Intelligent temperature management method and system for high-density server room

Abstract

The present invention discloses an intelligent temperature management method and system for a high-density server room, and relates to the field of intelligent temperature management technology. It includes: position acquisition: based on a first acquisition method, the server position and the cold source position are acquired, and a first position set and a second position set are obtained respectively, the first position set includes at least the position of one server, and the second position set includes at least the position of one cold source; temperature acquisition: based on the second acquisition method, the real-time temperature of the server is acquired to obtain a real-time temperature set. The present invention detects and acquires the real-time temperature of the server, and when a server needs to be cooled down, the cooling work is performed by scheduling the cold source, and in the process of scheduling the cold source, the scheduling method of the cold source is optimized, so that the cold source can achieve the cooling effect on the server at the fastest speed and the best cooling effect, and while achieving the energy saving effect, the target server can be quickly cooled down.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent temperature management, and in particular to an intelligent temperature management method and system for a high-density server room. Background Art

[0002] A high-density server room refers to a room where a large number of server devices are deployed in a limited space to achieve higher computing and storage capabilities, such as rack servers, blade servers, etc., to meet the growing computing needs. Due to the high density of server equipment, the heat dissipation is relatively high, so professional heat dissipation equipment and cold source systems are required to control the temperature of the room and keep it within an appropriate range. In order to improve the efficiency and stability of high-density server rooms, intelligent temperature management systems are usually used to monitor and adjust the temperature inside the room in real time to ensure that the server equipment works under the best environmental conditions. At the same time, it can also save energy and reduce costs. In general, high-density server rooms are characterized by high efficiency, energy saving and stability. They are a commonly used server deployment form for large and medium-sized enterprises and data centers, and can meet large-scale computing and storage needs.

[0003] The patent publication number is CN117574613A, which is an artificial intelligence-based temperature prediction system for an automated computer room. The system comprises: a temperature acquisition module that acquires the temperature of the inner wall of the computer room, the temperature of the air in the computer room and the temperature of the equipment in the computer room through a temperature acquisition device, and then acquires the heat change of the inner wall of the room, the heat change of the equipment in the computer room and the heat change of the ventilation holes in the computer room through a heat acquisition device, and constructs a computer room temperature system model by acquiring data; a data analysis module that analyzes the temperature in the computer room temperature system model to obtain the temperature change inside the computer room; a temperature prediction module that predicts the temperature of the computer room according to the temperature change to obtain the temperature change trend of the computer room; and a temperature intelligent control module that controls the temperature of the computer room according to the temperature change trend. The present invention can solve the problem of inaccurate and untimely temperature prediction of the computer room in the existing solution, and can save energy consumption through the temperature intelligent control module.

[0004] During the use of the above and similar technical solutions, since the density of servers in a high-density computer room is relatively high, it is generally necessary to install cold sources in multiple locations in the computer room for cooling. However, since the workload of each server in the computer room is inconsistent, when the temperature in the computer room is uniformly adjusted, the temperature of some servers with higher loads still cannot be effectively adjusted, thereby affecting the working condition of the server. In addition, when the cold source cools the server, it cools down within a certain range of the location of the server, and cannot achieve targeted cooling of a certain server. When the server needs to be cooled urgently, it cannot be cooled quickly in a short time. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent temperature management method and system for a high-density server room to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: an intelligent temperature management method and system for a high-density server room, comprising:

[0007] Location acquisition: acquiring the server location and the cold source location based on the first acquisition method, and obtaining a first location set and a second location set respectively, wherein the first location set includes the location of at least one server, and the second location set includes the location of at least one cold source;

[0008] Temperature acquisition: acquiring the real-time temperature of the server based on the second acquisition method to obtain a real-time temperature set;

[0009] Cold source scheduling: Set the operating temperature threshold of the server. When the real-time temperature set reaches the operating temperature threshold, the cold source is scheduled to cool the server based on the first position set and the second position set through the scheduling method;

[0010] Scheduling optimization: based on the third acquisition method, the air inlet position of the server and the air outlet position of the cold source are obtained to obtain an air inlet data set and an air outlet data set respectively. Based on the air inlet data set and the air outlet data set, the scheduling of the cold source is optimized by an optimization method;

[0011] The optimization method comprises:

[0012] Step 1: Determine the air inlet range. Based on the air inlet data set, set the optimal air inlet range of each server in the first location set to obtain at least one air inlet angle item.

