A method and device for intelligent linkage control of a metal heat sink and a fan

Abstract

The present invention discloses a method and device for intelligent linkage control of a metal heat sink and a fan, relating to the technical field of intelligent control. The method includes: connecting a temperature monitoring device to obtain the monitored temperature of the metal heat sink; constructing a three-dimensional coordinate of the metal heat sink, performing three-dimensional coordinate position fitting to determine the heat distribution of the heat sink; analyzing the heat dissipation circulation demand according to the heat distribution of the heat sink to determine the circulation demand distribution; establishing a control relationship between the fan control parameters and the heat dissipation circulation; taking the circulation demand distribution as the target, searching for the control parameters according to the control relationship to determine the fan control strategy, and the fan control strategy is used for the intelligent linkage control of the fan. It solves the technical problem in the prior art that the heat dissipation efficiency between the heat sink and the fan is mismatched and cannot be intelligently adjusted according to the real-time heat, resulting in poor heat dissipation effect. By real-time monitoring the temperature distribution of the heat sink and intelligently adjusting the fan control strategy, the technical effects of improving the heat dissipation efficiency and reducing the energy consumption are achieved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to a method and device for intelligent linkage control of a metal heat sink and a fan. Background Art

[0002] In today's era of rapid development of electronics and information technology, the integration and computing power of high-performance electronic devices such as servers, data centers, high-end workstations, and various consumer electronic products are constantly improving, and with it comes increasingly severe heat dissipation challenges. These devices generate a lot of heat during operation. If they cannot be dissipated in a timely and effective manner, it will not only affect the performance stability of the equipment, but may also shorten its service life and even cause safety hazards. Traditional heat dissipation methods often rely on passive heat dissipation of metal heat sinks or fixed fan systems, which cannot be flexibly adjusted according to the actual heat distribution of the equipment during operation. This "one-size-fits-all" heat dissipation strategy often leads to excessive heat dissipation in some areas and insufficient heat dissipation in other areas, which wastes energy and fails to achieve the best heat dissipation effect. Summary of the invention

[0003] The present application provides a method and device for intelligent linkage control of a metal heat sink and a fan, which solves the technical problem in the prior art that the heat dissipation efficiency between the heat sink and the fan is not matched, and intelligent adjustment cannot be performed according to real-time heat, resulting in poor heat dissipation effect.

[0004] In view of the above problems, the present application provides a method and device for intelligent linkage control of a metal heat sink and a fan.

[0005] A first aspect of the present application provides a method for intelligent linkage control of a metal heat sink and a fan, the method comprising:

[0006] Connect a temperature monitoring device to obtain a metal heat sink monitoring temperature, wherein the metal heat sink monitoring temperature has a heat sink distribution position identifier; construct a three-dimensional coordinate of the metal heat sink, perform three-dimensional coordinate position fitting according to the heat sink distribution position identifier, and determine the heat sink heat distribution; perform heat dissipation circulation demand analysis according to the heat sink heat distribution, and determine the circulation demand distribution; establish a control relationship between fan control parameters and heat dissipation circulation; take the circulation demand distribution as a target, perform a control parameter search according to the control relationship, and determine a fan control strategy, wherein the fan control strategy is used for intelligent linkage control of the fan.

[0007] A second aspect of the present application provides a metal heat sink and fan intelligent linkage control device, the device comprising:

