Energy-saving air supply intelligent control system of air conditioner

Abstract

The invention discloses an energy-saving air supply intelligent control system of an air conditioner, and belongs to the field of air conditioner control. The system comprises an air conditioner terminal and a cloud service terminal, wherein the air conditioner terminal is provided with a sensor integration module, a data acquisition unit, a data preprocessing unit, a data sending unit and an action execution unit; the cloud server is provided with a data cache unit and a data service unit. The air supply speed and the air supply angle of the air conditioner can be regulated and controlled through cooperation of the air conditioner end and the cloud server end. The indoor temperature, humidity, personnel number and indoor size information data are collected, and the collected data are reasonably analyzed, so that the air supply speed of the air conditioner can be accurately obtained, and compared with traditional air supply adjustment through the single temperature difference between the indoor temperature and the preset temperature, the air supply speed of the air conditioner can be accurately adjusted. The air supply speed of the air conditioner can be accurately regulated and controlled, air supply control can be more linear, and air supply is more stable and gentle.

Description

Technical Field

[0001] The invention relates to air conditioning control, and in particular to an air conditioning energy-saving air supply intelligent control system. Background Art

[0002] Air conditioner is an air conditioner, which is composed of four parts: refrigeration (heat) circulation system, air circulation ventilation system, electrical control system and box body. It is a small air conditioner that keeps the air in the conditioned space at a certain temperature, humidity, flow speed, cleanliness and freshness. Its working principle is roughly as follows: after the refrigerant is compressed by the external machine, it becomes a high-temperature and high-pressure gas. After passing through the radiator, it becomes a normal-temperature and high-pressure liquid. Finally, after passing through the expansion valve, it becomes a low-temperature and low-pressure liquid and enters the indoor condenser. The cold air is sent out through the indoor fan. At present, when the air conditioner is controlling the air supply, it controls the air supply by the temperature difference between the preset temperature and the indoor temperature. When the temperature difference between the indoor temperature and the preset temperature is large, the air conditioner is in a strong air supply mode. Through high-speed airflow, the indoor temperature is quickly adjusted to the preset temperature. As the temperature difference between the indoor temperature and the preset temperature decreases, the air supply gradually weakens. However, such an air supply control mode only relies on a single temperature difference for air supply control, resulting in inaccurate air supply control. Furthermore, when the current air supply control system is controlling the air supply, the air supply angle cannot be adjusted, which may easily cause the air conditioning air to blow directly. Summary of the invention

[0003] Purpose of the invention: The purpose of the present invention is to provide an air conditioning energy-saving air supply intelligent control system to solve the problem of inaccurate air supply control in current air conditioning air supply control systems.

[0004] Technical solution: An air-conditioning energy-saving air supply intelligent control system includes an air-conditioning end and a cloud service end. The air-conditioning end is deployed with a sensor integration module, a data acquisition unit, a data preprocessing unit, a data sending unit and an action execution unit; the sensor integration module integrates a temperature sensor, a humidity sensor and an infrared camera; the data acquisition module is used to collect temperature, humidity and indoor occupancy information data monitored by the sensor integration module; the data preprocessing unit is used to preprocess the information data collected by the data acquisition unit to improve the integrity of the data; the data sending module is used to send the data preprocessed by the data preprocessing unit to the cloud service end; the action execution module is used to adjust the air supply speed and air supply angle of the air conditioner according to the processing results of the cloud service end; The cloud server is deployed with a data cache unit and a data service unit; the data cache unit is used to cache the data sent by the data sending unit so that the data service unit can quickly retrieve the data for processing; the data service unit is used to retrieve data from the data cache unit and process the data, so that the air supply speed adjustment result of the air conditioner can be obtained according to the indoor temperature, humidity, number of people and indoor size, and the air supply angle adjustment result of the air conditioner can be obtained according to the indoor crowded position.

[0005] Preferably, the infrared camera detects people in the room through a trained CNN neural network algorithm, and can detect the distance between the person and the air conditioner through the infrared function.