[0013] Step 2: Determine the air outlet range, based on the air outlet data set, determine the air outlet range of each cold source in the second position set, and obtain at least one air outlet angle item;

[0014] Step 3: Range extension: extend the range in proportion to the air outlet angle item, and determine whether the air outlet angle item covers the air inlet angle item after extension. When the air outlet angle item covers the air inlet angle item, determine that the cooling source at this time can meet the optimal cooling of the server, and control the cooling source according to the cooling source setting that can achieve this air outlet angle item state;

[0015] Step 4: Cold source combination. Based on the coverage area of ​​the air outlet angle item to the air inlet angle item, when the coverage area does not reach the preset threshold of the total area of ​​the air inlet angle item, repeat step 3 to select another cold source for combined cooling of the server.

[0016] Furthermore, the scheduling method includes:

[0017] S1: Determine the demand point. Based on the first location set, take the server location coordinates where the real-time temperature set reaches the operating temperature threshold as the demand point to obtain the demand point set.

[0018] S2: Supply point confirmation: based on the demand point set, the demand range is set, at least one cold source within the demand range is obtained, the location coordinates of the cold source are used as the supply point, and the supply point set is obtained;

[0019] S3: Path generation: based on the demand point set and the supply point set, generate at least one straight line connecting the demand point set and the supply point set to obtain a path set;

[0020] S4: Path sorting: Based on the path set, the path set is sorted according to the length of the path to obtain the path sorting item, and the supply point with the shortest path is preferentially scheduled according to the path sorting item to cool down the demand point.

[0021] Furthermore, the scheduling method further includes:

[0022] S5: Path screening. In the process of S4, when the supply point in the shortest path between the target demand point and the supply point is in the state of cooling down another demand point, the supply point in the next path is selected to cool down the target demand point according to the path sorting item.

[0023] Furthermore, the first acquisition method includes locator acquisition:

[0024] M1: Installation of positioning equipment: Install positioning equipment on the server and cold source respectively, and continuously obtain the position change information of the server and cold source during the installation process;

[0025] M2: Feature point acquisition, using the location coordinate information of the positioning device as the feature point information of the server and the cold source, respectively, to obtain multiple first feature points and multiple second feature points, the first feature points are combined into a first position set, and the second feature points are combined into a second feature set.

[0026] Furthermore, the second characteristic point corresponds to at least one standing cold source, and the first acquisition method further includes:

[0027] M3: area determination, obtain the indoor area data of the computer room, and obtain the indoor area item;

[0028] M4: Determination of standing cold source: In the process of M2, based on the position coordinate information of multiple second feature points, the second feature point whose relative position is in the middle of the indoor area item is taken as the standing cold source, and the screening feature points are obtained, and the screening feature points are combined into the second feature set.

[0029] Furthermore, the second acquisition method includes conventional acquisition: based on the first feature point, at least one temperature sensor is installed at the position of the first feature point, and the real-time temperature of the server is scanned and acquired one-to-one or many-to-one in real time to obtain multiple real-time scanning items based on the first feature point, and the multiple real-time scanning items are combined into a real-time temperature set.

[0030] Furthermore, the second acquisition method includes predictive acquisition:

[0031] P1: Load acquisition, based on the first position set, obtain the real-time load rate of the server;

[0032] P2: Temperature prediction, predicting the server temperature based on the real-time load rate to obtain the predicted temperature item;

[0033] P3: Temperature comparison, comparing the predicted temperature item with the real-time scanning item. When the predicted temperature item is greater than the real-time scanning item, the real-time temperature set is a combination of multiple predicted temperature items. Conversely, when the predicted temperature item is less than the real-time scanning item, the real-time temperature set is a combination of multiple real-time scanning items.