[0008] A temperature monitoring module, which is used to connect to a temperature monitoring device to obtain the monitored temperature of the metal heat sink, and the monitored temperature of the metal heat sink has an identification of the heat sink distribution position; a fitting module, which is used to construct the three-dimensional coordinates of the metal heat sink and perform three-dimensional coordinate position fitting according to the identification of the heat sink distribution position to determine the heat distribution of the heat sink; a demand analysis module, which is used to perform heat dissipation circulation demand analysis according to the heat distribution of the heat sink to determine the distribution of circulation demands; a control relationship establishment module, which is used to establish the control relationship between the fan control parameters and the heat dissipation circulation; a control module, which is used to target the distribution of circulation demands and search for control parameters according to the control relationship to determine the fan control strategy, and the fan control strategy is used for intelligent linkage control of the fan.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] First, connect to the temperature monitoring device to obtain the monitored temperature of the metal heat sink, and the monitored temperature of the metal heat sink has an identification of the heat sink distribution position. Next, construct the three-dimensional coordinates of the metal heat sink and perform three-dimensional coordinate position fitting according to the identification of the heat sink distribution position to determine the heat distribution of the heat sink. Further, perform heat dissipation circulation demand analysis according to the heat distribution of the heat sink to determine the distribution of circulation demands. Then, establish the control relationship between the fan control parameters and the heat dissipation circulation. Finally, target the distribution of circulation demands and search for control parameters according to the control relationship to determine the fan control strategy, and the fan control strategy is used for intelligent linkage control of the fan. This solves the technical problem in the prior art that the heat dissipation efficiency between the heat sink and the fan does not match and cannot be intelligently adjusted according to the real-time heat, resulting in poor heat dissipation effect. By real-time monitoring the temperature distribution of the heat sink and intelligently adjusting the fan control strategy, the technical effects of improving the heat dissipation efficiency and reducing the energy consumption are achieved. Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0012] Figure 1 It is a schematic flow chart of a method for intelligent linkage control of a metal heat sink and a fan provided by an embodiment of this application;

[0013] Figure 2 It is a schematic structural diagram of a device for intelligent linkage control of a metal heat sink and a fan provided by an embodiment of this application.

[0014] Description of the drawing reference numerals: Temperature monitoring module 11, fitting module 12, demand analysis module 13, control relationship establishment module 14, control module 15. Detailed implementation manners

[0015] The present application provides a method and device for intelligent linkage control of a metal heat sink and a fan, and solves the technical problem in the prior art that the heat dissipation efficiency between the heat sink and the fan does not match, and it is impossible to perform intelligent adjustment according to real-time heat, resulting in poor heat dissipation effect.

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0017] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server including a series of steps or units is not necessarily limited to those clearly listed steps or units, but may include other steps or modules not clearly listed or inherent to these processes, methods, products or devices.

[0018] Embodiment 1, as Figure 1 shown, the present application provides a method for intelligent linkage control of a metal heat sink and a fan, wherein the method includes:

[0019] Connect a temperature monitoring device to obtain the monitored temperature of the metal heat sink, and the monitored temperature of the metal heat sink has a heat sink distribution position identifier.

[0020] By connecting a temperature monitoring device (such as a temperature sensor), the monitored temperature of each point on the metal heat sink is obtained in real time, and each monitored temperature point is attached with a heat sink distribution position identifier so as to accurately identify its spatial position in subsequent processing.

[0021] Furthermore, before connecting the temperature monitoring device, it includes:

[0022] Identifying the key areas of the heat sink based on the historical monitoring samples of the heat sink, including the heat source contact area, the center of the heat sink, and the edge of the heat sink; performing regional clustering according to the distribution distance of the key areas and the historical heat distribution to obtain the monitored point distribution information, and the monitored point distribution information is a sensor layout strategy to ensure that the measuring range of the temperature sensor distribution covers all temperature clustering areas; obtaining the temperature change frequency of the key areas to determine the monitoring response time; setting the temperature sensor based on the monitoring response time and the monitored point distribution information.

[0023] Specifically, based on the historical monitoring sample data of the heat sink, key areas on the heat sink are identified. These key areas typically include the heat source contact area (i.e., the part of the heat sink directly in contact with the heat source), the center of the heat sink (where heat is more concentrated), and the edge of the heat sink (where heat may be dissipated into the environment). According to the distribution distances of the key areas and the historical heat distribution data, cluster analysis is performed on these areas to group regions with similar heat distribution characteristics into the same set, so as to set reasonable monitoring points within each group of regions. Through regional clustering, the distribution information of the monitoring points can be obtained, that is, how many temperature sensors should be set in each clustering region and the approximate positions of these sensors. By obtaining the temperature change rate of the key areas, the monitoring response time is determined. Areas with a high temperature change frequency require a faster monitoring response speed to ensure timely capture of temperature changes. Based on these frequency data, appropriate monitoring response times can be set for different regions to ensure that the temperature sensors can respond quickly and accurately record temperature changes. Based on the monitoring response time, the monitoring point distribution information, and the actual situation of the heat sink (such as shape, size, material, etc.), the temperature sensors are set, including selecting a suitable sensor type (such as thermocouple, thermistor, etc.), determining the installation position of the sensor (ensuring that all temperature clustering regions can be covered), and setting parameters such as the sampling frequency and response time of the sensor.

