as second weighted average temperature data;

[0035] Step S402, calculating the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, the mathematical expression is:

[0036]

[0037] Among them, v d1 is the total cooling rate, T avg1 is the first weighted average temperature data, T avg2 is the second weighted average temperature data, t is the time interval;

[0038] The output is the current total cooling speed data;

[0039] Step S403, comparing the current total cooling rate data with the preset ideal total cooling rate data;

[0040] If the current total cooling rate data is less than the ideal cooling rate data, it is determined to be a local temperature adjustment;

[0041] If the current total cooling rate data is greater than or equal to the ideal cooling rate data, it is determined that no local temperature adjustment is required;

[0042] The output is a first comparison result, wherein the first comparison result includes performing local temperature adjustment and not requiring local temperature adjustment.

[0043] Preferably, step S5 includes the following sub-steps:

[0044] Step S501, obtaining a first comparison result. If the first comparison result is to perform local temperature adjustment, obtaining first temperature data and second temperature data corresponding to the same temperature area in the first area temperature set and the second area temperature set, and calculating the regional cooling rate. The mathematical expression is:

[0045]

[0046] Among them, v d2 is the regional cooling rate, T minus1 is any first temperature data in the first region temperature set, T minus2 The second temperature data of the same temperature region as the first temperature data in the second region temperature set;

[0047] The output is the cooling rate data of the current area.

[0048] Preferably, the step S5 further includes the following sub-steps:

[0049] Step S502, establishing a corresponding relationship between the current region cooling rate data and the corresponding temperature region, and outputting it as a cooling rate set;

[0050] Step S503, compare the current area cooling speed data in the cooling speed set with the preset ideal area cooling speed data, and output a second comparison result, which is the current area cooling speed data lower than the ideal area cooling speed data and the corresponding temperature area.

[0051] Preferably, step S6 includes the following sub-steps:

[0052] Step S601, inputting the second comparison result into a preset adjustment control comparison set, wherein the adjustment control comparison set includes a temperature zone, a corresponding adjustable fan position, and an adjustable fan angle, obtaining an adjustable fan position and an adjustable fan angle corresponding to a temperature zone that is the same as the temperature zone in the second comparison result, establishing a third corresponding relationship between the temperature zone, the adjustable fan position, and the adjustable fan angle, and outputting the third corresponding relationship as an adjustment parameter signal;

[0053] Step S602: inputting the adjustment parameter signal to the fan control terminal to adjust the fan.

[0054] A computer cooling fan intelligent adjustment system, which is applied to any of the above-mentioned computer cooling fan intelligent adjustment methods, comprises a primary acquisition module, a temperature weighting module, a secondary acquisition module, a first comparison module, a second comparison module and a regional control module;

[0055] The primary acquisition module is used to define the temperature area of ​​the computer host, output as a defined area set, perform a primary acquisition on the defined area set, obtain the temperature of each temperature area in the defined area set, output as first temperature data, establish a first corresponding relationship between each temperature area and the first temperature data, and output as a first area temperature set;

[0056] The temperature weighting module is used to define global target temperature data, establish a dynamic temperature weighting model, input the first area temperature set into the dynamic temperature weighting model, and obtain a global fan control signal and a first weighted average temperature data;

[0057] The secondary acquisition module is used to input the global fan control signal to the fan control end, and after a preset time interval, perform secondary acquisition on the defined area set to obtain the temperature of each temperature area in the defined area set, output as second temperature data, establish a second corresponding relationship between each temperature area and the second temperature data, and output as a second area temperature set;

[0058] The first comparison module is used to input the second area temperature set into the dynamic temperature weighted average model, obtain the second weighted average temperature data, calculate the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, output the current total cooling rate data, compare the current total cooling rate data with the preset ideal total cooling rate data, and output the first comparison result;

[0059] The second comparison module is used to obtain the first temperature data and the second temperature data corresponding to the same temperature area in the first area temperature set and the second area temperature set according to the first comparison result, calculate the cooling speed, output as the current area cooling speed data, establish the corresponding relationship between the current area cooling speed data and the corresponding temperature area, output as the cooling speed set, compare the current area cooling speed data in the cooling speed set with the preset ideal area cooling speed data, and output the second comparison result;

[0060] The regional control module is used to input the second comparison result into a preset adjustment control comparison set, which includes temperature zones, corresponding adjustable fan positions and adjustable fan angles, obtain an adjustment parameter signal and input it into the fan control terminal.

