CN115389049A - Method for calculating temperature field and electronic equipment - Google Patents

Abstract

This application relates to the technical field of data processing, and provides a method for calculating the temperature field, including: determining the first density of temperature sampling points in the first column; Density determines the number A of temperature sampling points between the first temperature sensor and the second temperature sensor; performs interpolation calculations to determine A temperature values according to the temperature values of the first temperature sensor and the second temperature sensor; determines the number of temperature sampling points in the first row The second density; determine the number B of temperature sampling points between the first temperature sampling point and the second temperature sampling point according to the second distance between the first temperature sampling point and the second temperature sampling point and the above-mentioned second density; according to the first temperature The temperature values of the sampling point and the second temperature sampling point are interpolated to determine B temperature values; and the temperature field of the computer room is determined according to the A temperature value and the B temperature value. This method can improve the efficiency of calculating the temperature field.

Description

Method and Electronic Equipment for Calculating Temperature Field

technical field

The present application relates to the technical field of data processing, in particular to a method for calculating a temperature field and electronic equipment.

Background technique

As we all know, the Internet Data Center (IDC) is a service platform with complete equipment (for example, a large number of servers), professional management, and perfect applications. Moreover, on the basis of this platform, IDC service providers It can provide customers with basic Internet platform services and various value-added services. For example, in industries such as the Internet, finance, industrial manufacturing, electric power, radio and television, and services, IDC can provide services for storing and processing huge amounts of data for various industries. Since a large number of servers in the IDC generate a lot of heat during work, in order to ensure the normal operation of the IDC, the temperature environment in the computer room where the servers are located needs to be maintained at a relatively constant temperature. In order to maintain a relatively constant temperature environment in the computer room, the cooling capacity, wind speed, cooling mode, and coordinated control of the computer room air conditioner should be adjusted according to the actual temperature of the computer room.

In order to accurately monitor the actual temperature changes in the computer room, a large number of temperature sensors are usually arranged in the computer room to collect temperature data at different locations in the computer room in real time. A large number of temperature sensors will increase the monitoring cost. Therefore, in order to reduce the monitoring cost, the temperature data collected by the actual temperature sensor (that is, the measured temperature data) and the simulated temperature data (that is, the calculated temperature data) are usually used to simulate the temperature field of the computer room. However, at present, the efficiency of calculating the temperature field based on the measured temperature data is very low.

Therefore, how to improve the efficiency of calculating the temperature field is an urgent problem to be solved.

Contents of the invention

The present application provides a method and electronic equipment for calculating a temperature field, which can improve the efficiency of calculating the temperature field.

In the first aspect, a method for calculating a temperature field is provided, the method is applied to a computer room provided with multiple temperature sensors, and the multiple temperature sensors are non-uniformly arranged on multiple rows of cabinets in the computer room, so A temperature sensor is respectively arranged at both ends of each row of cabinets in the machine room, and the plurality of temperature sensors are arranged in a dot matrix, and the temperature sensors arranged on the multi-row cabinets constitute a plurality of rows of the dot matrix, and the method Including: determining the first density of temperature sampling points in the first column, the first column being any column of the dot matrix; according to the first distance between the first temperature sensor and the second temperature sensor and the The first density of temperature sampling points determines the number A of temperature sampling points between the first temperature sensor and the second temperature sensor, where A is a positive integer, and the first temperature sensor and the second temperature sensor The sensors are two adjacent temperature sensors in the temperature sensors in the first column; interpolation operations are performed according to the temperature values of the first temperature sensor and the second temperature sensor to determine A temperature values; The second density of temperature sampling points, the first row of any row of the dot matrix; according to the second distance between the first temperature sampling point and the second temperature sampling point and the second temperature sampling point of the first row Density determines the number B of temperature sampling points between the first temperature sampling point and the second temperature sampling point, where B is a positive integer, and the first temperature sampling point and the second temperature sampling point are Two adjacent temperature sampling points in the first row of temperature sampling points, the first temperature sampling point is one of the plurality of temperature sensors or a sampling point obtained by the interpolation operation, and the second The temperature sampling point is one of the plurality of temperature sensors or the sampling point obtained by the interpolation operation; performing interpolation operation according to the temperature values of the first temperature sampling point and the second temperature sampling point to determine B temperature values ; Determine the temperature field of the equipment room according to the A temperature values and the B temperature values.

The foregoing method may be executed by an electronic device or a chip in the electronic device. The electronic equipment first calculates the temperature value (i.e., temperature data) between the adjacent temperature sensors in the column direction according to the temperature data collected by the temperature sensors on the cabinets in each column, that is, the interpolation operation in the column direction is performed first; then, according to the temperature collected by the temperature sensor Data and the temperature data obtained by the interpolation operation in the column direction, calculate the temperature data between the adjacent temperature sampling points in the row direction; since the interpolation operation in the column direction is completed, the adjacent columns in each row have temperature data, therefore, the interpolation When moving to the temperature data between two adjacent temperature sampling points, multiple sets of temperature sampling points (each set of temperature sampling points include two adjacent temperature sampling points) can be interpolated at the same time, without the need for sequential (that is, sequential ) to calculate the temperature value between two adjacent temperature sampling points, thereby improving the efficiency of the temperature field in the computer room.

Optionally, the determining the first density of temperature sampling points in the first column includes: obtaining the first length of the equipment room; determining a plurality of first numbers according to the plurality of columns of the lattice, the plurality of Each quantity in the first quantity is the number of temperature data collected by each column temperature sensor in the plurality of columns; calculate the least common multiple of the plurality of first quantities; calculate the least common multiple and the first length ratio to obtain the first density of temperature sampling points in the first column.

In this embodiment, the electronic device determines the least common multiple according to a plurality of first quantities, and determines the first density according to the least common multiple, so that the number of temperature data in each column in the dot matrix is the same, so that the electronic device is convenient for row-wise Fast interpolation.

Optionally, the determining the second density of the temperature sampling points in the first row includes: obtaining the second length and the number of resolutions of the equipment room, the direction where the first length is located and the direction where the second length is located The direction is vertical; calculate the ratio of the number of resolutions to the least common multiple to obtain the number of temperatures in a single row; calculate the ratio of the number of temperatures in a single row to the second length to obtain the second number of temperature sampling points in the first row density.

In this embodiment, the electronic device performs an interpolation operation on the temperature sampling points of each row in the dot matrix according to the second density of the temperature sampling points in the first row, so that the number of temperature data in each row of the dot matrix is the same, so that Perform quadratic interpolation on two adjacent temperature data between any two rows.

Optionally, among the plurality of temperature sensors, the number of temperature sensors located at the hot aisle of the equipment room is greater than or equal to the number of temperature sensors located at the cold aisle of the equipment room.

In this embodiment, because the temperature of the hot aisle is high, and the trend of temperature change is large (that is, the temperature change intensity of the hot aisle is high); while the temperature change of the cold aisle is small (that is, the temperature change intensity of the cold aisle is small), Therefore, deploying a large number of temperature sensors in the hot aisle can accurately monitor the actual situation of the temperature change at the highest temperature in the machine room, so as to accurately adjust the cooling mode of the refrigeration system.

Optionally, the temperature sensor at the hot aisle of the computer room is located at the highest temperature and the lowest temperature on the side of the hot aisle at the back of each row of cabinets in the computer room; the temperature sensor at the cold aisle of the computer room is located at the The back of each row of cabinets in the machine room is at the highest temperature on one side of the cold aisle.

In this embodiment, temperature sensors are deployed at the highest and lowest temperatures on the side of the hot aisle where the back of each row of cabinets is located, and at the highest temperature on the side of the cold aisle where the back of each row of cabinets is located, so as to accurately monitor the temperature in the equipment room. The variation of the temperature at the highest temperature is beneficial to improve the accuracy of the electronic equipment to calculate the temperature field based on the temperature data of the region with large temperature variation and the temperature data of the region with small temperature variation.

Optionally, the interpolation operation is a non-linear interpolation operation.

In this embodiment, compared with the linear interpolation algorithm, the accuracy of the method of calculating the temperature data between two adjacent temperature data by the non-linear interpolation algorithm in this application is higher.