[0024] Furthermore, connecting the temperature monitoring device to obtain the monitored temperature of the metal heat sink includes:

[0025] Obtaining the monitored temperature through the temperature monitoring device and locating the position of the temperature monitoring device; mapping the temperature clustering region according to the position of the temperature monitoring device; parsing the corresponding region of the heat sink according to the temperature clustering region, and establishing the heat sink distribution position identifier of the monitored temperature.

[0026] Real-time obtain the monitored temperature data on the metal heat sink through a temperature monitoring device. At the same time, use the built-in or additional positioning technology in the device (such as GPS, RFID tags, or a preset coordinate system) to accurately record the position information of each temperature monitoring device on the heat sink. In this way, each monitored temperature data point is associated with its specific position on the heat sink. According to the obtained positions of the temperature monitoring devices and their corresponding temperature data, methods such as K-means clustering and hierarchical clustering are used for temperature clustering analysis, that is, dividing the regions with similar temperature characteristics into a group to form temperature clustering regions. After clustering, each clustering region represents a heat sink region with specific temperature characteristics. According to the results of the temperature clustering regions, analyze and determine the corresponding physical regions on the heat sink, and assign a unique heat sink distribution position identifier to each temperature clustering region. This identifier can be a digital code based on a coordinate system, a combination of letters, or other forms of identifiers, which can clearly represent the specific position of each monitored temperature point on the heat sink. Associate each monitored temperature data point with its corresponding heat sink distribution position identifier to form a complete correspondence between the monitored temperature and the heat sink position.

[0027] Construct a three-dimensional coordinate of the metal heat sink, and perform three-dimensional coordinate position fitting according to the heat sink distribution position identifier to determine the heat distribution of the heat sink.

[0028] Construct a three-dimensional coordinate of the metal heat sink through modeling software. For example, the X and Y axes represent the horizontal plane of the heat sink (such as length and width), and the Z axis represents the height (or thickness). Convert each heat sink distribution position identifier into specific coordinates in the three-dimensional coordinate system, and associate the temperature data obtained by each temperature monitoring device with its corresponding three-dimensional coordinates, thereby determining the heat distribution of the heat sink.

[0029] Conduct an analysis of the heat dissipation circulation demand based on the heat distribution of the heat sink to determine the circulation demand distribution.

[0030] Conduct an analysis of the heat dissipation circulation demand based on the heat distribution of the heat sink, that is, evaluate the heat dissipation demands of different regions, that is, determine which regions need more air circulation to take away heat and which regions need relatively less, thereby determining the circulation demand distribution;

[0031] Furthermore, conduct an analysis of the heat dissipation circulation demand based on the heat distribution of the heat sink to determine the circulation demand distribution, including:

[0032] Identify the temperature gradient based on the heat distribution of the heat sink; obtain the fin characteristics of the heat sink, where the fin characteristics include shape, size, spacing, and direction, and analyze the heat dissipation path according to the fin characteristics; fit the natural path of heat flow of the heat sink according to the temperature gradient by means of hydrodynamics; use the heat dissipation path to perform flow direction intervention and correction on the natural path of heat flow to obtain the heat flow path; perform flow compensation on the heat flow path according to the heat distribution of the heat sink to obtain the distribution of the flow demand.

[0033] Specifically, based on the heat distribution of the heat sink, identify the temperature gradient on the heat sink. The temperature gradient refers to the rate of change of temperature in space and describes the trend of heat flowing from a high-temperature region to a low-temperature region. By calculating the temperature difference between adjacent monitoring points and combining their position information in a three-dimensional coordinate system, the direction and magnitude of the temperature gradient can be calculated; the fin characteristics of the heat sink include shape (such as straight, wavy, etc.), size (such as the height and width of the fins), spacing (the distance between adjacent fins), and direction (the direction of fin arrangement). Based on the obtained fin characteristics, analyze the heat dissipation path on the heat sink. The heat dissipation path refers to the path by which heat is transferred from the heat source to the heat sink and dissipated into the air through the fins; by analyzing factors such as the arrangement, spacing, and shape of the fins, the flow pattern of air in the heat sink can be predicted and the heat dissipation path can be determined; use the temperature gradient and the principles of hydrodynamics to fit the natural path of heat flow on the heat sink. Further, use the heat dissipation path to perform flow direction intervention and correction on the natural path of heat flow to obtain the heat flow path; according to the heat distribution of the heat sink and the heat flow path, compensate for the flow demand to obtain the distribution of the flow demand, including determining the required air flow rate, the rotation speed and power of the fan, etc. for each region. Through reasonable flow compensation, it can be ensured that each region on the heat sink can obtain sufficient air circulation, thereby achieving a balanced heat dissipation effect.