[0061] The beneficial effects of the present invention are as follows: the present invention can significantly improve the heat dissipation efficiency, avoid local excessive temperature, protect the internal components of the equipment, extend the service life, and improve the performance and stability of the equipment under high load, thereby reducing the operating cost. It conforms to the development trend of green energy conservation and has important application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A flowchart of a method for intelligently adjusting a computer cooling fan provided by an embodiment of the present invention;

[0063] Figure 2 A basic flow chart of a computer cooling fan intelligent adjustment system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0065] Example 1, reference Figure 1 , provides a computer cooling fan intelligent adjustment method, comprising the following steps:

[0066] Step S1, divide the temperature areas of the computer host and output them as a defined area set, collect the defined area set once, obtain the temperature of each temperature area in the defined area set, output it as first temperature data, establish a first corresponding relationship between each temperature area and the first temperature data, and output it as a first area temperature set.

[0067] Step S2, defining global target temperature data, establishing a dynamic temperature weighted model, inputting the first area temperature set into the dynamic temperature weighted model, and obtaining a global fan control signal and a first weighted average temperature data.

[0068] Step S3, input the global fan control signal to the fan control end, and after a preset time interval, perform secondary sampling on the defined area set to obtain the temperature of each temperature area in the defined area set, output as second temperature data, establish a second corresponding relationship between each temperature area and the second temperature data, and output as a second area temperature set.

[0069] Step S4, input the second area temperature set into the dynamic temperature weighted average model, obtain the second weighted average temperature data, calculate the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, output it as the current total cooling rate data, compare the current total cooling rate data with the preset ideal total cooling rate data, and output the first comparison result.

[0070] Step S5, according to the first comparison result, obtain the first temperature data and the second temperature data corresponding to the same temperature area in the first area temperature set and the second area temperature set, calculate the cooling rate, output it as the current area cooling rate data, establish the correspondence between the current area cooling rate data and the corresponding temperature area, output it as a cooling rate set, compare the current area cooling rate data in the cooling rate set with the preset ideal area cooling rate data, and output a second comparison result.

[0071] Step S6, inputting the second comparison result into a preset adjustment control comparison set, wherein the adjustment control comparison set includes the temperature zone, the corresponding adjustable fan position and the adjustable fan angle, obtaining the adjustment parameter signal and inputting it into the fan control terminal.

[0072] The step S1 includes the following sub-steps:

[0073] Step S101, dividing the temperature areas of the computer host and outputting them as a defined area set, wherein the names of the temperature areas in the defined area set include CPU, GPU, memory module, hard disk drive and power supply unit.

[0074] Step S101 clearly divides and names the temperature areas of the computer host and outputs them as a defined area set, establishing a framework for internal temperature monitoring of the computer host so that subsequent temperature data collection and analysis can be carried out in a targeted manner. By clearly naming each temperature area, temperature problems in different areas can be easily identified and handled, thereby improving the accuracy and efficiency of monitoring.

[0075] Step S102, collect data for the defined area set, obtain the temperature of each temperature area in the defined area set, output it as first temperature data, establish a first corresponding relationship between each temperature area and the first temperature data, and output it as a first area temperature set.

[0076] Step S102 collects the defined area set once, obtains the temperature data of each temperature area, and establishes the corresponding relationship between the temperature area and the temperature data, and outputs it as the first area temperature set, which actually obtains the temperature data of each key temperature area of ​​the computer host at present, and provides a direct basis for subsequent temperature analysis and early warning. By establishing the corresponding relationship between the temperature area and the temperature data, it is convenient to track and compare the temperature changes at different time points, and timely discover and deal with temperature abnormalities.

[0077] Step S1 systematically manages and collects data on key temperature areas of the computer host. By clearly dividing and naming each temperature area and collecting temperature data of these areas, step S1 provides basic data support for subsequent monitoring, analysis and fault warning, which helps to timely discover and deal with potential overheating problems and ensure the stable operation of the computer host.

[0078] The step S2 includes the following sub-steps:

[0079] Step S201, define global target temperature data and establish a dynamic temperature weighted model. The logic of the dynamic temperature weighted model is:

[0080] Receive the regional temperature set and calculate the weighted average temperature data according to the regional weight, where the regional weight is:

[0081] CPU: 0.4, GPU: 0.3, Memory module: 0.15, Hard drive: 0.1, Power supply unit: 0.05.