In a second aspect, an electronic device is provided, including a processor and a memory, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the electronic device executes any one of the methods in the first aspect.

In a third aspect, a computer-readable storage medium is provided, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the method in any one of the first aspects.

For the beneficial effects of the second aspect and the third aspect of the present application, please refer to the beneficial effects of the first aspect.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the accompanying drawings that need to be used in the descriptions of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings in the following description are only for the present application For some embodiments, those of ordinary skill in the art can also obtain other drawings based on these drawings without paying creative efforts.

FIG. 1 is a top view of an irregular server room 100 in an embodiment of the present invention;

2 is a schematic diagram of the distribution of temperature sensors in the server room 100 in the embodiment of the present invention;

3 is a schematic diagram of the distribution of temperature sensors in another server room 100 in an embodiment of the present invention;

4 is a schematic flow chart of a method for calculating a temperature field in an embodiment of the present invention;

5 is a schematic diagram of calculated temperature data in the X direction of the region 101 in an embodiment of the present invention;

6 is a schematic diagram of calculated temperature data in the Y direction of the region 101 in an embodiment of the present invention;

FIG. 7 is a schematic structural diagram of an electronic device in an embodiment of the present invention.

Detailed ways

In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and/or components, but does not exclude one or more other Presence or addition of features, wholes, steps, operations, elements, components and/or collections thereof.

It should also be understood that the term "and/or" used in the description of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

In addition, in the description of the specification and appended claims of the present application, the terms "first", "second", "third" and so on are only used to distinguish descriptions, and should not be understood as indicating or implying relative importance.

Reference to "one embodiment" or "some embodiments" or the like in the specification of the present application means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Accordingly, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in other embodiments," etc., in various places in this specification are not necessarily all References to the same embodiment mean "one or more but not all" unless specifically stated otherwise. The terms "including", "comprising", "having" and variations thereof mean "including but not limited to", unless specifically stated otherwise.

In order to solve the problem of low efficiency in calculating the temperature field, the present application proposes a method for calculating the temperature field, which can improve the efficiency of calculating the temperature field.

The present application will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

The present application proposes a method for calculating a temperature field, which can be executed by an electronic device or a chip on the electronic device. The method is applied to a computer room provided with multiple temperature sensors, and the multiple temperature sensors are non-uniformly arranged on multiple rows of cabinets in the computer room, and a temperature sensor is provided at each row of cabinets in the computer room, and the multiple temperature sensors are arranged It is a dot matrix, and the temperature sensors arranged on the multi-column cabinets form multiple columns of the dot matrix. It should be understood that when the temperature sensor is deployed in the computer room, each point in the above-mentioned dot matrix represents the temperature sensor deployed at a single location in the computer room; Temperature data (i.e. temperature value).

Exemplarily, the above-mentioned computer room can be used to place servers and heat-generating equipment such as power amplifiers. It is very important to deploy multiple temperature sensors in the computer room to collect the indoor temperature, and adjust the outlet temperature, air volume, and cooling mode of the air conditioner in the computer room according to the actual temperature of the computer room. This application takes a computer room where multiple servers are placed (that is, a server computer room) as an example to illustrate the method for calculating the temperature field in the server computer room.

Fig. 1 shows a top view of an irregular server room 100, with the upper left corner of the top view as the coordinate origin O, an XOY plane Cartesian coordinate system is established; each square in Fig. 1 represents a single sub-cabinet; each row of cabinets includes Multiple sub-cabinets, each sub-cabinet is used to place a server; multiple servers are placed on the cabinets arranged in columns in the server room 100 .

10 rows of cabinets are placed in the server room 100, which are the 01st row of cabinets, the 02nd row of cabinets, the 03rd row of cabinets, ..., the 10th row of cabinets; each row of cabinets contains multiple sub-cabinets, and the multiple sub-cabinets are used for Place multiple servers. For example, the cabinet in row 01 contains 5 sub-cabinets. A total of 5 servers are placed in the 5 sub-cabinets, namely server 11, server 21, server 31, server 41 and server 51.

Dotted line 104 in Fig. 1 divides server room 100 into two regular areas, respectively area 101 and area 102, wherein, area 101 includes 4 rows of cabinets, and each row of cabinets places 5 servers; area 102 includes 6 rows of cabinets, each 3 servers are placed in a row of cabinets.

Since different servers have different heat generation (that is, different power consumption), the temperature variation trends of the surrounding areas of different rows of cabinets are different. When the service provider deploys temperature sensors on different rows of cabinets in the computer room 100, it will determine the deployment strategy according to the distribution of the actual high and low temperatures. The number of temperature sensors; a small number of temperature sensors can be deployed in areas with low temperature and small temperature changes (that is, small temperature changes).

Due to the different positions of the air inlets and outlets of the servers on different rows of cabinets, the attributes of the channels formed between different rows of cabinets are different. Among them, the attributes of the channels include cold aisles and hot aisles, and cold aisles refer to low temperature and high temperature. Channels with small changes, for example, the channel where the air inlet of the server is located is usually lower in temperature, usually between 16°C and 22°C; The channel temperature is usually higher, usually between 23°C and 35°C.

For example, as shown in Figure 2, the computer room 100 is divided into 12 channels according to the positions of the server air inlets and air outlets on different rows of cabinets, namely channel 1 (ie CH1), channel 2 (ie CH2), ... , Channel 12 (that is, CH12); the 12 channels include cold aisles and hot aisles; for example, if there are 5 servers placed on the cabinet in row 01, the left side is the air inlet of the server, and the right side is the server outlet. If there is a tuyere, CH1 is the cold aisle and CH2 is the hot aisle.

In an embodiment, among the plurality of temperature sensors, the number of temperature sensors located at the hot aisles of the equipment room is greater than or equal to the number of temperature sensors located at the cold aisles of the equipment room.

For example, as shown in Figure 2, temperature sensors are deployed in each channel in the computer room 100, but the number of sensors deployed in each channel is different. The number is small; the reason is that the temperature of the area where the hot aisle is located is high, and the temperature change is large; while the temperature change of the area where the cold aisle is located is small (that is, the temperature change intensity is small), therefore, in order to accurately obtain the temperature of the area where the hot aisle is located For actual temperature changes, service providers usually deploy a large number of temperature sensors in the hot aisle and relatively few temperature sensors in the cold aisle, so that the actual temperature change at the highest temperature in the computer room can be accurately monitored, thereby It is convenient to adjust the cooling mode of the refrigeration system accurately.

In addition, when deploying temperature sensors, service providers can set deployment strategies according to the power consumption of different servers; for the cabinets where servers with high power consumption are located, a large number of temperature sensors can be deployed; A smaller number of temperature sensors can be deployed. For example, in Figure 2, the power consumption of server 11 on the 01st row of cabinets is the largest (that is, the heat generation is the largest), and the power consumption of the other four servers is not much different and is less than the power consumption of server 11, and the 01st row of cabinets The air inlets of the servers are all on the left and the air outlets are on the right. At this time, CH1 is the cold aisle and CH2 is the hot aisle; two temperature sensors are deployed on the left side of the 01st row of cabinets to collect the temperature data of CH1 6 temperature sensors are deployed on the right side to collect the temperature data of CH2, wherein 3 temperature sensors are deployed on the sub-cabinet where the server 11 is located, wherein one temperature sensor is located at a certain position on the left side of the cabinet (for example, The lowest temperature on the left side), and the remaining two temperature sensors are located at the highest temperature on the right side of the cabinet; among the other four servers, one temperature sensor is deployed at the highest temperature on the right side of each server, and the left side of server 51 A temperature sensor is deployed at the lowest temperature.

In this embodiment, compared with the prior art where multiple temperature sensors are uniformly deployed around each cabinet, this application unevenly distributes the Different numbers of temperature sensors are deployed in each cabinet. Without increasing the cost of temperature sensors, it can not only accurately monitor the temperature data of areas with large temperature changes in the computer room, but also help improve the accuracy of calculating the temperature field of the entire computer room.

In another embodiment, the temperature sensors at the hot aisle of the computer room are located at the highest temperature and the lowest temperature at the back of each row of cabinets in the computer room on one side of the hot aisle; the temperature sensors at the cold aisle of the computer room are located at each row The back of the cabinet is at the highest temperature on the cold aisle side.