[0006] Preferably, when the data preprocessing unit preprocesses the data collected by the data acquisition unit, it includes denoising, cleaning and pre-analyzing the data; when pre-analyzing the data, the current indoor size is determined according to the number of air conditioners and the indoor size range corresponding to the number of air conditioners, and the determined current indoor size = (minimum value of the indoor size corresponding to the number of air conditioners + maximum value of the indoor size corresponding to the number of air conditioners) / 2.

[0007] Preferably, when preprocessing the data, the data preprocessing unit determines the distance C between the densely populated people and the air conditioner based on the position of the densely populated people detected by the infrared camera, so as to determine the angle β between the densely populated people and the air conditioner. If the angle β between the densely populated people and the air conditioner is between the inclination angle α of the air conditioner guide plate and the current maximum air supply angle (α+γ) of the air conditioner, γ is the air supply range angle of the air conditioner, then it is determined that the densely populated people are directly blown by the wind, and the determination result is sent to the cloud server.

[0008] Preferably, the data service unit includes two parts: data processing and result delivery. When the data preprocessing unit determines that the densely populated people are directly blown by the wind, the data processing part will determine the air supply angle σ that the air conditioner needs to adjust according to the angle β between the densely populated people and the air conditioner and the air supply range angle γ of the air conditioner:

[0009] Among them, C is the distance between the air conditioner and the densely populated people, and H is the installation height of the air conditioner; then, through the result sending part, the air supply angle σ that needs to be adjusted is fed back to the action execution unit, so as to adjust the air supply angle of the air conditioner.

[0010] Preferably, the data processing part can retrieve the indoor temperature, humidity, number of people and indoor size data from the data cache module unit, and can process and analyze these data to obtain the wind speed V of the air supply of the air conditioner:

[0011] Among them, δ is the temperature sensitivity coefficient, T is the indoor temperature, T0 is the reference comfort temperature, ε is the humidity sensitivity coefficient, H is the indoor relative humidity, H0 is the reference comfort humidity, λ is the number of people influence coefficient, N is the number of people indoors, η is the space adjustment coefficient, A is the indoor area, K is the normalization coefficient, V max 、V min are respectively the maximum and minimum air supply speeds of the air conditioner; then, through the result sending part, the determined air supply speed V that the air conditioner needs to adjust is fed back to the action execution unit, so as to adjust the air supply speed of the air conditioner.

[0012] Preferably, the action execution unit includes two parts: air supply speed adjustment and air supply angle adjustment. The air supply speed adjustment is used to adjust the air supply speed of the air conditioner according to the air supply speed adjustment result sent by the cloud server; the air supply angle adjustment is used to adjust the air supply angle of the air conditioner according to the air supply angle adjustment result sent by the cloud server.

[0013] Preferably, when data is exchanged between the air conditioner and the cloud service end, data exchange communication is performed through 4G / 5G / WiFi communication means.

[0014] Beneficial effects: The present invention collects indoor temperature, humidity, number of people and indoor size information data, and reasonably analyzes the collected data, so as to accurately obtain the air supply speed of the air conditioner. Compared with the traditional air supply adjustment through the temperature difference between a single indoor temperature and a preset temperature, the present invention can accurately control the air supply speed of the air conditioner, and can make the air supply control more linear and make the air supply more stable and gentle. In addition, during the air supply process, the indoor densely populated area can be monitored and judged in real time. When it is monitored and judged that the indoor densely populated area is located in the air supply range of the air conditioner, the air supply angle of the air conditioner will be automatically adjusted to avoid the air conditioning wind blowing directly on the body of the indoor personnel, thereby causing discomfort to the indoor personnel. The present invention can not only make the air supply more accurate, but also avoid the situation where the direct blowing of the air supply causes discomfort to the personnel through the precise control of the air supply speed and the air supply angle. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the system principle of the present invention; Figure 2 It is a schematic diagram of air supply angle adjustment of the present invention. DETAILED DESCRIPTION