[0034] Furthermore, performing flow compensation on the heat flow path according to the heat distribution of the heat sink to obtain the distribution of the flow demand includes:

[0035] Calculate the total heat dissipation flow demand of the heat sink according to the heat distribution of the heat sink; perform operations on the heat dissipation heat flow on the path according to the heat flow path to determine the distribution path of the natural heat dissipation amount; establish the distribution coordinate relationship between the distribution path of the natural heat dissipation amount and the total heat dissipation flow demand of the heat sink according to the three-dimensional coordinates of the metal heat sink; determine the corresponding relationship between the total heat dissipation flow demand and the natural heat dissipation amount according to the distribution coordinate relationship, and perform difference calculation based on the corresponding relationship to obtain the distribution of the flow demand.

[0036] Preferably, according to the overall heat distribution of the heat sink, calculate the total heat dissipation flow demand of the heat sink. The total heat dissipation flow demand refers to the air flow volume required for heat dissipation of the heat sink. The neural network model can be trained by collecting data on the heat dissipation effect and the corresponding air flow volume of the heat sink under different conditions. After the training is completed, the model can calculate the total heat dissipation flow demand based on the heat distribution; according to the heat flow path, calculate the heat dissipation flow on the path to determine the distribution path of the natural heat dissipation amount; use the three-dimensional coordinates of the metal heat sink to correspond the distribution path of the natural heat dissipation amount to the physical position of the heat sink, that is, map the points on the heat flow path to the three-dimensional coordinate system, and then determine the corresponding relationship between the total heat dissipation flow demand and the natural heat dissipation amount on the heat sink; according to the corresponding relationship between the total heat dissipation flow demand and the natural heat dissipation amount, calculate the difference amount. The difference amount refers to the additional heat dissipation flow volume that needs to be provided to meet the total heat dissipation flow demand. By calculating the difference amount at each position, the distribution of the flow demand on the heat sink can be obtained.

[0037] Furthermore, obtaining the distribution of the flow demand further includes:

[0038] According to the fin characteristics of the heat sink, identify the flow dead zones and inefficient regions; according to the identification results of the flow dead zones and inefficient regions, locate the distribution of the flow demand and mark the flow dead zones and inefficient regions; according to the flow efficiency of the flow dead zones and inefficient regions, generate a flow demand forcing coefficient, which is used to increase the flow demand weight of the marked regions in the linkage control; add the flow demand forcing coefficient to the distribution of the flow demand according to the located position of the flow demand distribution.

[0039] Specifically, according to the fin characteristics of the heat sink, using fluid dynamics simulation or experimental data, identify the possible flow dead zones and inefficient regions in the heat sink. The flow dead zone refers to the area where air flow is difficult to reach or the speed is extremely low, while the inefficient region refers to the area where although air can flow, the heat dissipation efficiency is relatively low; according to the identification results of the flow dead zones and inefficient regions, mark the flow dead zones and inefficient regions in the three-dimensional coordinates of the heat sink; for the flow dead zones and inefficient regions, generate a flow demand forcing coefficient according to their flow efficiency (i.e., the comprehensive evaluation of air flow speed and heat dissipation effect). The flow demand forcing coefficient is a value greater than 1, which is used to increase the flow demand weight of these marked regions in the linkage control. By increasing the air flow volume in these regions, the heat dissipation effect can be improved and heat accumulation can be reduced; add the generated flow demand forcing coefficient to the original distribution of the flow demand according to the located position of the flow demand distribution. In this way, in the final distribution map of the flow demand, the flow dead zones and inefficient regions will have a higher flow demand weight, thereby improving the heat dissipation efficiency and the overall performance of the system.