In order to find the area with the most severe heat in the computer room, when deploying temperature sensors to the cold aisle or hot aisle, the temperature sensor is usually deployed to the position with the highest temperature (that is, the highest temperature) in the cold aisle or hot aisle; in addition, in order to obtain heat Due to the actual situation of temperature changes at different positions in the aisle, the temperature sensor is usually deployed at the position with the lowest temperature in the hot aisle (that is, the lowest temperature); because the temperature at different positions on the back of a single cabinet is different, and the highest temperature on the back of a single cabinet The temperature at the highest temperature changes the most relative to the temperature at the lowest temperature. Therefore, if you want to calculate the temperature data between the highest temperature and the lowest temperature, you must use the highest temperature data collected by the temperature sensor at the highest temperature, and use The lowest temperature data collected by the temperature sensor at the lowest temperature can accurately calculate the temperature data at other positions between the highest temperature and the lowest temperature through interpolation operations.

Therefore, when the service provider deploys temperature sensors on different rows of cabinets, the deployment strategy is determined according to the aisle attributes on the left and right sides of different rows of cabinets; Deployed at the highest temperature on the back of each sub-cabinet on the side of the hot aisle; similarly, to collect the highest temperature of each sub-cabinet on the cold aisle, the temperature sensor at the cold aisle should be deployed on the back of the sub-cabinet on the side of the cold aisle The reason is that the overall average temperature of the area where the cold aisle is located is usually lower than that of the hot aisle; however, due to the different power consumption of different servers, the heat generated around the sub-racks where different servers are located is different; service providers deploy in cold aisles When using a temperature sensor, the temperature sensor will be deployed according to the temperature in the area where the cold aisle is located. Usually, the temperature sensor will be deployed at the highest temperature in the area where the cold aisle is located (for example, at the highest temperature on the back side of the cold aisle where the X sub-cabinet is located. deployment temperature sensor).

In addition, the number of temperature sensors actually arranged on each cold aisle or hot aisle must be greater than or equal to 2, and the starting position of each cold aisle or hot aisle (for example, the location where server 11 is located in the 01st case cabinet in Figure 2 sub-cabinet) and the end position (for example, the sub-cabinet where server 51 is located in the 01st cabinet in Figure 2) must deploy a temperature sensor respectively, so that each cold aisle or hot aisle will have two temperature sensors to record the temperature of the respective aisle. For the temperature data at the first and last positions, even if there is no temperature sensor deployed in the middle of each cold aisle or hot aisle except the first and last positions, the electronic device can calculate the temperature data collected by the temperature sensors at the first and last positions of each aisle through interpolation Temperature data at the middle position.

For example, as shown in Figure 3, there are five sub-cabinets on the cabinet in column 01, which are sub-cabinet X1, sub-cabinet X2, sub-cabinet X3, sub-cabinet X4, and sub-cabinet X5. Servers are placed on each sub-cabinet, and the server The air inlets are all on the left, and the air outlets are all on the right. The channel CH1 on the left is the cold aisle and CH2 is the hot aisle. When the service provider deploys the temperature sensor on the sub-cabinet X1, consider The heat is very large, and the temperature sensor a will be deployed at the highest temperature on the right back of the sub-cabinet X1 (that is, the 01st cabinet), and the temperature sensor b will be deployed at the lowest temperature on the right back of the sub-cabinet X1 (that is, the 01st cabinet) to collect the temperature data at the highest temperature and the lowest temperature on the CH2 side of the back of the sub-cabinet X1; another temperature sensor c is deployed at the highest temperature on the left back of the sub-cabinet X1 (that is, the 01st cabinet), To collect the temperature data of the highest temperature at the back of sub-cabinet X1 on the side of the cold aisle.

When deploying the temperature sensor on sub-cabinet X2, considering that the heat generated by the server placed on sub-cabinet X2 is smaller than that of the server placed on sub-cabinet X1, a temperature sensor d will be deployed in sub-cabinet X2 (that is, the ) at the highest temperature on the right side of the back (that is, the back of sub-cabinet X2 is on the side of CH2) to collect the temperature data at the highest temperature of the back of sub-cabinet X2 on the side of CH2; There is no need to deploy a temperature sensor at the highest temperature of the side and back (that is, the back of sub-cabinet X2 is on the side of CH1), because the temperature change in the area where the cold aisle CH1 is located is small. Therefore, only the back of the first cabinet X1 in column 01 needs to be on CH1 It is enough to deploy temperature sensor c at the highest temperature on one side, and a temperature sensor g at the highest temperature on the CH1 side on the back of cabinet X5 at the end of column 01; the temperature value at the middle position between sub-cabinet X1 and sub-cabinet X5, The temperature data collected by the temperature sensor c and the temperature sensor g can be obtained through an interpolation operation, thereby reducing the cost of deploying the temperature sensor.

Of course, without considering the cost, the temperature sensor can also be deployed at the highest temperature on the left side of the sub-cabinet X2 (that is, the 01st cabinet) (that is, the back of the sub-cabinet X2 is on the side of CH1), and this application does not do this Limitation; service providers can reasonably deploy the number of temperature sensors according to the cost of temperature sensors.

Similarly, a temperature sensor e is deployed at the highest temperature on the back of the sub-cabinet X3 (that is, the back of the sub-cabinet X3 is on the side of CH2) to collect the temperature data at the highest temperature on the back of the sub-cabinet X3 on the side of CH2; A temperature sensor f is deployed at the highest temperature on the back of the right side of the sub-cabinet X4 (that is, the back of the sub-cabinet X4 is on the side of CH2) to collect temperature data at the highest temperature on the back of the sub-cabinet X4 on the side of CH2; while in the sub-cabinet X5 A temperature sensor h is deployed at the highest temperature on the back of the right side (that is, the back of the sub-cabinet X5 is on the side of CH2) to collect the temperature data at the highest temperature of the back of the sub-cabinet X5 on the side of CH2, and, on the left side of the sub-cabinet X5 A temperature sensor h is deployed at the highest temperature on the back (that is, the back of the sub-cabinet X5 is on the CH1 side) to collect temperature data at the highest temperature on the back of the sub-cabinet X5 on the CH1 side.

In some embodiments, since a cold aisle or a hot aisle is formed between adjacent rows of cabinets, a row of temperature sensors may be shared between adjacent rows of cabinets. Generally, the temperature of the area where the air inlet of the server is located is relatively low, while the temperature of the area where the air outlet of the server is located is relatively high; for example, as shown in Figure 3, the channel CH2 formed on the right side of the 01st The air outlet of the upper server is on the right (that is, the air outlet of the server on the 01st cabinet is on the side of CH2), and the air inlet of the server on the 02nd cabinet is on the left (that is, on the side of CH2). Multiple temperature sensors are deployed at the highest temperature on the back of the right side of the 01 cabinet (that is, on the CH2 side at the back of the 01 cabinet), and no temperature sensor is deployed on the left side of the 02 cabinet (that is, on the CH2 side at the back of the 02 cabinet). The sensor (the reason is that the temperature at the back of the 02 cabinet on the CH2 side is lower than the temperature at the back of the 01 cabinet on the CH2 side), only needs to be on the right back of the 02 cabinet (that is, the back of the 02 cabinet is on the CH3 side) The temperature sensor can be deployed at the highest temperature. This deployment method can not only accurately collect temperature data of channels with large temperature changes in the equipment room, but also reduce the deployment cost of temperature sensors.

In one deployment strategy, service providers can follow the following rules when deploying temperature sensors to hot aisles: when the number N of temperature sensors to be deployed in each row of cabinets ≤ the number n of sub-cabinets in each row of cabinets, N temperature sensors should be deployed at the highest temperature on the back of a single cabinet (that is, the entire cabinet); when the number N of temperature sensors to be deployed in each row of cabinets > the number n of sub-cabinets in each row of cabinets, and, When the number N of temperature sensors that need to be deployed in each row of cabinets is ≤ 2 times the number n of sub-cabinets in each row of cabinets, the temperature of the back of each sub-cabinet on the hot aisle (that is, the back of each sub-cabinet is on the side of the hot aisle) One temperature sensor is deployed at the highest temperature, and the remaining N-n temperature sensors are deployed at the lowest temperature on the back of each sub-cabinet on the hot aisle (that is, the back of each sub-cabinet is on the side of the hot aisle).