[0082] The mathematical expression of weighted average temperature data is:

[0083] T avg =W 1 ×T 1 +W 2 ×T 2 +W 3 ×T 3 +W 4 ×T 4 +W 5 ×T 5

[0084] Among them, T avg is the weighted average temperature data, W 1 is the regional weight corresponding to the temperature region CPU, T 1is the first temperature data corresponding to the temperature zone CPU, W 2 is the regional weight corresponding to the temperature region GPU, T 2 is the first temperature data corresponding to the temperature area GPU, W 3 is the regional weight corresponding to the temperature region memory module, T 3 is the first temperature data corresponding to the temperature region memory module, W 4 is the regional weight corresponding to the hard disk drive in the temperature region, T 4 is the first temperature data corresponding to the temperature zone hard disk drive, W 5 is the regional weight corresponding to the temperature regional power supply unit, T 5 The first temperature data corresponding to the temperature zone power supply unit.

[0085] The difference between the weighted average temperature data and the global target temperature data is calculated and output as first difference data.

[0086] If the first difference data is within the preset first threshold range or is smaller than the preset first threshold range, no global fan control signal is output.

[0087] If the first difference data is within a preset second threshold interval, the output global fan control signal is the first wind speed data and the first wind volume data.

[0088] If the first difference data is within the preset third threshold interval, the output global fan control signal is the second wind speed data and the second wind volume data.

[0089] If the first difference data is greater than a preset second threshold range, a fan failure warning signal is output.

[0090] Step S201 defines the global target temperature data and establishes a dynamic temperature weighted model, which receives the regional temperature set and calculates the weighted average temperature according to the preset regional weights. These weights reflect the relative importance of different regions to the overall temperature. Next, the model calculates the difference between the weighted average temperature and the global target temperature, and outputs different fan control signals according to the size of this difference. Accurate monitoring and intelligent adjustment of the computer host temperature is achieved. Through the dynamic temperature weighted model, the temperature conditions of each key area can be comprehensively considered, and the operating status of the fan can be adjusted according to the actual situation to keep the host running within the optimal temperature range.

[0091] The step S2 also includes a step S202, inputting the first area temperature set into a dynamic temperature weighted model, obtaining a fan control signal and weighted average temperature data, and outputting a global fan control signal and first weighted average temperature data.

[0092] Step S202 inputs the first area temperature set into the dynamic temperature weighted model, obtains the fan control signal and the weighted average temperature data, and outputs the global fan control signal and the first weighted average temperature data, combining the theoretical model with the actual operation, and obtaining the corresponding fan control signal and the weighted average temperature data by inputting the actual temperature data, thereby realizing the real-time monitoring and intelligent adjustment of the computer host temperature. By continuously inputting new temperature data and obtaining the corresponding fan control signal, the operating state of the fan can be adjusted in real time to adapt to the changes in the host temperature. At the same time, the output weighted average temperature data also provides the system administrator with intuitive information about the host temperature status, which helps to timely discover and deal with potential overheating problems.

[0093] Step S2 defines a global target temperature data and uses a dynamic temperature weighted model to calculate the weighted average temperature of each key area inside the computer host, and then intelligently controls the operating status of the fan according to the difference between the weighted average temperature and the global target temperature, thereby achieving precise monitoring and intelligent adjustment of the computer host temperature, helping to keep the host running within the optimal temperature range, extending the hardware life, and improving system stability.

[0094] The step S3 includes the following sub-steps:

[0095] Step S301, inputting a global fan control signal to a fan control terminal for a preset time interval.

[0096] Step S301 inputs the global fan control signal to the fan control end and continues for a preset time interval to ensure that the fan control system can receive and respond to the global fan control signal, while giving enough time for the fan to adjust its working state according to the control signal. The preset time interval is to ensure that the fan has enough time to respond to the control signal and produce observable temperature changes.

[0097] Step S302, after a time interval, perform secondary collection on the defined area set, obtain the temperature of each temperature area in the defined area set, output as second temperature data, establish a second corresponding relationship between each temperature area and the second temperature data, and output as a second area temperature set.

[0098] Step S302 performs secondary sampling on the defined area set after a time interval, obtains the temperature of each temperature area, and outputs it as second temperature data. At the same time, a second corresponding relationship between each temperature area and the second temperature data is established, and the second area temperature set is output. By re-collecting the temperature data, the effect of the fan control signal is evaluated to determine whether the fan control system effectively adjusts the temperature of each temperature area. The establishment of the second area temperature set provides a basis for subsequent temperature data analysis and adjustment of the fan control strategy.