[0034] Furthermore, the third acquisition method includes:

[0035] X1: Location acquisition: multiple camera positions are installed in the computer room to take pictures of the servers and cold sources in the computer room to obtain image sets.

[0036] X2: Area acquisition: Based on the image set, the air inlet area of ​​the server and the air outlet area of ​​the cold source are obtained respectively to obtain the air inlet area item and the air outlet area item. The air inlet data set includes multiple air inlet area items.

[0037] X3: Range calculation, based on the air outlet area item and the image set, at least two feature points are set at the midpoint position of the horizontal air outlet blades of the cold source, and at least two feature points are set at the midpoint position of the vertical air outlet blades of the cold source. The inclination angle of the line connecting the two feature points on the horizontal air outlet blades is used as the left and right swing range of the cold source, and the inclination angle of the line connecting the two feature points on the vertical air outlet blades is used as the up and down swing range of the cold source. The air outlet data set includes the left and right swing range and the up and down swing range.

[0038] An intelligent temperature management system for a high-density server room uses the above-mentioned intelligent temperature management method for a high-density server room.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The intelligent temperature management method and system of the high-density server room detects and obtains the real-time temperature of the server. When a server needs to be cooled, the cooling work is carried out by scheduling the cold source. In the process of scheduling the cold source, the scheduling method of the cold source is optimized so that the cold source can achieve the cooling effect on the server at the fastest speed and the best cooling effect, thereby achieving energy saving effect and quickly cooling the target server.

[0041] At the same time, when cooling the server, the air outlet angle of the cold source is adjusted according to the position of the air inlet of the server, so that the cold air blown by the cold source can reach the air inlet of the server through the shortest path, thereby achieving the best cooling effect on the server, and when the cold source is unable to effectively and fully cool down some servers due to the limitation of the air outlet range, other cold sources can be linked to cool down the target server at the same time, which fully guarantees the rapid cooling effect of the server, and by detecting the load rate of the server, the subsequent temperature change of the server can be predicted according to the load rate of the server, and the predicted temperature is used as the real-time temperature of the server, and the cold source is scheduled for cooling, which can more effectively achieve the pre-cooling effect of the server.

[0042] Moreover, the air outlet range of the cold source can be adjusted more specifically according to the air inlet range, and it can be determined whether the air outlet range can cover the air inlet range of the server. When the air outlet range can cover the air inlet range of the server, it means that the cold source can meet the best cooling effect for the server. On the contrary, when the air outlet range cannot cover the air inlet range of the server or cannot completely cover the air inlet range of the server, it means that the cold source cannot meet the best cooling effect for the server. At this time, it is decided whether to dispatch another cold source to cool the target server according to the coverage area of ​​the cold source air outlet range to the server air inlet range. The preset threshold is a changeable item. For example, when the air outlet range does not reach more than half of the total area of ​​the air inlet range, the server is cooled in combination by dispatching another cold source. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of the overall process relationship of position set acquisition and temperature control optimization of the present invention;

[0044] Figure 2 It is a schematic diagram of the optimization method of the present invention;

[0045] Figure 3 It is a schematic diagram of the scheduling method of the present invention;

[0046] Figure 4 This is a schematic diagram of the path screening of the present invention;

[0047] Figure 5It is a schematic diagram of the left-right swing range and the up-down swing range of the cooling source of the present invention;

[0048] Figure 6 It is a schematic diagram of a standing cold source of the present invention;

[0049] Figure 7 It is a schematic diagram of the horizontal and vertical fan blades of the cold source of the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] When the cold source is working, the range of its cooling mode is determined by the horizontal blades of the cold source air outlet, and the range of the cold air swinging up and down is determined by the longitudinal blades. When the horizontal blades and longitudinal blades of the cold source are swinging, the cold air generated spreads outward. When a server at a certain position generates more heat due to a large load, the cold source cannot effectively perform targeted cooling on the server at this position. When the technical solution provided by the present application is working, the location of the server and the cold source can be obtained first, and the air inlet position of the server and the air outlet position and air outlet range of the cold source can be further obtained. When cooling the server, the air outlet angle of the cold source is adjusted according to the air inlet position of the server, so that the cold air blown out by the cold source can reach the air inlet of the server in the shortest path, thereby achieving the best cooling effect on the server. When the cold source cannot effectively and fully cool down some servers due to the limitation of the air outlet range, other cold sources can be linked to cool down the target server at the same time, which fully ensures the rapid cooling effect of the server.