For example, as shown in Figure 3, there are n=3 sub-cabinets on the 05th row of cabinets, which are respectively sub-cabinet Y1, sub-cabinet Y2, and sub-cabinet Y3, and servers are placed on each sub-cabinet, and the air outlets of the servers are all on the right side , the air inlets are all on the left side, and the channel CH6 on the left is a cold channel and CH7 is a hot channel; the service provider requires that a total of N=5 temperature sensors be deployed for the 05th row of cabinets; since n<N<2n (that is, 3<N <6), therefore, when the service provider deploys the temperature sensor on the sub-cabinet Y1, the temperature sensor r will be deployed at the highest point on the right back of the sub-cabinet Y1 (that is, the 05th cabinet) (that is, the back of the sub-cabinet Y1 is on the side of CH7). temperature, to collect the temperature data at the highest temperature on the back of sub-cabinet Y1 on the side of CH7. side) at the highest temperature; temperature sensor k is deployed at the highest temperature on the back of the right side of sub-cabinet Y3 (that is, the 05th cabinet) (that is, the back of sub-cabinet Y3 is on the side of CH7). The remaining 2 (i.e. N-n=5-3) temperature sensors q and temperature sensor p must be deployed at the beginning and end of the cold aisle CH6; the temperature sensor q is deployed at the highest temperature on the back of the cabinet Y1 on the side of CH6, and The temperature sensor p is deployed at the highest temperature on the side of CH6 at the back of cabinet Y3.

Since the temperature change at the highest temperature on the back of the cabinet is large (that is, the degree of temperature change is high), and the temperature change at the back of the cabinet at the lowest temperature is small (that is, the degree of temperature change is small), therefore, in this embodiment, by Temperature sensors are deployed at the highest and lowest temperature points on the side of the hot aisle where the back of each row of cabinets is located, and at the highest temperature on the side of the cold aisle where the back of each row of cabinets is located, to accurately monitor the temperature changes at the highest temperature in the computer room. Therefore, it is beneficial to improve the accuracy of the electronic device in calculating the temperature field according to the temperature data of the region with large temperature change and the temperature data of the region with small temperature change.

In combination with the deployment strategy of the temperature sensor in the server room 100, the method for calculating the temperature field will be described below in combination with an embodiment. Fig. 4 shows a schematic flow chart of a method for calculating the temperature field, the method comprising:

S101. Determine a first density of temperature sampling points in a first column, where the first column is any column of the dot matrix.

Exemplarily, as shown in FIG. 5 , the electronic device acquires temperature data collected by a temperature sensor deployed in the computer room 100, and performs interpolation calculation according to the temperature data collected by the temperature sensor. Since the server room 100 is an irregular area, to perform interpolation calculations based on temperature data collected by temperature sensors at different locations, it is necessary to first divide the temperature data collected by the temperature sensors into regions.

As shown in Figure 1, the dotted line 104 divides the computer room 100 into two areas, area 101 and area 102, and the electronic equipment conducts temperature fields in area 101 and area 102 according to the temperature data collected by the temperature sensors actually deployed in area 101 and area 102 respectively. Calculation; for the temperature data at the boundary position of area 101 and area 102 (i.e. the position shown by the dotted line 104), the temperature data collected by the temperature sensor deployed at the boundary position of area 1 and area 2 (i.e. both sides of the dotted line 104) can be obtained by interpolation .

Since the calculation methods of the temperature fields in the electronic equipment calculation area 101 and the area 102 are the same, this application only takes the temperature field in the electronic equipment calculation area 101 as an example, and the calculation of the temperature field in the area 102 can refer to the calculation of the temperature field in the area 101. I won't repeat them here.

Fig. 5 is a top view of area 101 under the two-dimensional Cartesian coordinate system XOY. This area 101 includes 4 rows of cabinets, each row of cabinets includes 5 sub-cabinets (shown in the grid in Fig. 5), and the sub-cabinets in area 101 constitute 5* 4 dot matrix; different numbers of temperature sensors are unevenly deployed on each row of cabinets; the temperature sensors deployed on the 4 rows of cabinets in area 101 are arranged in a dot matrix, and the temperature data collected by the temperature sensors deployed on the 4 rows of cabinets are also arranged in a Arranged in a dot matrix; the temperature data collected by the temperature sensors deployed on each row of cabinets is a column of dot matrix data. The temperature sensors deployed on each row of cabinets are used to collect temperature data at different locations in the area 101 .

The temperature sensors deployed in area 101 (shown by black solid circles in FIG. 5 ) collect temperature data at different locations, and a total of 5 channels of temperature data are collected. The position where the temperature sensor is located in Figure 5 indicates that there is temperature data measured by the temperature sensor at this position (i.e. the actual temperature data); and the temperature data at the position without the temperature sensor (i.e. shown by the black hollow circle in Figure 5) is to be based on the actual measurement The temperature data is calculated by interpolation.

The above-mentioned temperature sampling points are temperature data; the electronic device determines the first density of the temperature sampling points in the first column, that is, determines the number of temperature data within a unit distance of the first column. In one case, part of the temperature data in the first column is the temperature data collected by the temperature sensor, and the other part is obtained by interpolation according to the temperature data collected by the temperature sensor (ie, the measured temperature data).

The above-mentioned first column is any column in the dot matrix formed by the temperature sensors deployed on different rows of cabinets in the area 101. For example, the first column can be the temperature data collected by the temperature sensor in the A column in the area 101 (that is, the temperature data deployed on the channel CH1 The data collected by the temperature sensor), may also be the temperature data collected by the temperature sensor in column C in the area 101 (ie, the data collected by the temperature sensor deployed on the channel CH3).

In one embodiment, the first density of the temperature sampling points in the first column can be preset by the user. For example, if the user sets the first density to 4, there are only two temperature data collected by the temperature sensor in the first column. It is the temperature data X1 of the first position and the temperature data X2 of the last position in the first column. At this time, it is necessary to obtain the temperature data of the two positions between the first and last positions through interpolation. For example, first calculate the temperature data X3 between them through the temperature data X1 and the temperature data X2, and then calculate the temperature data X4 between them according to the temperature data X1 and the temperature data X3.

In another embodiment, determining the first density of temperature sampling points in the first column includes: obtaining the first length of the equipment room; determining multiple first quantities according to multiple columns of the lattice, among the multiple first quantities Each quantity is the number of temperature data collected by each column temperature sensor in multiple columns; calculate the least common multiple of multiple first quantities; calculate the ratio of the least common multiple to the first length to obtain the first column of temperature sampling points density.

As shown in Figure 5, in the present embodiment, the computer room is an area 101, and the first length of the area 101 is acquired, and the first length refers to the length of the area 101 in the X direction (i.e. the longitudinal length of the area 101); for example, the first length The length is 4 meters.

The above-mentioned first quantity is the number of temperature data collected by each column of temperature sensors. The dot matrix formed by the temperature sensors in the area 101 has 5 columns in total, which are the A column, the B column, the C column, the D column and the E column, wherein the temperature data collected by the two temperature sensors in the A column (i.e. 2 measured temperature data); temperature data collected by 6 temperature sensors in column B (that is, 6 measured temperature data); temperature data collected by 4 temperature sensors in column C (that is, 4 measured temperature data); column D Temperature data collected by 3 temperature sensors (that is, 3 measured temperature data); temperature data collected by 4 temperature sensors in column E (that is, 4 measured temperature data).

The electronic device calculates the least common multiple of the number of measured temperature data in columns A, B, C, D and E, that is, calculates the least common multiple of 2, 6, 4, 3 and 4, The least common multiple is 12.

The electronic device calculates the ratio of the least common multiple of 12 to the first length of 4 meters, and obtains that the first density of the temperature sampling points in the first column is 3 (that is, 12 divided by 3), that is, each column of the area 101 needs to have 3 temperatures per vertical unit distance data (ie 3 temperature data per meter).

