Strategy linkage method of on-demand refrigeration monitoring system

Abstract

The invention discloses a strategy linkage method of an on-demand refrigeration monitoring system, which comprises a management server, a monitoring software module, an acquisition device and a refrigeration device, the monitoring software comprises a strategy linkage mode, and a method used by the strategy linkage mode comprises the following steps: refrigerating an area with an over-high heat degree by automatically controlling the refrigeration device; the power consumption of the refrigeration equipment in a cycle is calculated according to the rated power and the running time of the refrigeration equipment, the monitoring software integrates the acquired data volume into a data model for packaging, and the data is recorded through multiple strategy linkage to form a data model according to different environments, so that the power consumption of the refrigeration equipment is calculated. A plurality of data models are compared with one another, the data model with the lowest power consumption of the refrigeration equipment is obtained, specific energy-saving values under various energy-saving schemes are calculated, monitoring and regulation are carried out according to the energy-saving values, the requirement for refrigeration according to needs is met, local hot spots are cooled, and the method is suitable for being used in a data machine room monitoring system or a monitoring method.

Description

Technical Field

[0001] The invention relates to the technical field of energy saving in computer rooms, and in particular to a strategy linkage method for a demand-based refrigeration monitoring system used in a data computer room monitoring system. Background Art

[0002] Data centers are typical energy consumers, and "three parts construction, seven parts management" has become the collective consensus of the industry. At present, the cooling method used in conventional data rooms is the rotation air supply mode. The operation and maintenance personnel will increase the cooling capacity of precision air conditioners to reduce the heat generation of equipment. However, the cost of this method of reducing heat generation is that the overall temperature needs to be lowered. In fact, except for the high temperature in some places, other locations do not need to be cooled. With the popularization of intelligent systems, refined management has become the focus. On the basis of ensuring the closed-loop operation of the business, it is necessary to provide measurement, statistics, benchmarking, diagnosis, control, monitoring and operation and maintenance for the operating load, energy efficiency, efficiency improvement, cost optimization and other needs of each subsystem of the data center, so as to achieve transparent and visual management. Therefore, we propose a strategy linkage method for the demand-based cooling monitoring system for the data room monitoring system or monitoring method to solve the above-mentioned problems. Summary of the invention

[0003] The object of the present invention is to provide a strategy linkage method for a demand-based cooling monitoring system for a data room monitoring system or monitoring method, so as to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A strategy linkage method for a demand-based refrigeration monitoring system includes a management server, a monitoring software module, a collection device and a refrigeration device, the monitoring software includes a strategy linkage method, and the strategy linkage method uses a method including automatically controlling the refrigeration device to refrigerate an overheated area, and recording the startup and operation time of the refrigeration device, and calculating the power consumption of the refrigeration device within a cycle based on the rated power and operation time of the device, and the monitoring software integrates the above acquired data into a data model for packaging;

[0006] The monitoring software integrates the above acquired data into a data model for packaging. According to different environments, the monitoring software that has just started to run does not have a data model. After multiple policy linkages, the data is recorded to form a data model. Multiple data models are compared with each other to obtain the data model with the lowest power consumption of the refrigeration equipment.

[0007] During the operation of the monitoring software, a dynamic tuning strategy of "large to small" is adopted. The temperature of the refrigeration equipment is first adjusted over a large range, and then the temperature is gradually tried to be lowered until the solution with the lowest power consumption of the refrigeration equipment is obtained under the same cooling effect. Combined with traditional refrigeration solutions, the specific energy-saving values ​​under various energy-saving solutions are calculated, and the energy-saving values ​​are used for monitoring and regulation. After adopting the energy-saving model, the requirements of on-demand cooling are realized to cool down local hot spots.

[0008] The acquisition equipment includes a temperature sensor and a thermal imaging camera, and the refrigeration equipment includes a precision air conditioner, a fresh air fan and an intelligent floor. The temperature sensor is used to check the temperature and humidity of the environment, and the thermal imaging camera is used to check the distribution of hot spots in the area. The precision air conditioner, fresh air fan and intelligent floor are used to adjust the air volume and balance the temperature within the area.

