CN116624971A - Air conditioner monitoring system - Google Patents
Air conditioner monitoring system Download PDFInfo
- Publication number
- CN116624971A CN116624971A CN202310920859.3A CN202310920859A CN116624971A CN 116624971 A CN116624971 A CN 116624971A CN 202310920859 A CN202310920859 A CN 202310920859A CN 116624971 A CN116624971 A CN 116624971A
- Authority
- CN
- China
- Prior art keywords
- heat transfer
- data
- temperature
- sensor
- data processing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 32
- 238000012546 transfer Methods 0.000 claims abstract description 130
- 230000005855 radiation Effects 0.000 claims abstract description 45
- 230000033228 biological regulation Effects 0.000 claims abstract description 16
- 239000000463 material Substances 0.000 claims abstract description 6
- 238000012545 processing Methods 0.000 claims description 56
- 238000004378 air conditioning Methods 0.000 claims description 25
- 238000004458 analytical method Methods 0.000 claims description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 16
- 238000011217 control strategy Methods 0.000 claims description 16
- 238000000034 method Methods 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 15
- 238000004891 communication Methods 0.000 claims description 11
- 230000008859 change Effects 0.000 claims description 8
- 230000005540 biological transmission Effects 0.000 claims description 6
- 238000013079 data visualisation Methods 0.000 claims description 6
- 230000009123 feedback regulation Effects 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 6
- 230000001105 regulatory effect Effects 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 claims description 4
- 230000003993 interaction Effects 0.000 claims description 4
- 239000007787 solid Substances 0.000 claims description 4
- 235000003805 Musa ABB Group Nutrition 0.000 claims description 3
- 208000025174 PANDAS Diseases 0.000 claims description 3
- 208000021155 Paediatric autoimmune neuropsychiatric disorders associated with streptococcal infection Diseases 0.000 claims description 3
- 235000016496 Panda oleosa Nutrition 0.000 claims description 3
- 235000015266 Plantago major Nutrition 0.000 claims description 3
- 238000013480 data collection Methods 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 claims description 3
- 240000008790 Musa x paradisiaca Species 0.000 claims 1
- 240000000220 Panda oleosa Species 0.000 claims 1
- 238000009472 formulation Methods 0.000 claims 1
- 239000000203 mixture Substances 0.000 claims 1
- 230000000694 effects Effects 0.000 abstract description 9
- 238000004590 computer program Methods 0.000 description 4
- 238000005265 energy consumption Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 241000234295 Musa Species 0.000 description 2
- 240000004718 Panda Species 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000001276 controlling effect Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000000241 respiratory effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 210000004243 sweat Anatomy 0.000 description 1
- 238000009736 wetting Methods 0.000 description 1
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
- F24F11/32—Responding to malfunctions or emergencies
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/52—Indication arrangements, e.g. displays
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/88—Electrical aspects, e.g. circuits
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/50—Air quality properties
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The application discloses an air conditioner monitoring system, which relates to the technical field of air conditioner monitoring, and adopts a radiation energy transfer model, the radiation energy transfer quantity is calculated by considering the radiation rate and the Stefan-Boltzmann constant of a wall and the difference between the surface temperature of the wall and the indoor temperature, the system can accurately estimate the influence of radiation heat transfer on the indoor temperature, meanwhile, a convection heat transfer model is introduced, the regulation effect of indoor air flow on the temperature is considered, the system calculates a heat transfer coefficient, the coefficient is based on Nusselt number, reynolds number and Plantt number, the regulation effect of convection heat transfer on the indoor temperature can be accurately estimated by considering the influence of air flow, the conduction heat transfer quantity is calculated by using Fourier law, the heat conduction coefficient, the surface area, the contact surface temperature difference and the heat transfer thickness of a wall material are considered, the heat is mainly transferred through the heat conduction heat transfer property of the wall, and the regulation effect of the conduction heat transfer on the indoor temperature can be accurately estimated.
Description
Technical Field
The application relates to the technical field of air conditioner monitoring, in particular to an air conditioner monitoring system.