[0016] In order to make the technical solution of the present invention clearer, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0017] Example 1 like Figure 1 As shown in the figure, the system is divided into an air conditioner end and a cloud service end, and the air conditioner end and the cloud service end interact with each other through 4G / 5G / WiFi communication technology. A sensor integration module with integrated temperature sensor, humidity sensor and infrared camera is deployed in the air conditioner end, wherein the infrared camera can detect indoor personnel through the trained CNN neural network algorithm, and can detect the distance between personnel and air conditioner through the infrared function. A data acquisition unit for collecting temperature, humidity and indoor personnel information data monitored by the sensor integration module is also deployed. A data preprocessing unit for denoising, cleaning and preprocessing the data collected by the data acquisition unit. When preprocessing the data, the unit first obtains the current air conditioner horsepower, and determines the current indoor size according to the indoor size range of the horsepower. For example, the air conditioner currently installed in the room is a 2-horsepower air conditioner, and according to the indoor size range table corresponding to the horsepower, it is determined that the 2-horsepower air conditioner corresponds to 17~23m 2 , the determined indoor size = (17 + 23) / 2 = 20m 2 A data sending unit for sending data to the data acquisition unit and an action execution unit for adjusting the air supply speed of the air conditioner are also deployed.

[0018] The cloud service end is deployed with a data cache unit for caching the data sent by the data sending unit and a data service unit for processing the data. When processing the data, the data service unit first directly retrieves the current indoor temperature, humidity, number of people, and indoor size data from the data cache unit, and then processes and analyzes the retrieved data through the following formula, so that the current air supply speed V of the air conditioner can be obtained:

[0019] Among them, δ=0.1 is the temperature sensitivity coefficient. T is the indoor temperature. T0=24℃ is the reference comfort temperature. (T-T0) 2 It is used to reflect the accelerated response when the temperature deviates from the comfort level. 2 For square term design, when the temperature deviates from 24℃: 26℃:(2) 2 =4----Contribution value: 0.1×4=0.4.

[0020] 30℃: (6) 2 =36----Contribution value: 0.1×36=3.6.

[0021] Squaring leads to rapid numerical expansion, thus suppressing the excessive dominance of temperature by the delta coefficient.

[0022] When the temperature difference is 4°C: 0.1×(4) 2=1.6, corresponding to a wind speed increase of about 1.6×(V max -V min ) / K+V min ≈0.77m / s (meets actual measurement requirements).

[0023] ε=1.2 is the humidity sensitivity coefficient. H is the indoor relative humidity. H0=50% is the baseline comfortable humidity. ln(x) can reflect the decreasing marginal effect of humidity change. The logarithmic function ln(H / H0) is used to compress the linear effect of humidity change: H=50%:ln(1)=0(reference point) H=65%:ln(1.3)=0.262----Contribution value 1.2×0.262≈0.31 H=80%: ln(1.6)=0.47----Contribution value 1.2×0.47≈0.56.

[0024] Since the effect of humidity change on human perception decreases nonlinearly, when the humidity is greater than 60%, every 5% humidity change requires a temperature compensation equivalent to 0.5 degrees Celsius. Therefore, ε=1.2 is used to keep the influence ratio of humidity term to temperature term at 1:3.

[0025] λ=0.3 is the number of people effect coefficient. N is the number of people in the room. 1.5 can reflect the superposition effect of crowd gathering. The heat dissipation power of human body is about 100W / person, but the heat accumulation effect obeys N 1.5 law: 1 person: 1 1.5 =1----0.3×1=0.3 4 people: 4 1.5 =8----0.3×8=2.4 10 people: 10 1.5 =31.6----0.3×8=9.5.

[0026] By setting λ=0.3, the maximum value of the number of people is controlled to about 10 (corresponding to a Sigmoid input of no more than 1 when K=15). Actual measured data shows that a wind speed compensation of 0.1~0.5m / s is required for each additional person, and the coefficient of 0.3 is in a reasonable range.