[0040] Furthermore, according to the heat flow path, the heat dissipation heat flow on the path is calculated, including:

[0041] By using the natural heat dissipation formula: , the heat dissipation heat flow on the path is calculated to obtain the natural heat dissipation amount, where the natural heat dissipation amount, is the natural heat flux density, k is the thermal conductivity, is the temperature gradient at the three-dimensional coordinate position, is the infinitesimal area element on the path.

[0042] The natural heat dissipation formula: describes the calculation of the natural heat dissipation amount caused by the temperature gradient on a specific path. The natural heat dissipation amount on the path can be calculated using the natural heat dissipation formula, where the natural heat dissipation amount, is the natural heat flux density, k is the thermal conductivity, is the temperature gradient at the three-dimensional coordinate position, is the infinitesimal area element on the path.

[0043] Establish the control relationship between the fan control parameters and the heat dissipation flow.

[0044] By collecting the fan control parameters of the historical heat dissipation flow, the neural network model is trained to establish the control relationship between the fan control parameters and the heat dissipation flow. This control relationship defines how to change the intensity and direction of the air flow by adjusting the control parameters such as the rotation speed, angle, and number of fans turned on, so as to meet the heat dissipation requirements of different regions.

[0045] Taking the distribution of the flow demand as the target, according to the control relationship, the control parameters are searched to determine the fan control strategy, and the fan control strategy is used for the intelligent linkage control of the fan.

[0046] Taking the distribution of the flow demand as the target, according to the established control relationship, the control parameters are searched and optimized. Through this process, one or more optimal fan control strategies can be found, and these strategies can intelligently link and control the fan system, maximize the heat dissipation efficiency, and ensure the stable operation of the equipment and the reduction of energy consumption.

[0047] Furthermore, taking the distribution of the flow demand as the target, according to the control relationship, the control parameters are searched to determine the fan control strategy, including:

[0048] The control parameters include the fan angle and the air volume. Obtain the adjustment range of the fan angle and the adjustment range of the air volume. According to the adjustment range of the fan angle and the adjustment range of the air volume, set the angle grid and the air volume grid respectively, and generate a grid parameter space through the grid combination of all control parameters. Based on the circulation demand forcing coefficient, configure the distribution weights of each area of the circulation demand distribution, and construct a matching error function. Create an empty matrix to record the matching error of each parameter combination, traverse the parameter combinations according to the grid parameter space, perform error calculation based on the matching error function, and synchronously load the empty matrix using the error calculation results. When the target search requirement is completed, search for the minimum error control strategy based on the error matrix as the fan control strategy.

[0049] Preferably, the control parameters include the fan angle and the air volume, and the adjustment range of the fan angle refers to the adjustable range of the fan angle. For example, , , and the adjustment range of the air volume refers to the adjustable range of the fan air volume. For example, (cubic feet per minute), ; According to the adjustment range of the fan angle and the adjustment range of the air volume, set the angle grid and the air volume grid respectively. For example, generate an angle sequence from to : Generate an air volume sequence from to ; is the minimum angle, is the angle increment, is the maximum angle, is the minimum air volume, is the air volume increment, is the maximum air volume; Generate a grid parameter space through all possible combinations. For example, if has 10 values, If there are 20 values, there are a total of 200 combinations. Based on the circulation demand forced coefficient, allocate the weight values for each region of the circulation demand distribution; based on the circulation demand distribution and the heat dissipation effect under the current fan control parameters, construct a matching error function, which calculates the difference between the actual heat dissipation effect and the ideal heat dissipation demand. The smaller the difference, the smaller the matching error. Create an empty matrix to record the matching error corresponding to each grid parameter combination; traverse each parameter combination in the grid parameter space (i.e., each combination of fan angle and air volume); for each parameter combination, use the matching error function to calculate its corresponding matching error and store the result in the corresponding position in the empty matrix; when all grid parameter combinations have been traversed and the matching errors have been calculated, the empty matrix is completely filled to obtain the error matrix; search for the minimum error value in the error matrix, and the grid parameter combination corresponding to this value is the optimal fan control strategy. By systematically traversing all possible control parameter combinations and evaluating their impact on the heat dissipation effect, the optimal fan control strategy is found.