Background
An air conditioning monitoring system is a technical system for monitoring and controlling the performance of an air conditioning system. It is generally composed of hardware devices and software, and is intended to provide real-time monitoring, data recording and analysis of the operating conditions of an air conditioning system, the hardware of which generally comprises sensors and data acquisition devices for measuring and recording various parameters of the air conditioning system, such as temperature, humidity, air flow rate, pressure. These sensors are typically installed at critical locations of the air conditioning system to obtain accurate data, and through hardware and software analysis, provide real-time monitoring, data recording and analysis of the performance and energy consumption of the air conditioning system to help users optimize the operating efficiency and energy consumption of the air conditioning system.
The current air conditioner monitoring system mostly comprises indoor and outdoor temperature monitoring, and the high-end air conditioner is provided with indoor and outdoor humidity monitoring, but the control system of the air conditioner is used as equipment for improving the human comfort, and the control system of the air conditioner should have the function of improving the human comfort at the same time, wherein the comfort is mainly that whether the indoor temperature is timely when being regulated, whether the indoor temperature can reach the expected temperature or not, and actually, each person has different feelings for the heat comfort, and the comfort cannot be provided for each person at the same time, but the comfort of the human body can still be improved from the heat conduction angle, and the indoor heat conduction comprises conduction heat transfer, radiation heat transfer, convection heat transfer, respiratory heat transfer (drying and wetting), heat transfer of moisture and sweat on the skin, human body work and heat transfer of entering/leaving storage.
The traditional air conditioner monitoring system cannot monitor the temperature of the indoor and outdoor walls, and can not calculate the influence of heat conduction on the indoor temperature according to the temperature naturally, so that the daily indoor temperature is greatly influenced, for example, the daily indoor temperature is obviously different in the morning and the evening, the wall is not subjected to durable insolation in the morning, the influence of heat conduction on the indoor temperature is small, at the moment, the opening temperature of the air conditioner and the time required for reaching the target temperature are shorter, the temperature after the wall is insolated in the evening is higher, meanwhile, the scattered heat radiation acts in the indoor and on the human body, and the situation that the influence of heat conduction on the indoor temperature cannot reach the target temperature or the influence of heat radiation on the indoor temperature lasts longer is neglected, so that the air conditioner monitoring system capable of adding the influence of heat conduction and the heat radiation on the indoor temperature into the air conditioner adjusting system is needed to solve the problems.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the application provides an air conditioner monitoring system which solves the problem that the influence on the indoor temperature caused by conduction heat transfer and radiation heat transfer in the prior art is ignored, and the indoor temperature regulation of an air conditioner system is influenced.
(II) technical scheme
In order to achieve the above object, the present application provides an air conditioner monitoring system, which comprises:
the data acquisition system acquires indoor and outdoor data information by adopting a sensor, wherein the sensor comprises a temperature sensor, a humidity sensor, a wind speed sensor, an external temperature sensor, a wall temperature sensor, an indoor air quality sensor, a specific heat capacity sensor and an ultrasonic wind speed sensor;
the data processing system comprises a single board computer, a data processing unit, a storage device, a data transmission module, a sensor interface, a data processing frame, a library and a data visualization tool, is responsible for receiving, processing and analyzing data acquired from each sensor, making decisions and control according to algorithms and logics, using the acquired sensor data, establishing a model through a data processing and analyzing technology, predicting the change trend of indoor temperature based on historical data and external factors, and adjusting according to the set target temperature;
the control strategy making system comprises a software platform, an embedded system and a database system, and makes a corresponding control strategy according to the output of the model and the set target temperature, and adjusts the output parameters of the air conditioning system, including the set values of wind speed, temperature and humidity, based on the indoor temperature conditions under the influence of the heat radiation, heat convection and heat conduction factors determined by data processing and analysis;
the real-time control system is a FreeRTOS, zephyr, linux operating system, and further comprises a controller and a communication module, wherein the communication module is used for carrying out data interaction with the sensor, the actuator and other systems;
the feedback regulation system comprises an actuator and a control algorithm, performs feedback regulation according to the difference between the actual indoor temperature and the set target temperature, and gradually regulates the indoor temperature to the target temperature by regulating the control strategy and the output parameters of the air conditioning system according to the difference;
the user interface and the notification system provide a visual interface, display real-time monitoring data and temperature regulation state, provide real-time notification, alarm and suggestion for users, and send alarm when the temperature is too high or too low.