[0009] The intelligent floor comprises an adjustment and display panel (1), a high-strength floor grille (2) is arranged on the front wall of the adjustment and display panel (1), an EC high-voltage brushless fan (3) is arranged on the back wall of the adjustment and display panel (1), a core processing module (4) is arranged on one side of the EC high-voltage brushless fan (3), the core processing module (4) is arranged on the back wall of the adjustment and display panel (1), a dual power interface (5) is arranged on the core processing module (4), a Lan communication port (6) is arranged on one side of the dual power interface (5), the Lan communication port (6) is arranged on the core processing module (4), and a temperature control perforator (7) is arranged on the adjustment and display panel (1);

[0010] The method also includes using temperature and humidity sensors to detect the average temperature within the data room area, using thermal imaging cameras to detect the distribution of cabinet hot spots in the data room area, turning on precision air conditioning in areas where the average temperature is too high and using fresh air fans to evenly dissipate heat, and using smart floors for targeted heat dissipation in areas where some hot spots are too high.

[0011] A group of threaded sleeves (8) are arranged at the four corners of the back wall of the adjustment and display panel (1); a group of screw rods (9) are threadedly connected inside the multiple groups of threaded sleeves (8); two groups of cross bars (10) are arranged at the other ends of the multiple groups of screw rods (9); multiple groups of connecting rods (11) are arranged between the two groups of cross bars (10); support frames (12) are arranged on the end walls of the multiple groups of connecting rods (11) and the cross bars (10); multiple groups of supporting columns (13) are arranged on the side walls of the multiple groups of connecting rods (11); Multiple groups of support columns (13) are evenly spaced on the side walls of multiple groups of connecting rods (11); a group of support seats (14) are arranged on the other end faces of multiple groups of support columns (13); multiple groups of connecting rods (11) are evenly spaced on two groups of cross bars (10); one end of multiple groups of screw rods (9) is provided with a rotating rod (15); the other ends of multiple groups of rotating rods (15) pass through the cross bar (10) and are connected to a group of rotating handles (16); multiple groups of anti-slip strips are arranged on the outer walls of multiple groups of rotating handles (16).

[0012] The method also includes the front-end temperature sensor and thermal imaging camera continuously collecting data, the front-end collection device analyzes the data signals output by the temperature sensor and the thermal imaging camera, and transmits them back to the management server monitoring software for centralized collection in real time. The monitoring software completes the regular storage of real-time data with one data set per minute, and dynamically determines the data with excessive instantaneous fluctuations as key data storage.

[0013] The calculation, including the initial heat load calculation formula, is as follows:

[0014] (3) Equipment heat load Q1 = P × η1 × η2 × η3 (kW), where P is the total power consumption of various equipment in the room (kW), η1: simultaneous use coefficient, η2: utilization coefficient, η3: load uniformity coefficient. Usually, η1, η2, and η3 are between 0.6 and 0.8. Considering the redundancy of cooling capacity, η1 × η2 × η3 is usually set to 0.8.

[0015] (4) Heat load of lighting in the computer room

[0016] Q2 = (C × S) / 1000 (KW), C: illumination of the computer room. Generally, the illumination of the computer room should be greater than 200lx, and its power consumption is about 20W / ㎡. S: area of ​​the computer room.

[0017] Q = cm(T1-T2), where Q is the total cooling capacity, C is the specific heat capacity, M is the mass, and T is the temperature.

[0018] The total cooling capacity required on site is obtained through the initial formula. The system software monitors the operating status of the on-site environment in real time through thermal imaging cameras and temperature and humidity sensors, obtains actual values ​​and compares them with the results calculated by the initial formula, and gradually optimizes and controls the air volume of the smart floor, the speed of the fresh air fan, and the cooling capacity of the air conditioner.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] The strategy linkage method of this demand-based cooling monitoring system uses a data room monitoring system or a monitoring method, so that the data room monitoring system or the monitoring method can be implemented to adopt a reasonable and effective digital strategy after operation, and after the use time increases, the asset configuration of the data center is further optimized, the energy-saving potential is stimulated, the energy consumption of the facility equipment is reduced, and the overall energy efficiency is improved; the model is established by the method of automatic temperature adjustment of the cold channel of the data room, the actual heating situation is recorded, and the dynamic temperature adjustment and refrigeration are formed into basic data, and different constant temperature models are quoted according to the hot spot distribution in different scenes, so as to achieve dynamic and efficient energy saving, and provide measurement, statistics, benchmarking, diagnosis, control, monitoring and operation and maintenance, etc. The present invention can be widely used in the field of energy-saving technology of computer rooms for a long time, effectively save energy consumption, and achieve true demand-based cooling. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the structure of the monitoring software in the present invention.

[0022] Figure 2 It is a schematic diagram of the operation of the monitoring software in the present invention.