[0050] In summary, the embodiments of the present application have at least the following technical effects:

[0051] First, connect the temperature monitoring device to obtain the monitored temperature of the metal heat sink, and the monitored temperature of the metal heat sink has an identification of the heat sink distribution position. Then, construct the three-dimensional coordinates of the metal heat sink, perform three-dimensional coordinate position fitting according to the heat sink distribution position identification, and determine the heat distribution of the heat sink. Further, perform heat dissipation circulation demand analysis based on the heat distribution of the heat sink to determine the circulation demand distribution. Then, establish the control relationship between the fan control parameters and the heat dissipation circulation. Finally, with the circulation demand distribution as the goal, search for the control parameters according to the control relationship to determine the fan control strategy, and the fan control strategy is used for intelligent linkage control of the fan. This solves the technical problem in the prior art that the heat dissipation efficiency between the heat sink and the fan is not matched and cannot be intelligently adjusted according to the real-time heat, resulting in poor heat dissipation effect. By real-time monitoring the temperature distribution of the heat sink and intelligently adjusting the fan control strategy, the technical effects of improving the heat dissipation efficiency and reducing the energy consumption are achieved.

[0052] Embodiment 2, based on the same inventive concept as the method for intelligent linkage control of a metal heat sink and a fan in the foregoing embodiment, as Figure 2 shown, the present application provides a device for intelligent linkage control of a metal heat sink and a fan, wherein the device includes:

[0053] A temperature monitoring module 11, which is used to connect to a temperature monitoring device to obtain the monitored temperature of the metal heat sink, and the monitored temperature of the metal heat sink has a heat sink distribution position identifier; a fitting module 12, which is used to construct the three-dimensional coordinates of the metal heat sink, perform three-dimensional coordinate position fitting according to the heat sink distribution position identifier, and determine the heat distribution of the heat sink; a demand analysis module 13, which is used to analyze the heat dissipation circulation demand according to the heat distribution of the heat sink to determine the circulation demand distribution; a control relationship establishment module 14, which is used to establish the control relationship between the fan control parameters and the heat dissipation circulation; a control module 15, which is used to target the circulation demand distribution, search for control parameters according to the control relationship, and determine the fan control strategy, and the fan control strategy is used for intelligent linkage control of the fan.

[0054] Further, the temperature monitoring module 11 is used to execute the following method:

[0055] Identify the key areas of the heat sink based on the historical monitoring samples of the heat sink, including the heat source contact area, the center of the heat sink, and the edge of the heat sink; perform regional clustering according to the distribution distance of the key areas and the historical heat distribution to obtain the monitoring point distribution information, and the monitoring point distribution information is a sensor layout strategy to ensure that the range of the temperature sensor distribution covers all temperature clustering areas; obtain the temperature change frequency of the key areas to determine the monitoring response time; set the temperature sensor based on the monitoring response time and the monitoring point distribution information.

[0056] Further, the temperature monitoring module 11 is used to execute the following method:

[0057] Obtain the monitored temperature through the temperature monitoring device and locate the position of the temperature monitoring device; map the temperature clustering area according to the position of the temperature monitoring device; analyze the corresponding area of the heat sink according to the temperature clustering area, and establish the heat sink distribution position identifier of the monitored temperature.

[0058] Further, the demand analysis module 13 is used to execute the following method:

[0059] Identify the temperature gradient according to the heat distribution of the heat sink; obtain the fin characteristics of the heat sink, and the fin characteristics include shape, size, spacing, and direction, and analyze the heat dissipation path according to the fin characteristics; fit the natural path of the heat flow of the heat sink according to the temperature gradient according to fluid dynamics; use the heat dissipation path to perform flow direction intervention correction on the natural path of the heat flow to obtain the heat flow path; perform circulation compensation on the heat flow path according to the heat distribution of the heat sink to obtain the circulation demand distribution.

[0060] Further, the demand analysis module 13 is used to execute the following method:

[0061] According to the heat distribution of the heat sink, calculate the total heat dissipation circulation demand of the heat sink; according to the heat flow path, perform operations on the heat dissipation flow on the path to determine the distribution path of the natural heat dissipation; according to the three-dimensional coordinates of the metal heat sink, establish the distribution coordinate relationship between the distribution path of the natural heat dissipation and the total heat dissipation circulation demand of the heat sink; according to the distribution coordinate relationship, determine the correspondence between the total heat dissipation circulation demand and the natural heat dissipation, and calculate the difference based on the correspondence to obtain the distribution of the circulation demand.