The application is further arranged to: the data processing and analysis technology in the data processing system specifically comprises the following steps:
step 1, data collection and preprocessing
Obtaining measured data monitored by a data acquisition system and preprocessing the data;
step 2, radiation energy transfer model
The influence of wall radiation on indoor temperature is described by adopting a radiation energy transfer model, and a radiation energy transfer formula is adopted, wherein the radiation energy transfer formula is as follows:
establishing a Black-Body Approximation Model blackbody approximation model: assuming that the wall is a blackbody, the radiant energy transfer is calculated using the Stefan-Boltzmann law, with the specific formula:
wherein E represents radiant energy transfer, ε represents the emissivity of the wall, and σ is a Stefan-Boltzmann constant, T_w is the wall exterior surface temperature, and T_i is the indoor temperature;
the application is further arranged to: the data processing and analysis technique modeling in the data processing system further includes:
step 3, convective heat transfer influence determination
Adding the influence of air flow on indoor temperature, introducing a convection heat transfer model, and establishing a specific mode by the following steps:
the flow heat transfer coefficient α is a parameter for expressing the influence of the indoor air flow on the indoor temperature, which is Nu described below;
the flow heat coefficient calculation formula adopts the relation between Nusselt number Nu, reynolds number Re and Plantain number Pr, and the calculation formula is specifically as follows:
wherein C, m, n are empirical parameters derived from expert analysis and actual engineering practices in the field;
the application is further arranged to: the data processing and analysis technique modeling in the data processing system further includes:
step 4, determining the surface area and the temperature difference
The user autonomously inputs the wall surface area A, and the data processing system determines the wall surface temperature difference delta T according to the acquired data for subsequent calculation of convection heat transfer quantity;
step 5, calculating the convection heat transfer quantity
The convective heat transfer quantity q_conv is calculated using the convective heat transfer coefficient α, the surface area a, and the temperature difference Δt. The specific calculation formula is as follows:
the convection heat transfer quantity q_conv represents heat transfer caused by natural convection;
the application is further arranged to: the data processing and analysis technique modeling in the data processing system further includes:
step 6, determining the conduction heat transfer quantity
The conduction heat transfer quantity Q is determined by adopting a Fourier law, and the specific formula is as follows:
wherein k represents the heat conductivity coefficient of the wall material, A represents the surface area, namely the effective heat transfer area, T1 and T2 respectively represent the temperatures of two sides of the wall contacting the surface, and d represents the heat transfer thickness, namely the wall thickness;
step 7, indoor temperature regulation algorithm
The influence of radiation heat transfer, convection heat transfer and conduction heat transfer is synthesized, and the indoor temperature regulating quantity is calculated, wherein the specific calculation formula is as follows:
wherein Δt represents an adjustment amount of indoor temperature, E represents radiant energy transfer, a represents a surface area of a wall, h represents a heat radiation heat transfer coefficient, α represents a convection heat transfer coefficient, t_ext and t_i represent temperatures inside and outside the room, respectively, Q represents a conduction heat transfer amount, Δt represents a time step, m represents a mass of indoor air, and C represents a specific heat capacity of indoor air;
the application is further arranged to: in the data acquisition system, a single board computer is selected from Raspberry Pi and Arduino;
the data processing unit comprises an embedded processor and a microcontroller and is used for processing the sensor data and executing an algorithm in real time;
the storage device comprises a hard disk and a Solid State Drive (SSD) and is used for storing the acquired data;
the data transmission module is selected from a Wi-Fi module, a Bluetooth module and an internet of things (IoT) communication module and is used for transmitting data from the sensor to the data processing system;
the sensor interface comprises an analog input, a digital input and output and a serial port and is used for connecting a sensor;
the data processing frame and library select NumPy, pandas and Scikit-learn of Python for data processing, analysis and modeling;
the data visualization tool is selected from Matplotlib and Plotly and is used for visualizing and displaying the processed data;
the application is further arranged to: in the control strategy making system, a control strategy is applied to a controller of the air conditioning system, the operation parameters of the air conditioning system are adjusted in real time through the controller, and the operation state of the air conditioning system is controlled according to the temperature change predicted by the model and the actually monitored indoor temperature.