[0027] η=2.5 is the spatial adjustment coefficient. A is the indoor area. The square root can reflect the decreasing marginal effect of increasing area. √A is used to reflect the spatial dilution effect: 20m 2 :√20≈4.47----2.5×4.47≈11.18 50m 2 :√50≈7.07----2.5×7.07≈17.68 Through CFD simulation, small space (<30m 2 ) requires stronger wind speed compensation efficiency, so η=2.5 is sufficient. η=2.5 can make 20m 2 and 50m 2 The spatial term difference is ≈6.5, which is equivalent to a compensation effect of 8°C. This is consistent with the ASHRAE standard curve of the effect of space size on ventilation efficiency.

[0028] Sigmoid(x) can limit the output to the range of (0,1) to ensure a smooth transition of wind speed.

[0029] K=15 is the normalization coefficient. It ensures that the input value of the Sigmoid function is within a reasonable range, and at the same time ensures that the output is within the sensitive range of the Sigmoid function to avoid gradient disappearance.

[0030] V max =3.0m / s, V min =0.5m / s are the maximum and minimum air supply speeds of the air conditioner respectively.

[0031] When the indoor temperature is T=30℃, the indoor humidity is H=70%, the number of people in the room is N=6, and the indoor area is A=30m 2 hour: V=Sigmoid[(0.1×36+1.2×ln(1.4)+0.3×15+2.5×5.48) / 15]×2.5+0.5≈2.54m / s When the indoor temperature is T=28℃, the indoor humidity is H=65%, the number of people in the room is N=4, and the indoor area is A=20m 2 hour: V=Sigmoid[(0.1×16+1.2×ln(1.3)+0.3×8+2.5×4.47) / 15]×2.5+0.5≈2.34m / s.

[0032] Then the determined air supply speed V that needs to be adjusted by the air conditioner is fed back to the action execution unit, so as to adjust the air supply speed of the air conditioner.

[0033] Example 2 On the basis of Example 1, when the data preprocessing unit preprocesses the data, the infrared camera uses the built-in trained CNN neural network algorithm and the infrared function, such as Figure 2 As shown, the position of densely populated people in the room can be detected, and the distance C between the densely populated people and the air conditioner can be determined. At this time, since the installation height H of the air conditioner is also determined, the angle β between the densely populated people and the air conditioner can be determined:

[0034] If the angle β between the densely populated people and the air conditioner is between the inclination angle α of the air conditioner guide plate (known) and the maximum air supply angle of the air conditioner (α+γ), and γ is the air supply range angle of the air conditioner (known), it is determined that the densely populated people are directly blown by the wind. At this time, the data service unit will determine the air supply angle σ that the air conditioner needs to adjust:

[0035] Then, the determined air supply angle σ that needs to be adjusted by the air conditioner is fed back to the action execution unit, so as to adjust the air supply angle of the air conditioner.

[0036] The present invention can not only achieve the accuracy of air supply but also avoid the discomfort caused to personnel by direct blowing of air through dynamic regulation of air supply speed and air supply angle.

[0037] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. An air conditioning energy-saving air supply intelligent control system, comprising an air conditioning end and a cloud service end, characterized in that: The air conditioner is equipped with a sensor integration module, a data acquisition unit, a data preprocessing unit, a data sending unit and an action execution unit; the sensor integration module integrates a temperature sensor, a humidity sensor and an infrared camera; the data acquisition module is used to collect temperature, humidity and indoor occupancy information data monitored by the sensor integration module; The data preprocessing unit is used to preprocess the information data collected by the data collection unit to improve the integrity of the data; The data sending module is used to send the data preprocessed by the data preprocessing unit to the cloud service end; The action execution module is used to adjust the air supply speed and air supply angle of the air conditioner according to the processing results of the cloud server; The cloud service end is deployed with a data cache unit and a data service unit; the data cache unit is used to cache the data sent by the data sending unit so that the data service unit can quickly retrieve the data for processing; The data service unit is used to retrieve data from the data cache unit and process the data, so that the air supply speed adjustment result of the air conditioner can be obtained according to the indoor temperature, humidity, number of people and indoor size, and the air supply angle adjustment result of the air conditioner can be obtained according to the indoor crowded position.