In this embodiment, the electronic device determines the least common multiple according to a plurality of first quantities, and determines the first density according to the least common multiple, so that the number of temperature data in each column in the dot matrix is the same, so that the electronic device is convenient for row-wise Fast interpolation.

S102. Determine the number A of temperature sampling points between the first temperature sensor and the second temperature sensor according to the first distance between the first temperature sensor and the second temperature sensor and the first density of temperature sampling points in the first column, A is A positive integer, the first temperature sensor and the second temperature sensor are two adjacent temperature sensors in the first row of temperature sensors.

Exemplarily, the above-mentioned first distance is the distance projected on the X coordinate axis between the position where the first temperature sensor is deployed and the position where the adjacent second temperature sensor is deployed; because in actual deployment, the distance between the first temperature sensor and the adjacent The second temperature sensor is not necessarily on a straight line, but the first temperature sensor and the second temperature sensor may be near a straight line.

For example, as shown in Figure 5, taking the first column as the C column in Figure 5 as an example, the first temperature sensor is temperature sensor 1 and the second temperature sensor is temperature sensor 2 as an example, where the temperature sensor 1 is located The distance between the position and the position where the temperature sensor 2 is located is D1 (that is, the first distance is D1), wherein the first distance D1 is the distance between the position where the temperature sensor 1 is projected on the X axis and the position where the temperature sensor 2 is projected The absolute value of the difference between distances on the x-axis.

If the first density is 4, and the first distance D1 is 1 meter, then the number of temperature data required between the temperature sensor 1 and the temperature sensor 2 is D1*first density=1×4=4, except for both ends (i.e. In addition to the two temperature data collected by temperature sensor 1 and temperature sensor 2), the electronic device needs to calculate two more temperature data between the temperature data 1 collected by temperature sensor 1 and the temperature data 1 collected by temperature sensor 2 through multiple interpolation operations (that is, the number A=2 of the temperature sampling points that needs to be calculated is respectively the values of the temperature sampling points 5 and the temperature sampling points 6), that is, the number of points A that need to be interpolated between the temperature data 1 and the temperature data 2 is D1*first density- 2. The electronic device will divide the first distance D1 into 3 equal intervals (i.e. the number of interpolation points A+1=2+1), wherein the first section is the distance between the temperature sensor 1 and the temperature sensor 5, and the second section is the distance between the temperature sensor 1 and the temperature sensor 5. The first segment is the distance between the temperature sensor 5 and the temperature sensor 6, the third segment is the distance between the temperature sensor 6 and the temperature sensor 2, the above "*" means multiplication, and "-" means subtraction.

Similarly, the number of interpolation points A between temperature sensor 2 and temperature sensor 3 is 2 (that is, the first density * D2-2), that is, the number of temperature sampling points that need to be calculated is A=2, which are temperature sampling points 7 and temperature For the value of sampling point 8, the electronic device divides D2 into 3 segments (that is, the number of interpolation points A+1=2+1=3), and the temperature value at the middle end point needs to be based on the temperature data collected by temperature sensor 2 and temperature sensor 3. The temperature data 3 is obtained by performing multiple interpolation operations.

Similarly, the number of interpolation points A between the temperature sensor 3 and the temperature sensor 4 is 4 (that is, the first density * D3-2), that is, the number of temperature sampling points that need to be calculated is A=4, which are respectively temperature sampling points 9 to temperature For the value of sampling point 12, the electronic device divides D3 into 5 segments (that is, the number of interpolation points A+1=4+1=5), and the temperature value at the middle end point needs to be based on the temperature data collected by temperature sensor 3 and temperature sensor 4. The temperature data 4 is obtained by performing multiple interpolation operations.

S103, performing an interpolation operation according to the temperature values of the first temperature sensor and the second temperature sensor to determine A temperature values.

Exemplarily, the top view of the area 101 shown in FIG. 5 is in a two-dimensional Cartesian coordinate system XOY, where O is the coordinate origin, and the position of each temperature sensor in the area 101 can be represented by a two-dimensional coordinate; in addition, Each position in the temperature field of the region 101 can be represented by a two-dimensional coordinate. For example, the position coordinates of the temperature sensor 1 in XOY in Fig. 5 are T(x1, y1), where T represents the temperature data collected by the temperature sensor 1, and (x1, y1) is the position of the temperature sensor 1, where x1, y1 respectively represent the abscissa and ordinate values of the temperature sensor 1 in the coordinate system XOY, that is, the modulus of x1 in (x1, y1) |x1| represents the distance from the position (x1, y1) of the temperature sensor 1 to the y-axis, and The modulo |y1| of y1 in (x1, y1) represents the distance from the position (x1, y1) where the temperature sensor 1 is located to the x-axis.

为温度传感器1所在的位置(x1,y1)与温度传感器2所在的位置(x2,y2)之间的距离为点(x1,y1)与点(x2,y2)之间的距离。For example, the position of temperature sensor 1 is (x1, y1), the position of temperature sensor 2 is (x2, y2), and the absolute value of the difference between |x1| and |x2| (ie ||x1|-| x2||) is the distance between the temperature sensor 1 position (x1, y1) and the temperature sensor 2 position (x2, y2) respectively projected on the X-axis between the two temperature sensors; and ||y1|-| y2|| is the distance between the temperature sensor 1 position (x1, y1) and the temperature sensor 2 position (x2, y2) respectively projected on the Y axis between the two temperature sensors;

is the distance between the position (x1, y1) where the temperature sensor 1 is located and the position (x2, y2) where the temperature sensor 2 is located, and is the distance between the point (x1, y1) and the point (x2, y2).

FIG. 5 is only a method for establishing a coordinate system for the area 101. Of course, the coordinate origin can also be established in the middle of the area 101 or other positions. This application does not limit this, and an appropriate coordinate system can be established according to the actual scene. Of course, a three-dimensional coordinate system in space can also be established for the area 101. The three-dimensional coordinate system in space includes the X axis, the Y axis and the Z axis. In the three-dimensional coordinate system in space, the position of each temperature sensor in the coordinate system can use a (x, y, z) means; of course, the three-dimensional coordinate analysis of the region 101 can also be converted into a two-dimensional coordinate analysis, for example, the coordinate position (x, y, z) of each temperature sensor in the three-dimensional coordinate system of the space is projected on The coordinates on the XOY plane are (x, y), z=T(x, y), where (x, y) is the deployment position of each temperature sensor, and z=T(x, y) indicates that each temperature sensor Collected temperature data. It should be understood that the distance between different rows of cabinets and the distance between temperature sensors in the actual area 101 can be scaled in the same proportion in the coordinate system, and will not affect the calculation of the temperature field.

Before the electronic device performs difference calculation on the area 101, it will first preprocess the temperature data measured by the temperature sensor; for example, in some cases, the temperature sensor at a certain position in the area 101 fails, resulting in the temperature at this position not being collected Data, at this time, the temperature data collected before the failure will be used as the temperature data of the location.

For another example, the electronic device will normalize the temperature data collected by the temperature sensors at different positions in the area 101, and normalize all the temperature sensors at different heights to the temperature sensors at the same height, so that the top view of the area 101 can be obtained, And establish a two-dimensional Cartesian coordinate system XOY for the top view of the area 101, so that each temperature sensor can be represented by a two-dimensional coordinate (x, y), and the temperature data collected by each temperature sensor is represented by T(x, y ).

For another example, there is an edge area in area 101 where no temperature sensor is deployed (for example, some corridor areas, etc.), at this time, the electronic device can calculate the temperature field of the edge area based on the temperature data collected by two temperature sensors near the edge area ( That is, the temperature data of the edge region).

For another example, as mentioned above, the electronic device divides some irregular computer rooms (for example, server room 100) into a plurality of regular computer rooms (for example, area 101 and area 102), and calculates the temperature in each regular computer room respectively field.

For another example, the electronic device can perform some preprocessing on the display of the effect of the temperature field, such as color settings for different temperature values.

After the preprocessing is finished, the electronic device starts to perform interpolation calculation according to the first density, the temperature data collected by the first temperature sensor and the temperature data collected by the second temperature.