(III) beneficial effects
The application provides an air conditioner monitoring system. The beneficial effects are as follows:
by adopting a radiation energy transfer model, taking the radiation rate of a wall, the Stefan-Boltzmann constant and the difference between the wall surface temperature and the indoor temperature into consideration, by calculating the radiation energy transfer quantity, the system can accurately estimate the influence of radiation heat transfer on the indoor temperature, meanwhile, a convection heat transfer model is introduced, the regulation effect of indoor air flow on the temperature is considered, the system calculates a flow heat coefficient, the coefficient is based on Nusselt number, reynolds number and Plantt number, the regulation effect of convection heat transfer on the indoor temperature is accurately estimated by considering the influence of air flow, and the conduction heat transfer quantity is calculated by using Fourier law, and the heat is mainly transferred by the heat conduction property of the wall material, so that the regulation effect of the conduction heat transfer on the indoor temperature can be accurately estimated.
The method is characterized in that the influence of radiation heat transfer, convection heat transfer and conduction heat transfer is integrated, the adjustment quantity of the indoor temperature is calculated, the adjustment quantity represents the adjustment proposal of the system according to the heat transfer characteristic and the temperature difference, according to the adjustment quantity, the air conditioning system can correspondingly adjust the operation parameters to gradually adjust the indoor temperature to the set target temperature, the change trend of the indoor temperature can be accurately predicted, and a proper control strategy is adopted, so that the air conditioning system can improve the energy efficiency while ensuring the comfort, the energy consumption is reduced, and the intelligent and efficient characteristics are realized by the adjustment model of the comprehensive radiation heat transfer, convection heat transfer and conduction heat transfer, so that the comfortable indoor environment is provided for users.
The problems that the influence on the indoor temperature caused by conduction heat transfer and radiation heat transfer is ignored and the indoor temperature regulation of an air conditioning system is influenced in the center of the prior art are solved.
Drawings
Fig. 1 is a system configuration diagram of an air conditioner monitoring system according to the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Examples
Referring to fig. 1, the present application provides an air conditioner monitoring system, which includes:
the data acquisition system acquires indoor and outdoor data information by adopting a sensor, wherein the sensor comprises a temperature sensor, a humidity sensor, a wind speed sensor, an external temperature sensor, a wall temperature sensor, an indoor air quality sensor, a specific heat capacity sensor and an ultrasonic wind speed sensor, acquires indoor and outdoor real-time data comprising indoor and outdoor temperature, wind speed, wall temperature, air quality index and specific heat capacity through the data acquisition system, and is connected with the data processing system and performs data interaction so as to realize comprehensive monitoring and control of indoor environment.
The data processing system comprises a single board computer, a data processing unit, a storage device, a data transmission module, a sensor interface, a data processing frame, a library and a data visualization tool, is responsible for receiving, processing and analyzing data acquired from each sensor, making decisions and control according to algorithms and logics, using the acquired sensor data, establishing a model through a data processing and analyzing technology, predicting the change trend of indoor temperature based on historical data and external factors, and adjusting according to the set target temperature.
Wherein the single board computer selects Raspberry Pi and Arduino;
the data processing unit comprises an embedded processor and a microcontroller and is used for processing the sensor data and executing an algorithm in real time;
the storage device comprises a hard disk and a Solid State Drive (SSD) and is used for storing the acquired data;
the data transmission module is selected from a Wi-Fi module, a Bluetooth module and an internet of things (IoT) communication module and is used for transmitting data from the sensor to the data processing system;
the sensor interface comprises an analog input, a digital input and output and a serial port and is used for connecting a sensor;
the data processing frame and library select NumPy, pandas and Scikit-learn of Python for data processing, analysis and modeling;
the data visualization tool is selected from Matplotlib and Plotly, and is used for visualizing and displaying the processed data.