[0023] Figure 3 It is a structural schematic diagram of the smart floor in the present invention.

[0024] Figure 4 It is a structural schematic diagram of the adjustment and display panel in the present invention.

[0025] Figure 5 for Figure 4 A is a schematic diagram of the enlarged structure.

[0026] Figure 6 It is a schematic diagram of the structure of the EC high-voltage brushless blower in the present invention.

[0027] Figure 7 This is a diagram showing the distribution of hot spots in the area viewed by the thermal imaging camera in the present invention.

[0028] Figure 8 This is a schematic diagram of a circuit board of a core processing module on the smart floor of the present invention.

[0029] Fig. 9 This is a principle block diagram of the digital display temperature and humidity controller in the present invention.

[0030] Fig.10 This is a flowchart of the setting workflow of the intelligent floor block of the present invention.

[0031] Among them: 1. Adjustment and display panel; 2. High-strength floor grille; 3. EC high-voltage brushless fan; 4. Core processing module; 5. Dual power supply interface; 6. Lan communication port; 7. Temperature control sensor; 8. Threaded sleeve; 9. Screw; 10. Crossbar; 11. Connecting rod; 12. Support frame; 13. Support column; 14. Support seat; 15. Turning rod; 16. Turning handle. DETAILED DESCRIPTION

[0032] In one embodiment, Figure 1-Figure 10 As shown, a strategy linkage method of a demand-based cooling monitoring system is used for a data room monitoring system or a monitoring method, including a management server, a monitoring software module, a collection device and a refrigeration device, the collection device includes a temperature sensor and a thermal imaging camera, the refrigeration device includes a precision air conditioner, a fresh air fan and a smart floor, the temperature sensor is used to check the temperature and humidity of the environment, the thermal imaging camera is used to check the distribution of hot spots in the area, and the temporary precision air conditioner, the fresh air fan and the smart floor form a multi-point multi-encirclement controlled circulating hot and cold air source, which is used to adjust the air volume and balance the temperature within the area;

[0033] The intelligent floor comprises an adjustment and display panel 1, a high-strength floor grille 2 is arranged on the front wall of the adjustment and display panel 1, an EC high-voltage brushless fan 3 is arranged on the back wall of the adjustment and display panel 1, a core processing module 4 is arranged on one side of the EC high-voltage brushless fan 3, the core processing module 4 is arranged on the back wall of the adjustment and display panel 1, a dual power interface 5 is arranged on the core processing module 4, a Lan communication port 6 is arranged on one side of the dual power interface 5, and the Lan communication port 6 is arranged on the core processing module 4, and a temperature control perforator 7 is arranged on the adjustment and display panel 1; a group of threaded sleeves 8 are arranged at the four corners of the back wall of the adjustment and display panel 1, and the inner parts of the multiple groups of threaded sleeves 8 are all threadedly connected. A group of screw rods 9 are connected, and two groups of cross bars 10 are arranged at the other end of the multiple groups of screw rods 9. Multiple groups of connecting rods 11 are arranged between the two groups of cross bars 10, and support frames 12 are arranged on the two end walls of the multiple groups of connecting rods 11 and the cross bars 10; multiple groups of support columns 13 are arranged on the side walls of the multiple groups of connecting rods 11 at equal distances, and a group of support seats 14 are arranged on the other end faces of the multiple groups of support columns 13; multiple groups of connecting rods 11 are arranged on the two groups of cross bars 10 at equal distances; one end of the multiple groups of screw rods 9 is provided with a rotating rod 15, and the other end of the multiple groups of rotating rods 15 passes through the cross bar 10 and is connected to a group of rotating handles 16, and multiple groups of anti-slip strips are arranged on the outer walls of the multiple groups of rotating handles 16;

[0034] Specifically, when installing the smart floor, multiple sets of screw rods 9 are inserted into the inside of the threaded sleeve 8, and then multiple sets of rotating handles 16 are rotated. Multiple sets of rotating handles 16 drive multiple sets of screw rods 9 to rotate through the rotating rod 15, so that multiple sets of screw rods 9 are inserted into the inside of the threaded sleeve 8, so that multiple sets of cross bars 10 and connecting rods 11 can be set on the back wall of the adjustment and display panel 1, so that the smart floor can be supported by multiple sets of support seats 14, and at the same time, the back wall of the adjustment and display panel 1 can be protected by multiple sets of cross bars 10 and connecting rods 11, so that it can be well installed inside the floor for use as a floor block, and at the same time, the service life of the adjustment and display panel 1 is extended.