The above-mentioned interpolation operation includes linear interpolation operation and nonlinear interpolation operation, wherein, linear interpolation operation includes average value calculation and median calculation; for example, average value calculation is to determine the relative value by calculating the average value between two adjacent temperature data. The temperature value between two adjacent temperature data.

In one embodiment, a non-linear interpolation algorithm is used to calculate the temperature value between two adjacent temperature data. For example, the position of the first temperature sensor is (X _q , Y _p ), wherein, p and q respectively represent the column and row of the above-mentioned dot matrix where the first temperature sensor is located, and p is less than or equal to the total number of columns of the dot matrix (for example, Fig. 5 in area 101, p≤5), q is less than or equal to the least common multiple of the number of measured temperature data in each column (for example, in Figure 5 area 101, q≤12); between the first temperature sensor and the second temperature sensor The distance (that is, the first spacing) is D1, the first density is H1, and the number of points M1 that need a difference between the first temperature sensor and the second temperature sensor is D1*H1-2; the electronic device divides the first spacing D1 into M1 +1 equal division, M1 is a positive integer; the electronic device calculates the position where the temperature value needs to be calculated between the first temperature sensor and the second temperature sensor according to the formula (1), and the formula (1) is as follows:

X _q,t ＝X _q +t·(X _q+1 -X _q )/(M1+1) (1)

In the formula, X _q,t represents the longitudinal (i.e. column) coordinate of the interpolation position, X _q represents the longitudinal (i.e. column) coordinate of the first temperature sensor, X _q+1 represents the longitudinal (i.e. column) coordinate of the second temperature sensor ) coordinates, t indicates which interpolation point, and t is a positive integer from 1 to M1.

The electronic device calculates the temperature value between the first temperature sensor and the second temperature sensor according to the nonlinear interpolation algorithm shown in the formula (2); the formula (2) is as follows:

In the formula, T(X _q,t , Y _p ) is a calculated temperature value filled between the first temperature sensor and the second temperature sensor. h _q =T(X _q+1 ,Y _j )-T(X _q ,Y _j ), j represents the jth column, for example, j=p; M _q is calculated by formula (3), and M _q is M ₁ , M ₂ , ..., one of M _n , the formula (3) is as follows:

For example, in Fig. 5, temperature sensor 1 in column C is the first temperature sensor, and temperature sensor 2 is the second temperature sensor; wherein, the coordinate position of temperature sensor 1 is (X1, Y1), and the coordinate position of temperature sensor 2 is (X2, Y2), the distance between temperature sensor 1 and temperature sensor 2 (i.e. the first spacing) is D1=1, the first density is H1=4, the number of points that need difference between temperature sensor 1 and temperature sensor 2 M1 is D1*H1-2=2; the electronic device divides the first distance D1 into M1+1=3 equal parts; the electronic device calculates M1=2 calculated temperature data 5 between the temperature sensor 1 and the temperature sensor 2 and temperature data 6 (shown by the numbers in the hollow circles in Fig. 5); wherein, the electronic device calculates according to the temperature data 1 collected by the temperature sensor 1 and the temperature data 2 collected by the temperature sensor 2 through the formula (1) to the formula (3) The temperature data 5 is output; then the temperature data 6 is calculated through the temperature data 5 and the temperature data 2 through the formula (1) to the formula (3).

S104. Determine the second density of temperature sampling points in the first row, where the first row is any row of the dot matrix.

Exemplarily, the temperature data at different positions between two adjacent temperature sensors in the X-axis direction (that is, the column direction) have all been calculated, and then the electronic device calculates the Y direction (that is, the Horizontal) temperature data at different positions between two adjacent temperature data.

In one embodiment, the second density of temperature sampling points in the first row can be preset by the user. For example, as shown in FIG. 6, the user sets the second density to 3, and the temperature in column A in the second row Data 1, temperature data 3 in column C, temperature data 4 in column D, and temperature data 5 in column E are all temperature values obtained by interpolation in the X direction (ie column direction); and temperature data in column B 2 is the temperature value collected by the temperature sensor. The electronic device can simultaneously calculate the interpolated temperature value between two adjacent temperature values in the second row according to the second density, without first calculating the temperature value between temperature data 1 and temperature data 2, and then calculating temperature data 2 and temperature data 3, thereby improving the efficiency of interpolation in the Y direction (that is, the row direction). The reason is that after the interpolation operation in the X direction (that is, the column direction), the adjacent columns in each row have temperature values, therefore, the temperature data between adjacent columns can be calculated through the temperature data of adjacent columns. For example, column B and column C in the second row have temperature data 2 and temperature data 3 respectively. Therefore, the difference between temperature data 2 and temperature data 3 in the second row can be calculated by interpolation according to temperature data 2 and temperature data 3. The temperature value between (that is, calculate the temperature value between column B and column C in the second row).

In another embodiment, determining the second density of temperature sampling points in the first row includes: obtaining the second length and the number of resolutions of the computer room, where the direction of the first length is perpendicular to the direction of the second length; calculating The ratio of the number of resolutions to the above least common multiple is used to obtain the number of temperatures in a single row; the ratio of the number of temperatures in a single row to the second length is calculated to obtain the second density of temperature sampling points in the first row.

As shown in Figure 5, in the present embodiment, the computer room is an area 101, and the second length of the area 101 is obtained, and the second length refers to the length of the area 101 in the Y direction (ie, the lateral length of the area 101); for example, the second The length is 9 meters, wherein the X direction where the first length is located is perpendicular to the Y direction where the second length is located.

The above-mentioned resolution number is the number of temperature values required at different positions in the entire computer room (for example, area 101) set by the user according to the rendering effect of the later temperature field, that is, the above-mentioned resolution number is the number of temperature data in the X direction after the interpolation is completed (ie The sum of the number of points in the column direction) and the number of interpolation points in the Y direction (that is, the number of simulated temperature data obtained by electronic equipment through interpolation operations in the Y direction except the temperature data collected by the temperature sensor); The total number of points after the end of the interpolation in the column direction of the computer room. For example, there are 5 columns in the area 101. After the interpolation in the X direction, the total number of points is the product of the least common multiple and the total number of columns (that is, the total number of columns of the lattice); as shown in Figure 5 above After the column-wise interpolation in the middle area 101 is completed, the number of total temperature values (ie, temperature data) in the 5 columns is 5×12=60 (ie, the number of column-wise points is 60).

The above-mentioned single-line temperature quantity is the ratio of the resolution quantity to the least common multiple; the ratio of the single-line temperature quantity to the second length is the number of temperature data per unit distance in the Y direction (ie horizontal or row direction). The above-mentioned temperature quantity of a single row is the number of temperature data of each row after the electronic device interpolates the row direction; after the electronic device interpolates each row, the temperature data of each row are equal, which is convenient for the electronic device Two adjacent temperature data are interpolated. For example, row A has a total of 10 temperature data, and row B has a total of 10 temperature data. Row A is adjacent to row B. The electronic device is performing secondary temperature data on any column of row A and row B. During secondary interpolation (secondary column-wise interpolation), and during interpolation, the temperature data between the two temperature data of multiple columns in row A and row B can be interpolated at the same time, for example, the electronic device is While interpolating the temperature data T1 of row A of the column and the temperature data T2 of row B of the first column, the temperature data T3 of row A of the second column and row B of the second column can also be interpolated at the same time The temperature data T4 is interpolated, which can improve the efficiency of the secondary interpolation.

For example, the number of resolutions is 240, the least common multiple is 12, the second length is 5 meters, the number of single-line temperatures is 240 divided by 12 equals 20; the second density is 4 (that is, the number of single-line temperatures is 20 divided by the second length 5), That is, the number of temperature data per unit distance is 4.

In this embodiment, the electronic device performs an interpolation operation on the temperature sampling points of each row in the dot matrix according to the second density of the temperature sampling points in the first row, so that the number of temperature data in each row of the dot matrix is the same, thereby facilitating The electronic device performs quadratic interpolation on two adjacent temperature data between any two rows.