The data processing and analysis technique in a data processing system is modeled specifically as follows:
s1, data collection and preprocessing
Obtaining measured data monitored by a data acquisition system and preprocessing the data;
s2, radiation energy transfer model
The influence of wall radiation on indoor temperature is described by adopting a radiation energy transfer model, and a radiation energy transfer formula is adopted, wherein the radiation energy transfer formula is as follows:
establishing a Black-Body Approximation Model blackbody approximation model: assuming that the wall is a blackbody, the radiant energy transfer is calculated using the Stefan-Boltzmann law, with the specific formula:
wherein E represents radiant energy transfer, ε represents the emissivity of the wall, and σ is a Stefan-Boltzmann constant, T_w is the wall exterior surface temperature, and T_i is the indoor temperature;
s3, determining influence of convection heat conduction
Adding the influence of air flow on indoor temperature, introducing a convection heat transfer model, and establishing a specific mode by the following steps:
the flow heat transfer coefficient α is a parameter for expressing the influence of the indoor air flow on the indoor temperature, which is Nu described below;
the flow heat coefficient calculation formula adopts the relation between Nusselt number Nu, reynolds number Re and Plantain number Pr, and the calculation formula is specifically as follows:
wherein C, m, n are empirical parameters derived from expert analysis and actual engineering practices in the field;
s4, determining the surface area and the temperature difference
The user autonomously inputs the wall surface area A, and the data processing system determines the wall surface temperature difference delta T according to the acquired data for subsequent calculation of convection heat transfer quantity;
s5, calculating the convection heat transfer quantity
The convective heat transfer quantity q_conv is calculated using the convective heat transfer coefficient α, the surface area a, and the temperature difference Δt. The specific calculation formula is as follows:
the convection heat transfer quantity q_conv represents heat transfer caused by natural convection;
s6, determining the conduction heat transfer quantity
The conduction heat transfer quantity Q is determined by adopting a Fourier law, and the specific formula is as follows:
wherein k represents the heat conductivity coefficient of the wall material, A represents the surface area, namely the effective heat transfer area, T1 and T2 respectively represent the temperatures of two sides of the wall contacting the surface, and d represents the heat transfer thickness, namely the wall thickness;
s7, indoor temperature regulation algorithm
The influence of radiation heat transfer, convection heat transfer and conduction heat transfer is synthesized, and the indoor temperature regulating quantity is calculated, wherein the specific calculation formula is as follows:
wherein Δt represents an adjustment amount of indoor temperature, E represents radiant energy transfer, a represents a surface area of a wall, h represents a heat radiation heat transfer coefficient, α represents a convection heat transfer coefficient, t_ext and t_i represent temperatures inside and outside the room, respectively, Q represents a conduction heat transfer amount, Δt represents a time step, m represents a mass of indoor air, and C represents a specific heat capacity of indoor air.
The control strategy making system comprises a software platform, an embedded system and a database system, and makes a corresponding control strategy according to the output of the model and the set target temperature, and adjusts the output parameters of the air conditioning system, including the set values of wind speed, temperature and humidity, based on the indoor temperature conditions under the influence of the heat radiation, heat convection and heat conduction factors determined by data processing and analysis.
MATLAB/Simulink, labVIEW, python and C/C++ are selected as software platforms;
the embedded system adopts an embedded computing platform;
the database system is used for storing and managing historical data, algorithm models and control parameters.
The real-time control system is a FreeRTOS, zephyr, linux operating system and comprises a controller and a communication module;
the communication module is used for carrying out data interaction with the sensor, the actuator and other systems, applying the control strategy to the controller of the air conditioning system, adjusting the operation parameters of the air conditioning system in real time through the controller, and controlling the operation state of the air conditioning system according to the temperature change predicted by the model and the actually monitored indoor temperature.
And the feedback regulation system comprises an actuator and a control algorithm, performs feedback regulation according to the difference between the actual indoor temperature and the set target temperature, and gradually regulates the indoor temperature to the target temperature according to the regulation control strategy and the output parameters of the air conditioning system.
The actuator comprises an electric valve controller, an electric fan controller and a compressor controller;
the control algorithm adopts a PID control algorithm;
the user interface and the notification system provide a visual interface, display real-time monitoring data and temperature regulation state, provide real-time notification, alarm and suggestion for users, and send alarm when the temperature is too high or too low.
In the present application, the above is combined with the above matters:
the air conditioner monitoring system provided by the application adopts a radiation energy transfer model, considers the emissivity of a wall, the Stefan-Boltzmann constant and the difference between the surface temperature of the wall and the indoor temperature, and can accurately estimate the influence of radiation heat transfer on the indoor temperature by calculating the radiation energy transfer quantity.
Meanwhile, a convection heat transfer model is introduced, the adjusting effect of indoor air flow on the temperature is considered, the system calculates a flow heat coefficient, and the coefficient is based on a Nusselt number, a Reynolds number and a Plantt number, and by considering the influence of the air flow, the system can accurately estimate the adjusting effect of the convection heat transfer on the indoor temperature.