[0062] Further, the demand analysis module 13 is used to execute the following method:

[0063] According to the fin characteristics of the heat sink, identify the circulation dead corners and inefficient areas; according to the identification results of the circulation dead corners and inefficient areas, locate the distribution of the circulation demand and mark the circulation dead corners and inefficient areas; according to the circulation efficiency of the circulation dead corners and inefficient areas, generate a circulation demand forcing coefficient, which is used to increase the circulation demand weight of the marked area in the linkage control; according to the located distribution position of the circulation demand, add the circulation demand forcing coefficient to the distribution of the circulation demand;

[0064] Further, the demand analysis module 13 is used to execute the following method:

[0065] Through the natural heat dissipation formula: , perform operations on the heat dissipation flow on the path to obtain the natural heat dissipation, where natural heat dissipation, is the natural heat flux density, is the thermal conductivity, is the three-dimensional coordinate temperature gradient at the position, is the infinitesimal area element on the path.

[0066] Further, the control module 15 is used to execute the following method:

[0067] The control parameters include the fan angle and the air volume. The adjustment ranges of the fan angle and the air volume are obtained. According to the adjustment ranges of the fan angle and the air volume, an angle grid and an air volume grid are respectively set. Through the grid combination of all control parameters, a grid parameter space is generated. Based on the circulation demand forcing coefficient, the distribution weights of each region of the circulation demand distribution are configured, and a matching error function is constructed. An empty matrix is created to record the matching error of each parameter combination. According to the grid parameter space, the parameter combinations are traversed, the error calculation is performed based on the matching error function, and the empty matrix is loaded synchronously using the error calculation results. After meeting the target search requirements, the minimum error control strategy is searched based on the error matrix and used as the fan control strategy.

[0068] It should be noted that the above sequence of embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above describes specific embodiments of this specification. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0070] This specification and the drawings are only exemplary descriptions of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A method for intelligent linkage control of a metal heat sink and a fan, characterized in that: The metal heat sink and fan intelligent linkage control method comprises: Connecting a temperature monitoring device to obtain a monitoring temperature of a metal heat sink, wherein the monitoring temperature of the metal heat sink has a heat sink distribution position identifier; Constructing the three-dimensional coordinates of the metal heat sink, performing three-dimensional coordinate position fitting according to the heat sink distribution position identifier, and determining the heat distribution of the heat sink; Perform heat dissipation circulation demand analysis based on the heat distribution of the heat sink to determine the circulation demand distribution; Establish the control relationship between fan control parameters and heat dissipation circulation; Taking the circulation demand distribution as a target, searching for control parameters according to the control relationship, and determining a fan control strategy, wherein the fan control strategy is used for intelligent linkage control of fans; Performing heat dissipation circulation demand analysis according to the heat distribution of the heat sink to determine the circulation demand distribution includes: identifying a temperature gradient based on the heat distribution of the heat sink; Obtaining fin features of a heat sink, wherein the fin features include shape, size, spacing, and direction, and analyzing a heat dissipation path according to the fin features; Using the temperature gradient to fit the natural path of heat flow of the heat sink according to fluid dynamics; Using the heat dissipation path to perform flow intervention correction on the natural heat flow path to obtain a heat flow path; According to the heat distribution of the heat sink, flow compensation is performed on the heat flow path to obtain the flow demand distribution.

2. The metal heat sink and fan intelligent linkage control method according to claim 1, characterized in that: The connection temperature monitoring device previously comprises: Identify key areas of the heat sink based on historical monitoring samples of the heat sink, including the heat source contact area, the center of the heat sink, and the edge of the heat sink; According to the distribution distance and historical heat distribution of the key areas, regional clustering is performed to obtain monitoring point distribution information, wherein the monitoring point distribution information is a sensor deployment strategy to ensure that the range of temperature sensor distribution covers all temperature clustering areas; Obtaining the temperature change frequency of the key area and determining the monitoring response time; The temperature sensor is set based on the monitoring response time and the monitoring point distribution information.

3. The metal heat sink and fan intelligent linkage control method according to claim 2, characterized in that: The connecting temperature monitoring device to obtain the monitoring temperature of the metal heat sink includes: Acquiring the monitoring temperature through the temperature monitoring device and locating the position of the temperature monitoring device; Mapping temperature clustering areas according to the locations of the temperature monitoring devices; The heat sink corresponding area is analyzed according to the temperature clustering area, and the heat sink distribution position identification of the monitored temperature is established.