[0099] Step S3 verifies the effect of the global fan control signal after application. By re-collecting the temperature data of the defined area set, it is evaluated whether the fan control signal effectively adjusts the temperature of each temperature area, which helps to ensure that the fan control system can be accurately adjusted according to actual needs, thereby achieving the purpose of optimizing heat dissipation and improving system stability.

[0100] The step S4 includes the following sub-steps:

[0101] Step S401, inputting the second region temperature set into the dynamic temperature weighted average model, obtaining weighted average temperature data, and outputting the second weighted average temperature data.

[0102] Step S401 inputs the second zone temperature set into the dynamic temperature weighted average model to obtain weighted average temperature data, and outputs it as second weighted average temperature data. By means of weighted average method, the temperature data of multiple temperature zones are integrated into a representative temperature value so as to more intuitively reflect the overall temperature state of the system. The dynamic temperature weighted average model can dynamically calculate the weighted average temperature according to the weight of each temperature zone and the real-time temperature data, thus providing a basis for the subsequent calculation of the cooling rate.

[0103] Step S402, calculating the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, the mathematical expression is:

[0104]

[0105] Among them, v d1 is the total cooling rate, T avg1 is the first weighted average temperature data, T avg2 is the second weighted average temperature data, and t is the time interval.

[0106] The output is the current total cooling speed data.

[0107] Step S402 calculates the total cooling rate based on the first weighted average temperature data, the second weighted average temperature and the time interval, and outputs it as the current total cooling rate data. The cooling effect of the system is quantified by comparing the weighted average temperatures of the initial state and the current state, as well as the time interval between them. The calculation of the total cooling rate helps to evaluate the performance and efficiency of the fan control system and provide a basis for subsequent judgments.

[0108] Step S403, comparing the current total cooling rate data with the preset ideal total cooling rate data.

[0109] If the current total cooling rate data is less than the ideal cooling rate data, it is determined to be a local temperature adjustment.

[0110] If the current total cooling rate data is greater than or equal to the ideal cooling rate data, it is determined that no local temperature adjustment is required.

[0111] The output is a first comparison result, wherein the first comparison result includes performing local temperature adjustment and not requiring local temperature adjustment.

[0112] Step S403 compares the current total cooling speed data with the preset ideal total cooling speed data, and determines whether local temperature adjustment is needed based on the comparison result. If the current total cooling speed data is less than the ideal cooling speed data, it means that the cooling effect of the system has not met expectations. In this case, it is necessary to determine that local temperature adjustment is needed to further reduce the temperature. If the current total cooling speed data is greater than or equal to the ideal cooling speed data, it means that the cooling effect of the system has met or exceeded expectations. In this case, it is determined that local temperature adjustment is not needed to avoid unnecessary energy consumption and noise, which provides an important basis for subsequent fan control strategy adjustments.

[0113] Step S4 determines whether a local temperature adjustment operation is required by comparing the actual cooling effect with the preset ideal cooling effect, which helps to ensure that the system can avoid unnecessary energy consumption and noise while ensuring heat dissipation efficiency.

[0114] The step S5 includes the following sub-steps:

[0115] Step S501, obtaining a first comparison result. If the first comparison result is to perform local temperature adjustment, obtaining first temperature data and second temperature data corresponding to the same temperature area in the first area temperature set and the second area temperature set, and calculating the regional cooling rate. The mathematical expression is:

[0116]

[0117] Among them, v d2 is the regional cooling rate, T minus1 is any first temperature data in the first region temperature set, T minus2 It is the second temperature data of the same temperature region as the first temperature data in the second region temperature set.

[0118] The output is the cooling rate data of the current area.

[0119] The effect of step S501 is to obtain the first comparison result, and determine whether local temperature adjustment is required based on the result. If local temperature adjustment is required, the first temperature data and the second temperature data corresponding to the same temperature area in the first area temperature set (initial temperature data) and the second area temperature set (temperature data after fan control) are further obtained. By calculating the temperature changes of these temperature areas before and after fan control, the regional cooling speed is obtained and output as the current regional cooling speed data. This step provides basic data for subsequent cooling speed comparison.

[0120] The step S5 further comprises the following sub-steps:

[0121] Step S502, establishing a corresponding relationship between the current region cooling rate data and the corresponding temperature region, and outputting it as a cooling rate set.

[0122] Step S502 establishes a correspondence between the cooling speed data of the current area and the corresponding temperature area, and outputs it as a cooling speed set, so as to organize and classify the cooling speeds of each temperature area, so as to facilitate subsequent rapid data analysis and comparison. The establishment of the cooling speed set helps the system to more intuitively understand the cooling conditions of each area and provide a basis for formulating targeted fan control strategies.