[0052] like Figure 1-Figure 7As shown, the present invention provides a technical solution: an intelligent temperature management method and system for a high-density server room, including: position acquisition: based on a first acquisition method, the server position and the cold source position are acquired to obtain a first position set and a second position set respectively, the first position set includes at least the position of one server, and the second position set includes at least the position of one cold source; temperature acquisition: based on the second acquisition method, the real-time temperature of the server is acquired to obtain a real-time temperature set; cold source scheduling: setting the working temperature threshold of the server, when the real-time temperature set reaches the working temperature threshold, based on the first position set and the second position set, the cold source is scheduled to cool down the server through a scheduling method; scheduling optimization: based on a third acquisition method, the air inlet position of the server and the air outlet position of the cold source are acquired to obtain an air inlet data set and an air outlet data set respectively, and based on the air inlet data set and the air outlet data set, the cold source is scheduled through an optimization method. Optimization is performed; the optimization method includes: step one: determining the air inlet range, based on the air inlet data set, setting the optimal air inlet range of each server in the first position concentration, and obtaining at least one air inlet angle item; step two: determining the air outlet range, based on the air outlet data set, determining the air outlet range of each cold source in the second position concentration, and obtaining at least one air outlet angle item; step three: extending the range, extending in proportion according to the air outlet angle item, judging whether the air outlet angle item covers the air inlet angle item after extension, when the air outlet angle item can cover the air inlet angle item, judging that the cold source at this time can meet the optimal cooling of the server, and controlling the cold source according to the cold source setting that can achieve this air outlet angle item state; step four: cold source combination, based on the coverage area of ​​the air outlet angle item to the air inlet angle item, when the coverage area does not reach the preset threshold of the total area of ​​the air inlet angle item, repeating step three to select another cold source to perform combined cooling on the server.

[0053] It should be noted that the location information of the server and the cold source should be obtained respectively first. During the installation and use of the server and the cold source, their locations may change. Therefore, it is necessary to obtain the locations of the server and the cold source regularly to facilitate rapid cooling of the servers that need cooling, and to detect and obtain the real-time temperature of the server. When a server needs to be cooled, the cooling work is carried out by scheduling the cold source, and in the scheduling process of the cold source, the scheduling method of the cold source is optimized so that the cold source can achieve the cooling effect on the server at the fastest speed and the best cooling effect, thereby achieving energy saving effect and quickly cooling the target server.

[0054] As a specific implementation method, in the optimization process of cold source scheduling, the air inlet range of the server is first determined. Since each server has an air inlet slot to achieve the heat dissipation effect, when the air inlet range of the server is determined, the air outlet range of the cold source can be adjusted more specifically according to the air inlet range. During the operation of the cold source, the air outlet range is adjusted with the help of the cold source's own equipment. For example, during the operation of the cold source, the air outlet range is adjusted through the horizontal air outlet plate and the vertical air outlet plate respectively. The horizontal air outlet plate adjusts the up and down air outlet range of the cold source during the up and down swinging process, and the vertical air outlet plate adjusts the left and right air outlet range of the cold source during the left and right swinging process. Therefore, it can be determined according to the maximum rotation range of the horizontal air outlet plate and the vertical air outlet plate. The overall air outlet range of the cold source, and whether the air outlet range of the cold source can cover the air inlet range of the server is determined according to the air outlet range of the cold source. When the air outlet range of the cold source can cover the air inlet range of the server, it means that the cold source can meet the best cooling effect for the server. Conversely, when the air outlet range of the cold source cannot cover the air inlet range of the server or cannot completely cover the air inlet range of the server, it means that the cold source cannot meet the best cooling effect for the server. At this time, whether to dispatch another cold source to cool the target server is determined according to the coverage area of ​​the cold source air outlet range of the server air inlet range. The preset threshold is a changeable item. For example, when the air outlet range does not reach more than half of the total area of ​​the air inlet range, the server is cooled in combination by dispatching another cold source.