S105. Determine the number of temperature sampling points between the first temperature sampling point and the second temperature sampling point according to the second distance between the first temperature sampling point and the second temperature sampling point and the second density of the temperature sampling points in the first row B, B is a positive integer, the first temperature sampling point and the second temperature sampling point are two adjacent temperature sampling points in the temperature sampling points of the first row, and the first temperature sampling point is one or more of the temperature sensors The sampling point obtained by interpolation operation, the second temperature sampling point is one of the multiple temperature sensors or the sampling point obtained by interpolation operation.

Exemplarily, the above-mentioned second distance is the projected distance between the first temperature sampling point and the second temperature sampling point on the Y coordinate axis; the first temperature sampling point can be the data collected by the temperature sensor, or the temperature obtained by interpolation calculation data. The second temperature sampling point may also be data collected by a temperature sensor, or temperature data obtained through interpolation calculation.

For example, taking the second row in Figure 6 as an example, the first temperature sampling point 1 is the temperature data obtained by interpolation operation and the second temperature sampling point 2 is the temperature data collected by the temperature sensor, wherein the first temperature sampling point 1 and the second temperature sampling point The distance between the two temperature sampling points 2 is d1 (that is, the second distance is d1), wherein the second distance d1 is the distance between the projection of the first temperature sampling point 1 on the Y axis and the projection of the second temperature sampling point 2 on the Y axis The absolute value of the difference between the distances.

If the second density is 4, and the second distance d1 is 0.76 meters, then the number of temperature data required between the first temperature sampling point 1 and the second temperature sampling point 2 is d1*second density=0.76×4=3.04, Except for the endpoints on both sides (namely, the first temperature sampling point 1 and the second temperature sampling point 2), the electronic device needs to calculate another one between the first temperature sampling point 1 and the second temperature sampling point 2 through one interpolation operation. Temperature data (that is, the number B=1 of temperature sampling points that needs to be calculated, that is, the value of temperature sampling point 6); that is, the number B of temperature sampling points between the first temperature sampling point and the second temperature sampling point (ie, the number of interpolation points) It is d1*second density-2. The electronic device will divide the second interval d1 into 2 sections (that is, the number of interpolation points B+1=1+1) with equal distances, wherein the first section is the interval between the first temperature sampling point 1 and the temperature sampling point 6 Distance, the second paragraph is the distance between the temperature sampling point 6 and the second temperature sampling point 2.

Similarly, the number of points to be interpolated between the second temperature sampling point 2 and the third temperature sampling point 3 is 3 (i.e. the second density*d2-2), that is, the number of temperature sampling points to be calculated B=3, respectively For the values of sampling point 7, temperature sampling point 8, and temperature sampling point 9, the electronic device divides d2 into 4 segments (that is, the number of interpolation points B+1=3+1=4), and the temperature value at the middle end point needs to be sampled according to the second temperature Point 2 and the third temperature sampling point 3 are obtained by performing multiple interpolation operations.

Similarly, the number of points to be interpolated between the third temperature sampling point 3 and the fourth temperature sampling point 4 is 3 (i.e. the second density*d3-2), that is, the number of temperature sampling points to be calculated B=3, respectively For the values of sampling point 10, temperature sampling point 11, and temperature sampling point 12, the electronic device divides d3 into 4 segments (that is, the number of interpolation points B+1=3+1=4), and the temperature value at the middle end point needs to be sampled according to the third temperature Point 3 and the fourth temperature sampling point 4 are obtained by performing multiple interpolation operations.

Similarly, the number of points to be interpolated between the fourth temperature sampling point 4 and the fifth temperature sampling point 5 is 2 (i.e. the second density*d4-2), that is, the number of temperature sampling points to be calculated B=2, respectively For the value of sampling point 13 and temperature sampling point 14, the electronic device divides d4 into 3 segments (that is, the number of interpolation points B+1=2+1=3), and the temperature value at the middle end point needs to be based on the fourth temperature sampling point 4 and the fifth The temperature sampling point 5 is obtained by performing multiple interpolation operations.

S106, performing an interpolation operation according to the temperature values of the first temperature sampling point and the second temperature sampling point to determine B temperature values.

Exemplarily, the electronic device starts to perform difference calculation according to the second density, the first temperature sampling point and the second temperature sampling point. The first temperature sampling point and the second temperature sampling point are two adjacent temperature sampling points in the first row of temperature sampling points.

For example, the position of the first temperature sampling point is (X _q , Y _p ), wherein, p and q respectively represent the column and row of the above-mentioned dot matrix where the first temperature sensor is located, and p is less than or equal to the total number of columns of the dot matrix (for example, In Figure 5 area 101, p≤5), q is less than or equal to the least common multiple of the number of the measured temperature data of each column (for example, in Figure 5 area 101, q≤12); between the first temperature sensor and the second temperature sensor The distance (that is, the first spacing) is d1, the second density is H2, and the number of points M2 that needs a difference between the first temperature sampling point and the second temperature sampling point is d1*H2-2; the electronic device divides the second spacing d1 Divided into M2+1 equal parts, M2 is a positive integer; the electronic device calculates the position where the temperature value needs to be calculated between the first temperature sampling point and the second temperature sampling point according to the formula (4), and the formula (4) is as follows:

Y _p,k = Y _p +t·(Y _p+1 -Y _p )/(M2+1) (4)

In the formula, Y _pk represents the horizontal (ie row direction) coordinate of the interpolation position, Y _p represents the horizontal (ie row direction) coordinate of the first temperature sampling point, and Y _p+1 represents the horizontal (ie row direction) coordinate of the second temperature sampling point, k indicates which interpolation point, t is a positive integer from 1 to M2.

The electronic device calculates the temperature value between the first temperature sampling point and the second temperature sampling point according to the nonlinear interpolation algorithm shown in formula (5); formula (5) is as follows:

In the formula, T(X _q , Y _p,k ) is the calculated temperature value filled between the first temperature sampling point and the second temperature sampling point. h _p =T(X _q ,Y _p+1 )-T(X _q ,Y _p ); M _p is calculated by the above formula (3), and M _p is M ₁ , M ₂ ,...,M _n One.

Such as, in Fig. 6, temperature sampling point 1 is the first temperature sampling point in the second row and column, and temperature sampling point 12 is the second temperature sampling point; Wherein, the coordinate position of temperature sampling point 1 is (X1, Y1), temperature sampling point The coordinate position of point 2 is (X2, Y2), the distance between temperature sampling point 1 and temperature sampling point 2 (ie the second distance) is d1=1, the second density is H2=3, temperature sampling point 1 and temperature The number of points M2 that need a difference between sampling points 2 is d1*H2-2=1; the electronic device divides the second distance d1 into M2+1=2 equal parts; the electronic device calculates the temperature sampling point 1 and the temperature sampling point 2 Between M2=1 calculated temperature data 6 (i.e. shown by the numbers in the hollow circle in Figure 6); wherein, the electronic equipment passes the formula (3) to the formula (5) according to the temperature sampling point 1 and the temperature sampling point 2 Calculate the temperature data6.

In this embodiment, compared with the linear interpolation algorithm, the accuracy of the method of calculating the temperature value between two adjacent temperature data by using the nonlinear interpolation algorithm in this application is higher.

S107. Determine the temperature field of the equipment room according to the A temperature value and the B temperature value.

Exemplarily, the electronic device obtains all the temperature data of the area 101 and the area 102 according to the temperature data collected by the A temperature value (ie temperature data), the B temperature value and the temperature sensor; all the temperature data constitute the temperature of the entire server room 100 field; the electronic device colors different temperature values according to the values of all the temperature data to obtain the temperature field of the server room 100 . The temperature field of the server room 100 may be a two-dimensional plane temperature field or a three-dimensional display temperature field. In the two-dimensional plane temperature field, each temperature data is filled with tiny color cells to form a two-dimensional plane temperature field. In the three-dimensional temperature field XYZ, the temperature value of each temperature data projected on the XOY plane coordinate system area is T(x, y), where the size of the temperature value T(x, y) is determined by the coordinate distance on the Z axis and Cube tiny color cells represent together.