[0123] Step S503, compare the current area cooling speed data in the cooling speed set with the preset ideal area cooling speed data, and output a second comparison result, which is the current area cooling speed data lower than the ideal area cooling speed data and the corresponding temperature area.

[0124] Step S503 compares the cooling speed data of the current area in the cooling speed concentration with the preset ideal area cooling speed data, and outputs a second comparison result to identify which areas have cooling speeds lower than the ideal value, thereby determining the fan control strategy that needs to be adjusted. The second comparison result includes the cooling speed data of the current area that is lower than the ideal area cooling speed data and the corresponding temperature area. This information provides important basis for subsequent adjustment and optimization of the system.

[0125] In step S5, when local temperature adjustment is required, the cooling rates of various temperature zones are compared to identify which zones have cooling rates lower than the ideal value, thereby determining the fan control strategy that needs to be adjusted. This helps ensure that the system can accurately control the temperature of specific zones while maintaining overall heat dissipation efficiency.

[0126] The step S6 includes the following sub-steps:

[0127] Step S601, input the second comparison result into a preset adjustment control comparison set, wherein the adjustment control comparison set includes a temperature zone, a corresponding adjustable fan position and an adjustable fan angle, obtain the adjustable fan position and the adjustable fan angle corresponding to the temperature zone that is the same as the temperature zone in the second comparison result, establish a third corresponding relationship between the temperature zone, the adjustable fan position and the adjustable fan angle, and output it as an adjustment parameter signal.

[0128] Step S601 inputs the second comparison result into a preset adjustment control comparison set, which includes information on temperature zones, corresponding adjustable fan positions, and adjustable fan angles. By matching the temperature zones with the same temperature zones in the second comparison result, the corresponding adjustable fan positions and adjustable fan angles can be obtained, and a third correspondence between the temperature zones, the adjustable fan positions, and the adjustable fan angles is established. An adjustment parameter signal is output, providing specific control parameters for subsequent fan regulation, thereby ensuring that the fan can be precisely regulated as expected.

[0129] Step S602: inputting the adjustment parameter signal to the fan control terminal to adjust the fan.

[0130] Step S602 inputs the adjustment parameter signal to the fan control end to achieve precise control of the fan. By adjusting the position and angle of the fan, the air supply direction and intensity of the fan can be changed, thereby achieving precise heat dissipation in a specific temperature area. The fan can be flexibly controlled according to actual needs, thereby improving the heat dissipation efficiency and stability of the system.

[0131] Step S6 determines the fan position and angle that need to be adjusted based on the second comparison result through a preset adjustment control reference set, and outputs an adjustment parameter signal to control the fan for precise regulation, which helps to ensure that the system maintains overall heat dissipation efficiency while performing precise temperature control for specific areas, thereby improving the stability and reliability of the system.

[0132] This system can accurately grasp the temperature distribution inside the device by dividing the temperature area of ​​the computer host and collecting the temperature data of each area in real time. Through the dynamic temperature weighted model, the weighted average temperature is calculated according to the temperature weight of each area, and compared with the global target temperature, so as to intelligently adjust the speed and angle of the fan to achieve accurate heat dissipation in different areas, significantly improve the heat dissipation efficiency, and reduce the overall temperature inside the device. Traditional fixed speed fans are often difficult to solve the problem of uneven heat dissipation. This system can accurately adjust the heat dissipation requirements of different areas by intelligently adjusting the speed and angle of the fan, thereby avoiding the phenomenon of excessive local temperature, which helps to protect sensitive components inside the device and extend the service life of the device. Since this system can achieve accurate heat dissipation of different components inside the device, it can significantly reduce the performance degradation and stability problems caused by excessive temperature of the device, which helps to improve the overall performance and stability of the device, thereby ensuring the normal operation of the device under high load. By intelligently adjusting the speed and angle of the fan, this system can flexibly adjust the heat dissipation power according to the temperature distribution inside the device, avoiding unnecessary energy waste, which not only helps to reduce the operating cost of the equipment, but also conforms to the current development trend of green and energy saving.

[0133] Example 2, reference Figure 2 , provides a computer cooling fan intelligent adjustment system, which is applied to any of the computer cooling fan intelligent adjustment methods described above, including a primary acquisition module, a temperature weighted module, a secondary acquisition module, a first comparison module, a second comparison module and a regional control module.