[0055] like Figure 3 As shown, the scheduling method includes: S1: demand point determination, based on the first location set, taking the server location coordinates of the real-time temperature set reaching the working temperature threshold as the demand point, and obtaining the demand point set; S2: supply point confirmation, based on the demand point set, setting the demand range, obtaining at least one cold source within the demand range, taking the location coordinates of the cold source as the supply point, and obtaining the supply point set; S3: path generation, based on the demand point set and the supply point set, generating at least one straight line connecting the demand point set and the supply point set, and obtaining the path set; S4: path sorting, based on the path set, sorting the path set according to the length of the path, obtaining the path sorting item, and according to the path sorting item, preferentially scheduling the supply point with the shortest path to cool the demand point.

[0056] It should be noted that during the operation of the server, the temperature in the entire computer room is maintained in a certain temperature range, and individual servers may have excessive loads that cause the temperature to rise. At this time, these servers are servers that have reached the operating temperature threshold, and the location information of these servers is used as the demand point. By setting a circular range, there are many cold sources within the circular range. At this time, these cold sources are supply points. According to the location of the demand point and the location of the supply point, multiple paths are generated between the two points. These paths are sorted by length, and the shortest path is the target supply point. The path can achieve the best cooling effect on the target demand point.

[0057] like Figure 4 As shown, the scheduling method also includes: S5: path screening. In the process of S4, when the supply point in the shortest path between the target demand point and the supply point is in the state of cooling down another demand point, the supply point in the next path is selected to cool down the target demand point according to the path sorting item.

[0058] It should be noted that in the sorted path, when two demand points are simultaneously the shortest paths to the same cold source, it is determined whether the supply point is in working condition. If the supply point is in working condition, the path between this supply point and the target demand point is determined as a eliminated path. According to the sorting effect of the path, another path is reselected, that is, another cold source is reselected to cool the target demand point.

[0059] The first acquisition method includes locator acquisition: M1: positioning device installation, installing the positioning device on the server and the cold source respectively, and continuously acquiring the position change information of the server and the cold source during the installation process; M2: feature point acquisition, using the position coordinate information of the positioning device as the feature point information of the server and the cold source respectively, and obtaining multiple first feature points and multiple second feature points respectively. The first feature points are combined into a first position set, and the second feature points are combined into a second feature set.

[0060] like Figure 6 As shown, there is at least one standing cold source corresponding to the second feature point, and the first acquisition method also includes: M3: area determination, obtaining the indoor area data of the computer room to obtain the indoor area item; M4: standing cold source determination: in the process of M2, based on the position coordinate information of multiple second feature points, the second feature point whose relative position is in the middle of the indoor area item is used as the standing cold source to obtain the screening feature points, and the screening feature points are combined into the second feature set.

[0061] It should be noted that since the servers in the computer room will be in a state of working all the time, the temperature in the entire computer room needs to be maintained in a certain range to ensure the normal operation of the servers. Therefore, a standing cold source is required to be in a state of working all the time. At this time, the second feature point whose relative position is in the middle of the indoor area item is selected as the standing cold source among the second feature points, and the remaining second feature points are used as screening feature points as dispatchable cold sources.

[0062] The second acquisition method includes conventional acquisition: based on the first feature point, at least one temperature sensor is installed at the position of the first feature point, and the real-time temperature of the server is scanned one-to-one or many-to-one in real time to obtain multiple real-time scanning items based on the first feature point, and the multiple real-time scanning items are combined into a real-time temperature set.