[0035] At the same time, the core processing module 4 is electrically connected to the dual power interface 5 and the Lan communication port 6 , so that the core processing module 4 can be controlled through the dual power interface 5 and the Lan communication port 6 .

[0036] The monitoring software also includes a strategy linkage method. The strategy linkage method uses the following methods: automatically controlling the refrigeration equipment to cool the overheated area, and recording the startup and operation time of the refrigeration equipment. The power consumption of the refrigeration equipment in the cycle is calculated based on the rated power and operation time of the equipment. The monitoring software integrates the above acquired data into a data model for packaging;

[0037] The monitoring software integrates the above acquired data into a data model for packaging. Depending on the environment, the monitoring software does not have a data model when it is first run. It needs to record the data through multiple policy linkages to form a data model. Multiple data models are compared with each other to obtain the data model with the lowest power consumption of the refrigeration equipment.

[0038] Use temperature and humidity sensors to detect the average temperature within the data room area, and use thermal imaging cameras to detect the distribution of cabinet hotspots in the data room area. For areas where the average temperature is too high, turn on precision air conditioning and use fresh air fans to dissipate heat evenly. For areas where some hotspots are too high, use smart floors for targeted heat dissipation.

[0039] Further, such as Fig. 9 , Fig.10 As shown, the CPU of the core processing module 4 receives the signal conditioning of the temperature and humidity sensor through the A / D converter, and at the same time operates through key operations. The specific work is as follows:

[0040] S1. Press the SET key for a few seconds;

[0041] S2, the heating light flashes, the heating temperature is set, and the system will exit after the temperature exceeds 10 seconds.

[0042] S3. Press the SET key, the heating and temperature lights flash, set the heating return difference, and exit when it is greater than 10 seconds;

[0043] S4. Press the SET button, the exhaust light flashes, set the exhaust temperature value, and exit when it is greater than 10 seconds;

[0044] S5. Press the SET button, the dehumidification light flashes, set the upper humidity limit, and exit when it exceeds 10 seconds;

[0045] S6. Press the SET button, the dehumidification and humidity lights flash, set the dehumidification return difference, and exit when it is greater than 10 seconds;

[0046] S7. Press the SET key. If the time is greater than 3 seconds, the system will exit. If the time is less than 3 seconds, the system will return to S2.

[0047] A data center monitoring method based on the above system configuration includes the following steps:

[0048] Step 1: The temperature sensor and thermal imaging camera at the front end continuously collect data. The front-end collection device analyzes the data signals output by the temperature sensor and thermal imaging camera, and transmits them back to the management server monitoring software for centralized collection in real time. The monitoring software completes the regular storage of real-time data with one data set per minute, and dynamically determines the data with excessive instantaneous fluctuations as key data for storage;

[0049] Step 2: The monitoring software uses a strategy linkage method to automatically control the refrigeration equipment to cool the overheated area, and records the startup and operation time of the refrigeration equipment. The power consumption of the refrigeration equipment during the cycle is calculated based on the rated power and operation time of the equipment. The monitoring software integrates the above acquired data into a data model for packaging;

[0050] Step 3: In different environments, the monitoring software that has just started running does not have a data model. It is necessary to record the data through multiple policy linkages to form a data model. Multiple data models are compared with each other to obtain the data model with the lowest power consumption of the refrigeration equipment;

[0051] Step 4: When the monitoring software is running, a dynamic tuning strategy of "large to small" is adopted. First, the temperature of the refrigeration equipment is adjusted over a large range, and then the temperature is gradually lowered until the solution with the lowest power consumption of the refrigeration equipment is obtained under the same refrigeration effect. Combined with traditional refrigeration solutions, the specific energy-saving values ​​under various energy-saving solutions are calculated, and the energy-saving values ​​are used for monitoring and regulation.

[0052] After operation, it is possible to adopt reasonable and effective digital strategies, and after the use time increases, the asset configuration of the data center is further optimized, the energy-saving potential is stimulated, the energy consumption of facilities and equipment is reduced, and the overall energy efficiency is improved; the model is established by the method of automatic temperature adjustment of the cold channel of the data room, and the actual heating situation is recorded to form basic data for dynamic temperature adjustment and refrigeration. Different constant temperature models are quoted according to the distribution of hot spots in different scenarios, so as to achieve dynamic and efficient energy saving. The present invention can be widely used in the field of energy-saving technology of computer rooms for a long time, effectively saving energy consumption and achieving true cooling on demand.