[0134] A primary acquisition module is used to define the temperature area of ​​the computer host, and the output is a defined area set. The defined area set is collected once to obtain the temperature of each temperature area in the defined area set, and the output is the first temperature data. A first corresponding relationship between each temperature area and the first temperature data is established, and the output is the first area temperature set.

[0135] The primary acquisition module is mainly responsible for defining the temperature zones of the computer host and collecting initial temperature data for these zones. By establishing a first correspondence between each temperature zone and the first temperature data, the first zone temperature set is output, providing basic data for subsequent temperature weighting, fan control and effect evaluation, ensuring that the initial temperature status of the computer host can be accurately understood.

[0136] The temperature weighting module is used to define global target temperature data, establish a dynamic temperature weighting model, input the first area temperature set into the dynamic temperature weighting model, and obtain a global fan control signal and a first weighted average temperature data.

[0137] The temperature weighted module defines the global target temperature data and establishes a dynamic temperature weighted model. The first area temperature set is input into the model, and the global fan control signal and the first weighted average temperature data are calculated. According to the initial temperature data, the global fan control strategy is obtained through dynamic weighting, which provides a basis for the preliminary adjustment of the fan.

[0138] The secondary acquisition module is used to input the global fan control signal to the fan control end, and after a preset time interval, perform secondary acquisition on the defined area set, obtain the temperature of each temperature area in the defined area set, output it as second temperature data, establish a second corresponding relationship between each temperature area and the second temperature data, and output it as a second area temperature set.

[0139] After the global fan control signal is input, the secondary acquisition module collects temperature data for the defined area set again after a preset time interval, establishes a second corresponding relationship between each temperature area and the second temperature data, outputs the second area temperature set, evaluates the actual effect of the fan control signal, and provides data support for the subsequent total cooling speed calculation and local temperature adjustment judgment.

[0140] The first comparison module is used to input the second area temperature set into the dynamic temperature weighted average model, obtain the second weighted average temperature data, calculate the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, and output the current total cooling rate data, compare the current total cooling rate data with the preset ideal total cooling rate data, and output the first comparison result.

[0141] The first comparison module inputs the second area temperature set into the dynamic temperature weighted average model again to calculate the second weighted average temperature data, then calculates the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, and compares it with the preset ideal total cooling rate data, outputs the first comparison result, evaluates the cooling effect of the fan control system as a whole, and provides a basis for judging whether local temperature adjustment is needed later.

[0142] The second comparison module is used to obtain the first temperature data and the second temperature data corresponding to the same temperature area in the first area temperature set and the second area temperature set according to the first comparison result, calculate the cooling rate, output it as the current area cooling rate data, establish the corresponding relationship between the current area cooling rate data and the corresponding temperature area, output it as a cooling rate set, compare the current area cooling rate data in the cooling rate set with the preset ideal area cooling rate data, and output a second comparison result.

[0143] Based on the first comparison result, the second comparison module further analyzes the temperature areas that require local temperature adjustment, calculates the cooling speed of the same temperature areas in the first area temperature set and the second area temperature set, establishes a cooling speed set, and compares it with the preset ideal area cooling speed data, outputs the second comparison result, identifies the temperature areas with insufficient cooling speed, and provides specific adjustment targets for subsequent precise fan control.

[0144] The regional control module is used to input the second comparison result into a preset adjustment control comparison set, which includes temperature zones, corresponding adjustable fan positions and adjustable fan angles, obtain an adjustment parameter signal and input it into the fan control terminal.

[0145] The regional control module inputs the second comparison result into the preset adjustment control comparison set, obtains the adjustment parameter signal based on the information in the comparison set, and inputs it into the fan control end. According to the specific cooling requirements, the position and angle of the fan are precisely controlled, thereby achieving precise adjustment of the computer host temperature and improving the heat dissipation efficiency and stability.

[0146] It should be understood by those skilled in the art that the embodiments of the present invention can be provided as methods, systems or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1A function specified in one or more boxes.