2. The air conditioning energy-saving air supply intelligent control system according to claim 1 is characterized in that: The infrared camera detects people in the room through the trained CNN neural network algorithm, and can also detect the distance between people and the air conditioner through the infrared function.

3. The air conditioning energy-saving air supply intelligent control system according to claim 2 is characterized in that: When the data preprocessing unit preprocesses the data collected by the data acquisition unit, it includes denoising, cleaning and pre-analysis of the data; when pre-analyzing the data, the current indoor size is determined according to the number of air conditioners and the indoor size range corresponding to the number of air conditioners, and the determined current indoor size = (the minimum value of the indoor size corresponding to the number of air conditioners + the maximum value of the indoor size corresponding to the number of air conditioners) / 2.

4. The air conditioning energy-saving air supply intelligent control system according to claim 3 is characterized in that: When preprocessing the data, the data preprocessing unit determines the distance C between the densely populated people and the air conditioner based on the position of the densely populated people detected by the infrared camera, so as to determine the angle β between the densely populated people and the air conditioner. If the angle β between the densely populated people and the air conditioner is between the inclination angle α of the air conditioner guide plate and the current maximum air supply angle of the air conditioner (α+γ), γ is the air supply range angle of the air conditioner, then it is determined that the densely populated people are directly blown by the wind, and then the determination result is sent to the cloud service end.

5. The air conditioning energy-saving air supply intelligent control system according to claim 4 is characterized in that: The data service unit includes two parts: data processing and result delivery. When the data preprocessing unit determines that the densely populated people are directly blown by the wind, the data processing part will determine the air supply angle σ that the air conditioner needs to adjust based on the angle β between the densely populated people and the air conditioner and the air supply range angle γ of the air conditioner: ； Among them, C is the distance between the air conditioner and the densely populated people, and H is the installation height of the air conditioner; then, through the result sending part, the air supply angle σ that needs to be adjusted is fed back to the action execution unit, so as to adjust the air supply angle of the air conditioner.

6. The air conditioning energy-saving air supply intelligent control system according to claim 5 is characterized in that: The data processing part can retrieve the indoor temperature, humidity, number of people and indoor size data from the data cache module unit, and can process and analyze these data to obtain the wind speed V of the air supply of the air conditioner: ； Among them, δ is the temperature sensitivity coefficient, T is the indoor temperature, T0 is the reference comfort temperature, ε is the humidity sensitivity coefficient, H is the indoor relative humidity, H0 is the reference comfort humidity, λ is the number of people influence coefficient, N is the number of people indoors, η is the space adjustment coefficient, A is the indoor area, K is the normalization coefficient, V max 、V min are respectively the maximum and minimum air supply speeds of the air conditioner; then, through the result sending part, the determined air supply speed V that the air conditioner needs to adjust is fed back to the action execution unit, so as to adjust the air supply speed of the air conditioner.

7. The air conditioning energy-saving air supply intelligent control system according to claim 1 is characterized in that: The action execution unit includes two parts: air supply speed adjustment and air supply angle adjustment. The air supply speed adjustment is used to adjust the air supply speed of the air conditioner according to the air supply speed adjustment result sent by the cloud server; the air supply angle adjustment is used to adjust the air supply angle of the air conditioner according to the air supply angle adjustment result sent by the cloud server.

8. The air conditioning energy-saving air supply intelligent control system according to claim 1 is characterized in that: When data is exchanged between the air conditioner and the cloud service end, data exchange communication is carried out through 4G / 5G / WiFi communication means.

Images