[0063] The second acquisition method includes predictive acquisition: P1: load acquisition, based on the first position set, obtaining the real-time load rate of the server; P2: temperature prediction, predicting the temperature of the server based on the real-time load rate to obtain a predicted temperature item; P3: temperature comparison, comparing the predicted temperature item with the real-time scanning item. When the predicted temperature item is greater than the real-time scanning item, the real-time temperature set is a combination of multiple predicted temperature items. Conversely, when the predicted temperature item is less than the real-time scanning item, the real-time temperature set is a combination of multiple real-time scanning items.

[0064] It should be noted that when the server is working, running different programs or with different usage, its load rate is different, so the temperature generated by the server is also different. When the load is generated, the temperature of the server will rise after a period of time. At this time, by detecting the load rate of the server, the subsequent temperature change of the server can be predicted according to the load rate of the server. The predicted temperature is used as the real-time temperature of the server, and the cold source is scheduled for cooling. The pre-cooling effect of the server can be more effectively achieved. By comparing the predicted temperature with the detected temperature obtained by the temperature sensor, when the predicted temperature is greater than the detected temperature, the real-time temperature is a combination of multiple predicted temperatures. Conversely, when the predicted temperature is less than the detected temperature, the real-time temperature is a combination of multiple detected temperatures. In this way, the temperature of the server can be detected more effectively, thereby effectively controlling the temperature of the server.

[0065] like Figure 5As shown, the third acquisition method includes: X1: position acquisition, multiple sets of camera positions are installed in the computer room, and the servers and cold sources in the computer room are photographed respectively to obtain an image set; X2: area acquisition, based on the image set, the air inlet area of ​​the server and the air outlet area of ​​the cold source are respectively acquired to obtain an air inlet area item and an air outlet area item, and the air inlet data set includes multiple air inlet area items; X3: range calculation, based on the air outlet area item and the image set, at least two feature points are set at the midpoint position of the horizontal outlet fan blade of the cold source, and at least two feature points are set at the midpoint position of the longitudinal outlet fan blade of the cold source, and the inclination angle of the line connecting the two feature points on the horizontal outlet fan blade is used as the up and down swing range of the cold source, and the inclination angle of the line connecting the two feature points on the longitudinal outlet fan blade is used as the left and right swing range of the cold source, and the air outlet data set includes the left and right swing range and the up and down swing range.

[0066] It should be noted that two characteristic points are set at the midpoint of the transverse fan blades of the cold source, and the two characteristic points are located one in front and one behind, respectively at the front and rear positions of the transverse fan blades. Two characteristic points are set at the midpoint of the longitudinal fan blades of the cold source, and are located at the front and rear positions of the longitudinal fan blades, respectively. The line connecting the two characteristic points on the transverse fan blades is used as the up and down swing range of the cold source, and the line connecting the two characteristic points on the longitudinal fan blades is used as the left and right swing range of the cold source, so that the air outlet range of the cold source can be intuitively obtained.

[0067] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is limited by the attached embodiments and their equivalents.