[0147] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A computer cooling fan intelligent adjustment method, characterized in that: The steps include: Step S1, dividing the temperature area of ​​the computer host and outputting it as a defined area set, collecting the defined area set once, obtaining the temperature of each temperature area in the defined area set, outputting it as first temperature data, establishing a first corresponding relationship between each temperature area and the first temperature data, and outputting it as a first area temperature set; Step S2, defining global target temperature data, establishing a dynamic temperature weighted model, inputting the first area temperature set into the dynamic temperature weighted model, and obtaining a global fan control signal and a first weighted average temperature data; Step S3, inputting the global fan control signal to the fan control terminal, performing secondary collection on the defined area set after a preset time interval, obtaining the temperature of each temperature area in the defined area set, outputting it as second temperature data, establishing a second corresponding relationship between each temperature area and the second temperature data, and outputting it as a second area temperature set; Step S4, inputting the second area temperature set into the dynamic temperature weighted average model, obtaining the second weighted average temperature data, calculating the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, outputting the current total cooling rate data, comparing the current total cooling rate data with the preset ideal total cooling rate data, and outputting the first comparison result; Step S5, obtaining the first temperature data and the second temperature data corresponding to the same temperature area in the first area temperature set and the second area temperature set according to the first comparison result, calculating the cooling speed, outputting it as the current area cooling speed data, establishing a corresponding relationship between the current area cooling speed data and the corresponding temperature area, outputting it as a cooling speed set, comparing the current area cooling speed data in the cooling speed set with the preset ideal area cooling speed data, and outputting a second comparison result; Step S6, inputting the second comparison result into a preset adjustment control comparison set, wherein the adjustment control comparison set includes the temperature zone, the corresponding adjustable fan position and the adjustable fan angle, obtaining the adjustment parameter signal and inputting it into the fan control terminal.

2. A computer cooling fan intelligent adjustment method as claimed in claim 1, characterized in that: The step S1 includes the following sub-steps: Step S101, dividing the temperature regions of the computer host and outputting them as a defined region set, wherein the names of the temperature regions in the defined region set include CPU, GPU, memory module, hard disk drive and power supply unit; Step S102, collect data for the defined area set, obtain the temperature of each temperature area in the defined area set, output it as first temperature data, establish a first corresponding relationship between each temperature area and the first temperature data, and output it as a first area temperature set.

3. A computer cooling fan intelligent adjustment method as claimed in claim 2, characterized in that: The step S2 includes the following sub-steps: Step S201, define global target temperature data and establish a dynamic temperature weighted model. The logic of the dynamic temperature weighted model is: Receive the regional temperature set and calculate the weighted average temperature data according to the regional weight, where the regional weight is: CPU: 0.4, GPU: 0.3, memory module: 0.15, hard disk drive: 0.1, power supply unit: 0.05; The mathematical expression of weighted average temperature data is: T avg =W1×T1+W2×T2+W3×T3+W4×T4+W5×T5 Among them, T avg为 Weighted average temperature data, W1 is the regional weight corresponding to the temperature zone CPU, T1 is the first temperature data corresponding to the temperature zone CPU, W2 is the regional weight corresponding to the temperature zone GPU, T2 is the first temperature data corresponding to the temperature zone GPU, W3 is the regional weight corresponding to the temperature zone memory module, T3 is the first temperature data corresponding to the temperature zone memory module, W4 is the regional weight corresponding to the temperature zone hard disk drive, T4 is the first temperature data corresponding to the temperature zone hard disk drive, W5 is the regional weight corresponding to the temperature zone power supply unit, T5 is the first temperature data corresponding to the temperature zone power supply unit; Calculate the difference between the weighted average temperature data and the global target temperature data, and output it as first difference data; If the first difference data is within the preset first threshold interval or is smaller than the preset first threshold interval, no global fan control signal is output; If the first difference data is within the preset second threshold interval, the global fan control signal is output as the first wind speed data and the first wind volume data; If the first difference data is within a preset third threshold interval, the global fan control signal is output as the second wind speed data and the second wind volume data; If the first difference data is greater than a preset second threshold range, a fan failure warning signal is output.

4. A computer cooling fan intelligent adjustment method as claimed in claim 3, characterized in that: The step S2 also includes a step S202, inputting the first area temperature set into a dynamic temperature weighted model, obtaining a fan control signal and weighted average temperature data, and outputting a global fan control signal and first weighted average temperature data.

5. A computer cooling fan intelligent adjustment method as claimed in claim 4, characterized in that: The step S3 includes the following sub-steps: Step S301, inputting a global fan control signal to a fan control terminal for a preset time interval; Step S302, after a time interval, perform secondary collection on the defined area set, obtain the temperature of each temperature area in the defined area set, output as second temperature data, establish a second corresponding relationship between each temperature area and the second temperature data, and output as a second area temperature set.