To sum up, the electronic equipment first calculates the temperature value (ie, temperature data) between the adjacent temperature sensors in the column direction based on the temperature data collected by the temperature sensors on the cabinets in each column, that is, the interpolation operation in the column direction is performed first; then, according to The temperature data collected by the temperature sensor and the temperature data obtained by the interpolation operation in the column direction are used to calculate the temperature data between the adjacent temperature sampling points in the row direction; after the interpolation operation in the column direction is completed, the adjacent columns in each row have temperature data , therefore, when interpolating the temperature data between two adjacent temperature sampling points, multiple groups of temperature sampling points (each group of temperature sampling points include two adjacent temperature sampling points) can be interpolated at the same time without The temperature values between two adjacent temperature sampling points are calculated sequentially (that is, sequentially), thereby improving the efficiency of the temperature field of the computer room.

FIG. 7 shows a schematic structural diagram of an electronic device provided by the present application. The dotted line in Fig. 7 indicates that the unit or the module is optional. The electronic device 700 may be used to implement the methods described in the foregoing method embodiments. The electronic device 700 may be a server or a chip.

The electronic device 700 includes one or more processors 701, and the one or more processors 701 can support the electronic device 700 to implement the method in the method embodiment corresponding to FIG. 4 . Processor 701 may be a general purpose processor or a special purpose processor. For example, the processor 701 may be a central processing unit (Central Processing Unit, CPU). The CPU can be used to control the electronic device 700, execute software programs, and process data of the software programs. The electronic device 700 may also include a communication unit 705, configured to implement input (reception) and output (send) of signals.

For example, the electronic device 700 may be a chip, and the communication unit 705 may be an input and/or output circuit of the chip, or the communication unit 705 may be a communication interface of the chip, and the chip may serve as a component of the electronic device.

For another example, the communication unit 705 may be a transceiver of the electronic device 700 , or the communication unit 705 may be a transceiver circuit of the electronic device 700 .

The electronic device 700 may include one or more memories 702, on which a program 704 is stored, and the program 704 may be run by the processor 701 to generate instructions 703, so that the processor 701 executes the methods described in the above method embodiments according to the instructions 703. Optionally, data may also be stored in the memory 702 . Optionally, the processor 701 may also read the data stored in the memory 702, the data may be stored in the same storage address as the program 704, and the data may also be stored in a different storage address from the program 704.

The processor 701 and the memory 702 may be set separately, or may be integrated together, for example, integrated on a system-on-chip (System On Chip, SOC) of an electronic device.

For a specific manner of executing the method for calculating the temperature field by the processor 701, reference may be made to relevant descriptions in the method embodiments.

It should be understood that the steps in the foregoing method embodiments may be implemented by logic circuits in the form of hardware or instructions in the form of software in the processor 701 . The processor 701 may be a CPU, a digital signal processor (Digital Signal Processor, DSP), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, such as discrete gates, transistor logic devices or discrete hardware components .

The present application also provides a computer program product, which implements the method in any method embodiment in the present application when the computer program product is executed by the processor 701 .

The computer program product can be stored in the memory 702, such as a program 704, and the program 704 is finally converted into an executable object file that can be executed by the processor 701 through processes such as preprocessing, compiling, assembling and linking.

The present application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a computer, the method of any method embodiment in the present application is implemented. The computer program may be a high-level language program or an executable object program.

The computer readable storage medium is, for example, the memory 702 . The memory 702 may be a volatile memory or a nonvolatile memory, or, the memory 702 may include both a volatile memory and a nonvolatile memory. Among them, the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (ProgrammableROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electrically erasable In addition to programmable read-only memory (Electrically EPROM, EEPROM) or flash memory. The volatile memory may be Random Access Memory (RAM), which acts as an external cache. By way of illustration and not limitation, many forms of RAM are available such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (Synchronous DRAM, SDRAM) ), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous connection dynamic random access memory (SynchLink DRAM, SLDRAM) And direct memory bus random access memory (Direct Rambus RAM, DRRAM).

Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process and technical effects of the devices and equipment described above can refer to the corresponding processes and technical effects in the foregoing method embodiments, here No longer.

In the several embodiments provided in this application, the disclosed systems, devices and methods may be implemented in other ways. For example, some features of the method embodiments described above may be omitted, or not implemented. The device embodiments described above are only illustrative, and the division of units is only a logical function division. In actual implementation, there may be other division methods, and multiple units or components may be combined or integrated into another system. In addition, the coupling between the various units or the coupling between the various components may be direct coupling or indirect coupling, and the above coupling includes electrical, mechanical or other forms of connection.

The above embodiments are only used to illustrate the technical solution of the present application, not to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: they can still modify the technical solutions described in the aforementioned embodiments, or perform equivalent replacements for some of the technical features, and these Any modification or replacement that does not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application shall be included within the protection scope of the present application.

Claims (8)

1. A method for calculating the temperature field, characterized in that, the method is applied to a computer room provided with a plurality of temperature sensors, and the plurality of temperature sensors are non-uniformly arranged on multiple columns of cabinets in the computer room, so A temperature sensor is respectively arranged at both ends of each row of cabinets in the machine room, and the plurality of temperature sensors are arranged in a dot matrix, and the temperature sensors arranged on the multi-row cabinets constitute a plurality of rows of the dot matrix, and the method include: determining a first density of temperature sampling points in a first column, where the first column is any column of the dot matrix; determining the number of temperature sampling points between the first temperature sensor and the second temperature sensor according to a first distance between the first temperature sensor and the second temperature sensor and a first density of temperature sampling points in the first column A, the A is a positive integer, and the first temperature sensor and the second temperature sensor are two adjacent temperature sensors in the first row of temperature sensors; performing an interpolation operation according to the temperature values of the first temperature sensor and the second temperature sensor to determine A temperature values; determining a second density of temperature sampling points in the first row, the first row being any row of the dot matrix; Determine the temperature between the first temperature sampling point and the second temperature sampling point according to the second distance between the first temperature sampling point and the second temperature sampling point and the second density of the temperature sampling points in the first row The number B of sampling points, the B is a positive integer, the first temperature sampling point and the second temperature sampling point are two adjacent temperature sampling points in the first row of temperature sampling points, the The first temperature sampling point is one of the plurality of temperature sensors or a sampling point obtained by the interpolation operation, and the second temperature sampling point is one of the plurality of temperature sensors or a sampling point obtained by the interpolation operation point; performing an interpolation operation according to the temperature values of the first temperature sampling point and the second temperature sampling point to determine B temperature values; A temperature field of the equipment room is determined according to the A temperature values and the B temperature values. 2. The method according to claim 1, wherein said determining the first density of the temperature sampling points of the first column comprises: Obtain the first length of the machine room; A plurality of first quantities are determined according to a plurality of columns of the dot matrix, and each first quantity in the plurality of first quantities is the number of temperature data collected by each column temperature sensor in the plurality of columns; calculating a least common multiple of the plurality of first quantities; calculating the ratio of the least common multiple to the first length to obtain a first density of temperature sampling points in the first column. 3. The method according to claim 2, wherein said determining the second density of the temperature sampling points of the first row comprises: Acquiring the second length and the number of resolutions of the computer room, where the direction of the first length is perpendicular to the direction of the second length; Calculating the ratio of the number of resolutions to the least common multiple to obtain the number of single-row temperatures; calculating the ratio of the number of temperatures in the single row to the second length to obtain the second density of temperature sampling points in the first row. 4. The method according to any one of claims 1 to 3, characterized in that, among the plurality of temperature sensors, the number of temperature sensors located at the hot aisle of the machine room is greater than or equal to the number of the temperature sensors located at the cold aisle of the machine room. The number of temperature sensors at the channel. 5. The method according to claim 4, wherein the temperature sensor at the hot aisle of the machine room is located at the highest temperature and the lowest temperature on the side of the hot aisle at the back of each row of cabinets in the machine room; The temperature sensor at the cold aisle of the machine room is located at the highest temperature on the back of each row of cabinets in the machine room on one side of the cold aisle. 6. The method according to any one of claims 1 to 3, characterized in that the interpolation operation is a non-linear interpolation operation. 7. An electronic device, characterized in that the electronic device comprises a processor and a memory, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the electronic device executes any one of claims 1 to 6 method described in the item. 8. A computer-readable storage medium, characterized in that, a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the processor executes the method described in any one of claims 1 to 6. method.

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