[0053] The initial heat load calculation formula used in the present invention is as follows:

[0054] (5) Equipment heat load Q1 = P × η1 × η2 × η3 (kW), where P is the total power consumption of various equipment in the room (kW), η1: simultaneous use coefficient, η2: utilization coefficient, η3: load uniformity coefficient. Usually, η1, η2, and η3 are between 0.6 and 0.8. Considering the redundancy of cooling capacity, η1 × η2 × η3 is usually set to 0.8.

[0055] (6) Heat load of lighting in the machine room

[0056] Q2 = (C × S) / 1000 (KW), C: illumination of the computer room. Generally, the illumination of the computer room should be greater than 200lx, and its power consumption is about 20W / ㎡. S: area of ​​the computer room.

[0057] Q = cm(T1-T2), where Q is the total cooling capacity, C is the specific heat capacity, M is the mass, and T is the temperature.

[0058] The total cooling capacity required on site is obtained through the initial formula. Since the actual environment will inevitably have errors with the calculation results of the general formula, the system software uses thermal imaging cameras and temperature and humidity sensors to monitor the operating status of the on-site environment in real time, obtain the actual value and compare it with the calculation results of the initial formula, and gradually optimize and control the air output of the smart floor, the speed of the fresh air fan, and the cooling capacity of the air conditioner;

[0059] The cooling target temperature is proportional to the cooling capacity. The greater the temperature difference, the greater the cooling capacity. The constant temperature of the data room is around 22°C. For equipment with high heat output, the operation and maintenance personnel will increase the cooling capacity of the precision air conditioner to reduce the heat output of the equipment. However, this method of reducing heat output requires the overall temperature to be lowered. In fact, except for local high temperatures, other locations do not need to be cooled. After adopting the energy-saving model, the cooling requirements can be met, and the local hot spots can be cooled without cooling the entire area, thus reducing the energy consumption of the refrigeration equipment.

[0060] Monitoring data obtains basic information through the front-end perception layer device. The sensor transmits the data in the device's own register to the serial port server through the RS485 signal. The serial port server forwards the data to the access system. After the system obtains the data, it filters the data and stores it in the database.

[0061] The system makes real-time judgments based on the monitoring data collected from the front end, sets the linkage mode, takes one day as a cycle, and uses a step-by-step adjustment method to generate the optimal solution for the current environment. For example, when the hot spot temperature exceeds 25 degrees on that day, the smart floor is activated to use the maximum wind speed to cool the hot spot. When it is below 23 degrees, it is adjusted to medium wind speed. When it is below 21 degrees, it is adjusted to low wind speed. If the temperature is still dropping, the smart floor is turned off. The principles of other controlled devices such as fans and air conditioners are basically the same. Among them, the main power-consuming equipment is the air conditioner. The system gives priority to the air conditioner energy-saving solution and continuously ensures the minimum power for cooling. After a cycle ends, the system will count the power consumption of the current solution and compare it with the power consumption of the previous day to fine-tune the temperature changes for the next day.

[0062] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A strategy linkage method for a demand-based refrigeration monitoring system, characterized in that: It includes a management server, a monitoring software module, a collection device and a refrigeration device. The monitoring software includes a strategy linkage method. The strategy linkage method uses a method including automatically controlling the refrigeration device to cool the overheated area, and recording the startup and operation time of the refrigeration device, and calculating the power consumption of the refrigeration device within the cycle based on the rated power and operation time of the device. The monitoring software integrates the above acquired data into a data model for packaging; The monitoring software integrates the above acquired data into a data model for packaging. According to different environments, the monitoring software that has just started to run does not have a data model. After multiple policy linkages, the data is recorded to form a data model. Multiple data models are compared with each other to obtain the data model with the lowest power consumption of the refrigeration equipment. During the operation of the monitoring software, a dynamic tuning strategy of "large to small" is adopted. The temperature of the refrigeration equipment is first adjusted over a large range, and then the temperature is gradually tried to be lowered until the solution with the lowest power consumption of the refrigeration equipment is obtained under the same cooling effect. Combined with traditional refrigeration solutions, the specific energy-saving values ​​under various energy-saving solutions are calculated, and the energy-saving values ​​are used for monitoring and regulation. After adopting the energy-saving model, the requirements of on-demand cooling are realized to cool down local hot spots.