6. A computer cooling fan intelligent adjustment method as claimed in claim 5, characterized in that: The step S4 includes the following sub-steps: Step S401, inputting the second region temperature set into a dynamic temperature weighted average model, obtaining weighted average temperature data, and outputting the data as second weighted average temperature data; Step S402, calculating the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, the mathematical expression is: Among them, v d1 is the total cooling rate, T avg1 is the first weighted average temperature data, T avg2 is the second weighted average temperature data, t is the time interval; The output is the current total cooling speed data; Step S403, comparing the current total cooling rate data with the preset ideal total cooling rate data; If the current total cooling rate data is less than the ideal cooling rate data, it is determined to be a local temperature adjustment; If the current total cooling rate data is greater than or equal to the ideal cooling rate data, it is determined that no local temperature adjustment is required; The output is a first comparison result, wherein the first comparison result includes performing local temperature adjustment and not requiring local temperature adjustment.

7. A computer cooling fan intelligent adjustment method as claimed in claim 6, characterized in that: The step S5 comprises the following sub-steps: Step S501, obtaining a first comparison result. If the first comparison result is to perform local temperature adjustment, obtaining first temperature data and second temperature data corresponding to the same temperature area in the first area temperature set and the second area temperature set, and calculating the regional cooling rate. The mathematical expression is: Among them, v d2 is the regional cooling rate, T minus1 is any first temperature data in the first region temperature set, T minus2 The second temperature data of the same temperature region as the first temperature data in the second region temperature set; The output is the cooling rate data of the current area.

8. A computer cooling fan intelligent adjustment method as claimed in claim 7, characterized in that: The step S5 further comprises the following sub-steps: Step S502, establishing a corresponding relationship between the current region cooling rate data and the corresponding temperature region, and outputting it as a cooling rate set; Step S503, compare the current area cooling speed data in the cooling speed set with the preset ideal area cooling speed data, and output a second comparison result, which is the current area cooling speed data lower than the ideal area cooling speed data and the corresponding temperature area.

9. A computer cooling fan intelligent adjustment method as claimed in claim 8, characterized in that: The step S6 comprises the following sub-steps: Step S601, inputting the second comparison result into a preset adjustment control comparison set, wherein the adjustment control comparison set includes a temperature zone, a corresponding adjustable fan position, and an adjustable fan angle, obtaining an adjustable fan position and an adjustable fan angle corresponding to a temperature zone that is the same as the temperature zone in the second comparison result, establishing a third corresponding relationship between the temperature zone, the adjustable fan position, and the adjustable fan angle, and outputting the third corresponding relationship as an adjustment parameter signal; Step S602: inputting the adjustment parameter signal to the fan control terminal to adjust the fan.

10. A computer cooling fan intelligent adjustment system, which is applied to a computer cooling fan intelligent adjustment method as claimed in any one of claims 1 to 9, characterized in that: It includes a primary acquisition module, a temperature weighting module, a secondary acquisition module, a first comparison module, a second comparison module and a regional control module; The primary acquisition module is used to define the temperature area of ​​the computer host, output as a defined area set, perform a primary acquisition on the defined area set, obtain the temperature of each temperature area in the defined area set, output as first temperature data, establish a first corresponding relationship between each temperature area and the first temperature data, and output as a first area temperature set; The temperature weighting module is used to define global target temperature data, establish a dynamic temperature weighting model, input the first area temperature set into the dynamic temperature weighting model, and obtain a global fan control signal and a first weighted average temperature data; The secondary acquisition module is used to input the global fan control signal to the fan control end, and after a preset time interval, perform secondary acquisition on the defined area set to obtain the temperature of each temperature area in the defined area set, output as second temperature data, establish a second corresponding relationship between each temperature area and the second temperature data, and output as a second area temperature set; The first comparison module is used to input the second area temperature set into the dynamic temperature weighted average model, obtain the second weighted average temperature data, calculate the total cooling rate based on the first weighted average temperature data, the second weighted average temperature data and the time interval, output the current total cooling rate data, compare the current total cooling rate data with the preset ideal total cooling rate data, and output the first comparison result; The second comparison module is used to obtain the first temperature data and the second temperature data corresponding to the same temperature area in the first area temperature set and the second area temperature set according to the first comparison result, calculate the cooling speed, output as the current area cooling speed data, establish the corresponding relationship between the current area cooling speed data and the corresponding temperature area, output as the cooling speed set, compare the current area cooling speed data in the cooling speed set with the preset ideal area cooling speed data, and output the second comparison result; The regional control module is used to input the second comparison result into a preset adjustment control comparison set, which includes temperature zones, corresponding adjustable fan positions and adjustable fan angles, obtain an adjustment parameter signal and input it into the fan control terminal.

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