4. The metal heat sink and fan intelligent linkage control method according to claim 1, characterized in that: According to the heat distribution of the heat sink, flow compensation is performed on the heat flow path to obtain the flow demand distribution, including: Calculating the total heat dissipation flow demand of the heat sink according to the heat distribution of the heat sink; According to the heat flow path, calculating the heat dissipation heat flow on the path to determine the distribution path of natural heat dissipation; According to the three-dimensional coordinates of the metal heat sink, a distribution coordinate relationship between a distribution path of natural heat dissipation and a total amount of heat dissipation circulation demand of the heat sink is established; The corresponding relationship between the total amount of heat dissipation circulation demand and the natural heat dissipation is determined according to the distribution coordinate relationship, and the difference amount is calculated based on the corresponding relationship to obtain the circulation demand distribution.

5. The metal heat sink and fan intelligent linkage control method according to claim 4, characterized in that: Obtaining the circulation demand distribution further includes: According to the fin characteristics of the heat sink, dead corners and inefficient areas of circulation are identified; According to the identification results of the circulation blind spots and inefficient areas, the circulation demand distribution is located, and the circulation blind spots and inefficient areas are marked; Generate a circulation demand force coefficient according to the circulation efficiency of the circulation dead angle and the inefficient area, and the circulation demand force coefficient is used to increase the circulation demand weight of the marked area in the linkage control; According to the located circulation demand distribution position, the circulation demand mandatory coefficient is added to the circulation demand distribution.

6. The metal heat sink and fan intelligent linkage control method according to claim 4, characterized in that: According to the heat flow path, the heat dissipation heat flow on the path is calculated, including: Through the natural heat dissipation formula: The heat dissipation flow on the path is calculated to obtain the natural heat dissipation, where Q natural Natural heat dissipation, is the natural heat flux, k is the thermal conductivity, is the temperature gradient at the three-dimensional coordinates x, y, and z, and dA is the small area element on the path.

7. The metal heat sink and fan intelligent linkage control method according to claim 5, characterized in that: Taking the circulation demand distribution as a target, searching for control parameters according to the control relationship and determining a fan control strategy include: The control parameters include fan angle and air volume, and the fan angle adjustment range and air volume adjustment range are obtained; According to the fan angle adjustment range and the air volume adjustment range, an angle grid and an air volume grid are set respectively, and a grid parameter space is generated by combining the grids of all control parameters; Based on the circulation demand mandatory coefficient, the distribution weights of each area of ​​the circulation demand distribution are configured, and based on the circulation demand distribution and the heat dissipation effect under the current fan control parameters, a matching error function is constructed, where the matching error function is used to calculate the difference between the actual heat dissipation effect and the ideal heat dissipation demand, and the smaller the difference, the smaller the matching error; Creating an empty matrix for recording the matching error of each parameter combination, traversing the parameter combination according to the grid parameter space, performing error calculation based on the matching error function, and synchronously loading the empty matrix using the error calculation result; The target search requirement is completed, and the minimum error control strategy is searched based on the error matrix as the fan control strategy.

8. A metal heat sink and fan intelligent linkage control device, characterized in that: The device is used to implement a method for intelligent linkage control of a metal heat sink and a fan as described in any one of claims 1 to 7, and comprises: A temperature monitoring module, the temperature monitoring module is used to connect to a temperature monitoring device to obtain a monitoring temperature of a metal heat sink, the monitoring temperature of the metal heat sink having a heat sink distribution position identifier; A fitting module, the fitting module is used to construct the three-dimensional coordinates of the metal heat sink, perform three-dimensional coordinate position fitting according to the heat sink distribution position identifier, and determine the heat distribution of the heat sink; A demand analysis module, the demand analysis module is used to perform heat dissipation and circulation demand analysis according to the heat distribution of the heat sink, and determine the circulation demand distribution; A control relationship establishing module, the control relationship establishing module is used to establish a control relationship between fan control parameters and heat dissipation circulation; A control module is used to take the circulation demand distribution as a target, search for control parameters according to the control relationship, and determine a fan control strategy, wherein the fan control strategy is used for intelligent linkage control of the fan.

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