2. The strategy linkage method of the demand-based refrigeration monitoring system according to claim 1, characterized in that: The acquisition equipment includes a temperature sensor and a thermal imaging camera, and the refrigeration equipment includes a precision air conditioner, a fresh air fan and an intelligent floor. The temperature sensor is used to check the temperature and humidity of the environment, and the thermal imaging camera is used to check the distribution of hot spots in the area. The precision air conditioner, fresh air fan and intelligent floor are used to adjust the air volume and balance the temperature within the area.

3. The strategy linkage method of the demand-based refrigeration monitoring system according to claim 2, characterized in that: The intelligent floor comprises an adjustment and display panel (1), a high-strength floor grille (2) is arranged on the front wall of the adjustment and display panel (1), an EC high-voltage brushless fan (3) is arranged on the back wall of the adjustment and display panel (1), a core processing module (4) is arranged on one side of the EC high-voltage brushless fan (3), the core processing module (4) is arranged on the back wall of the adjustment and display panel (1), a dual power interface (5) is arranged on the core processing module (4), a Lan communication port (6) is arranged on one side of the dual power interface (5), the Lan communication port (6) is arranged on the core processing module (4), and a temperature control perforator (7) is arranged on the adjustment and display panel (1).

4. The strategy linkage method of the demand-based refrigeration monitoring system according to claim 3 is characterized in that: The method also includes using temperature and humidity sensors to detect the average temperature within the data room area, using thermal imaging cameras to detect the distribution of cabinet hot spots in the data room area, turning on precision air conditioning in areas where the average temperature is too high and using fresh air fans to evenly dissipate heat, and using smart floors for targeted heat dissipation in areas where some hot spots are too high.

5. The strategy linkage method of the demand-based refrigeration monitoring system according to claim 3, characterized in that: A group of threaded sleeves (8) are arranged at the four corners of the back wall of the adjustment and display panel (1); a group of screw rods (9) are threadedly connected inside the multiple groups of threaded sleeves (8); two groups of cross bars (10) are arranged at the other ends of the multiple groups of screw rods (9); multiple groups of connecting rods (11) are arranged between the two groups of cross bars (10); support frames (12) are arranged on the end walls of the multiple groups of connecting rods (11) and the cross bars (10); multiple groups of supporting columns (13) are arranged on the side walls of the multiple groups of connecting rods (11); Multiple groups of support columns (13) are evenly spaced on the side walls of multiple groups of connecting rods (11); a group of support seats (14) are arranged on the other end faces of multiple groups of support columns (13); multiple groups of connecting rods (11) are evenly spaced on two groups of cross bars (10); one end of multiple groups of screw rods (9) is provided with a rotating rod (15); the other ends of multiple groups of rotating rods (15) pass through the cross bar (10) and are connected to a group of rotating handles (16); multiple groups of anti-slip strips are arranged on the outer walls of multiple groups of rotating handles (16).

6. The strategy linkage method of the demand-based refrigeration monitoring system according to claim 3, characterized in that: The method also includes the front-end temperature sensor and thermal imaging camera continuously collecting data, the front-end collection device analyzes the data signals output by the temperature sensor and the thermal imaging camera, and transmits them back to the management server monitoring software for centralized collection in real time. The monitoring software completes the regular storage of real-time data with one data set per minute, and dynamically determines the data with excessive instantaneous fluctuations as key data storage.

7. The strategy linkage method of the demand-based refrigeration monitoring system according to claim 1, characterized in that: The calculation, including the initial heat load calculation formula, is as follows: (1) Equipment heat load Q1 = P × η1 × η2 × η3 (kW), where P is the total power consumption of various equipment in the room (kW), η1: simultaneous use coefficient, η2: utilization coefficient, η3: load uniformity coefficient. Usually, η1, η2, and η3 are between 0.6 and 0.

8. Considering the redundancy of cooling capacity, η1 × η2 × η3 is usually set to 0.

8. (2) Heat load of lighting in the computer room Q2 = (C × S) / 1000 (KW), C: illumination of the computer room. Generally, the illumination of the computer room should be greater than 200lx, and its power consumption is about 20W / ㎡. S: area of ​​the computer room. Q = cm(T1-T2), where Q is the total cooling capacity, C is the specific heat capacity, M is the mass, and T is the temperature. The total cooling capacity required on site is obtained through the initial formula. The system software monitors the operating status of the on-site environment in real time through thermal imaging cameras and temperature and humidity sensors, obtains actual values ​​and compares them with the results calculated by the initial formula, and gradually optimizes and controls the air volume of the smart floor, the speed of the fresh air fan, and the cooling capacity of the air conditioner.

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