Claims

1. An intelligent temperature management method for a high-density server room, characterized in that: include: Location acquisition: acquiring the server location and the cold source location based on the first acquisition method, and obtaining a first location set and a second location set respectively, wherein the first location set includes the location of at least one server, and the second location set includes the location of at least one cold source; Temperature acquisition: acquiring the real-time temperature of the server based on the second acquisition method to obtain a real-time temperature set; Cold source scheduling: Set the operating temperature threshold of the server. When the real-time temperature set reaches the operating temperature threshold, the cold source is scheduled to cool the server based on the first position set and the second position set through the scheduling method; Scheduling optimization: based on the third acquisition method, the air inlet position of the server and the air outlet position of the cold source are obtained to obtain an air inlet data set and an air outlet data set respectively. Based on the air inlet data set and the air outlet data set, the scheduling of the cold source is optimized by an optimization method; The optimization method comprises: Step 1: Determine the air inlet range. Based on the air inlet data set, set the optimal air inlet range of each server in the first location set to obtain at least one air inlet angle item. Step 2: Determine the air outlet range, based on the air outlet data set, determine the air outlet range of each cold source in the second position set, and obtain at least one air outlet angle item; Step 3: Range extension: extend the range in proportion to the air outlet angle item, and determine whether the air outlet angle item covers the air inlet angle item after extension. When the air outlet angle item covers the air inlet angle item, determine that the cooling source at this time can meet the optimal cooling of the server, and control the cooling source according to the cooling source setting that can achieve this air outlet angle item state; Step 4: cold source combination, based on the coverage area of ​​the air outlet angle item to the air inlet angle item, when the coverage area does not reach the preset threshold of the total area of ​​the air inlet angle item, repeat step 3 to select another cold source to perform combined cooling on the server; The second acquisition method includes conventional acquisition: based on the first feature point, at least one temperature sensor is installed at the position of the first feature point, and the real-time temperature of the server is scanned and acquired in a one-to-one or many-to-one real-time manner to obtain multiple real-time scanning items based on the first feature point, and the multiple real-time scanning items are combined into a real-time temperature set; The second acquisition method includes predictive acquisition: P1: Load acquisition, based on the first position set, obtain the real-time load rate of the server; P2: Temperature prediction, predicting the server temperature based on the real-time load rate to obtain the predicted temperature item; P3: Temperature comparison, comparing the predicted temperature item with the real-time scan item. When the predicted temperature item is greater than the real-time scan item, the real-time temperature set is a combination of multiple predicted temperature items. Conversely, when the predicted temperature item is less than the real-time scan item, the real-time temperature set is a combination of multiple real-time scan items. The third acquisition method includes: X1: Location acquisition: multiple camera positions are installed in the computer room to take pictures of the servers and cold sources in the computer room to obtain image sets. X2: Area acquisition: Based on the image set, the air inlet area of ​​the server and the air outlet area of ​​the cold source are obtained respectively to obtain the air inlet area item and the air outlet area item. The air inlet data set includes multiple air inlet area items. The scheduling method comprises: S1: Determine the demand point. Based on the first location set, take the server location coordinates where the real-time temperature set reaches the operating temperature threshold as the demand point to obtain the demand point set. S2: Supply point confirmation: based on the demand point set, the demand range is set, at least one cold source within the demand range is obtained, the location coordinates of the cold source are used as the supply point, and the supply point set is obtained; S3: Path generation: based on the demand point set and the supply point set, generate at least one straight line connecting the demand point set and the supply point set to obtain a path set; S4: Path sorting: Based on the path set, the path set is sorted according to the length of the path to obtain the path sorting item, and the supply point with the shortest path is preferentially scheduled according to the path sorting item to cool down the demand point.

2. The intelligent temperature management method for a high-density server room according to claim 1, characterized in that: The scheduling method further includes: S5: Path screening. In the process of S4, when the supply point in the shortest path between the target demand point and the supply point is in the state of cooling down another demand point, the supply point in the next path is selected to cool down the target demand point according to the path sorting item.

3. The intelligent temperature management method for a high-density server room according to claim 1, characterized in that: The first acquisition method includes locator acquisition: M1: Installation of positioning equipment: Install positioning equipment on the server and cold source respectively, and continuously obtain the position change information of the server and cold source during the installation process; M2: Feature point acquisition, using the location coordinate information of the positioning device as the feature point information of the server and the cold source, respectively, to obtain multiple first feature points and multiple second feature points, the first feature points are combined into a first position set, and the second feature points are combined into a second feature set.

4. The intelligent temperature management method for a high-density server room according to claim 3, characterized in that: The second characteristic point corresponds to at least one standing cold source, and the first acquisition method further includes: M3: area determination, obtain the indoor area data of the computer room, and obtain the indoor area item; M4: Determination of standing cold source: In the process of M2, based on the position coordinate information of multiple second feature points, the second feature point whose relative position is in the middle of the indoor area item is taken as the standing cold source, and the screening feature points are obtained, and the screening feature points are combined into the second feature set.

5. An intelligent temperature management system for a high-density server room, characterized in that: An intelligent temperature management method for a high-density server room is used as described in any one of claims 1-4.

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