Meanwhile, the Fourier law is used for calculating the conduction heat transfer quantity, and the heat transfer coefficient, the surface area, the contact surface temperature difference and the heat transfer thickness of the wall material are considered, so that the conduction heat transfer mainly transfers heat through the heat transfer property of the wall, and the indoor temperature adjusting effect of the conduction heat transfer can be accurately estimated.
The method is characterized in that the influences of radiation heat transfer, convection heat transfer and conduction heat transfer are integrated, the adjustment quantity of the indoor temperature is calculated, the adjustment quantity represents the adjustment proposal of the system according to the heat transfer characteristic and the temperature difference, according to the adjustment quantity, the air conditioning system can correspondingly adjust the operation parameters to gradually adjust the indoor temperature to the set target temperature, the change trend of the indoor temperature can be accurately predicted, and a proper control strategy is adopted, so that the air conditioning system can improve the energy efficiency and reduce the energy consumption while ensuring the comfort.
The system has the characteristics of intelligence and high efficiency by integrating the regulation models of radiation heat transfer, convection heat transfer and conduction heat transfer, and provides a comfortable indoor environment for users.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave) means. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the application is not intended to limit the application, but to enable any modification, equivalent or improvement to be made without departing from the spirit and principles of the application.
Claims (7)
1. An air conditioning monitoring system, the system comprising:
the data acquisition system acquires indoor and outdoor data information by adopting a sensor, wherein the sensor comprises a temperature sensor, a humidity sensor, a wind speed sensor, an external temperature sensor, a wall temperature sensor, an indoor air quality sensor, a specific heat capacity sensor and an ultrasonic wind speed sensor;
the data processing system comprises a single board computer, a data processing unit, a storage device, a data transmission module, a sensor interface, a data processing frame, a library and a data visualization tool, is responsible for receiving, processing and analyzing data acquired from each sensor, making decisions and control according to algorithms and logics, using the acquired sensor data, establishing a model through a data processing and analyzing technology, predicting the change trend of indoor temperature based on historical data and external factors, and adjusting according to the set target temperature;
the control strategy making system comprises a software platform, an embedded system and a database system, and makes a corresponding control strategy according to the output of the model and the set target temperature, and adjusts the output parameters of the air conditioning system, including the set values of wind speed, temperature and humidity, based on the indoor temperature conditions under the influence of the heat radiation, heat convection and heat conduction factors determined by data processing and analysis;
the real-time control system is a FreeRTOS, zephyr, linux operating system, and further comprises a controller and a communication module, wherein the communication module is used for carrying out data interaction with the sensor, the actuator and other systems;
the feedback regulation system comprises an actuator and a control algorithm, performs feedback regulation according to the difference between the actual indoor temperature and the set target temperature, and gradually regulates the indoor temperature to the target temperature by regulating the control strategy and the output parameters of the air conditioning system according to the difference;
the user interface and the notification system provide a visual interface, display real-time monitoring data and temperature regulation state, provide real-time notification, alarm and suggestion for users, and send alarm when the temperature is too high or too low.
2. An air conditioner monitoring system according to claim 1, wherein the data processing and analysis technique in the data processing system comprises:
step 1, data collection and preprocessing
Obtaining measured data monitored by a data acquisition system and preprocessing the data;
step 2, radiation energy transfer model
The influence of wall radiation on indoor temperature is described by adopting a radiation energy transfer model, and a radiation energy transfer formula is adopted, wherein the radiation energy transfer formula is as follows:
establishing a Black-Body Approximation Model blackbody approximation model: assuming that the wall is a blackbody, the radiant energy transfer is calculated using the Stefan-Boltzmann law, with the specific formula:
where E represents radiant energy transfer, ε represents the emissivity of the wall, determined by the wall properties, σ is the Stefan-Boltzmann constant, T_w is the wall exterior surface temperature, and T_i is the indoor temperature.
3. An air conditioner monitoring system as set forth in claim 1 wherein the data processing and analysis techniques in the data processing system further comprise:
step 3, convective heat transfer influence determination
Adding the influence of air flow on indoor temperature, introducing a convection heat transfer model, and establishing a specific mode by the following steps:
the flow heat transfer coefficient α is a parameter for expressing the influence of the indoor air flow on the indoor temperature, which is Nu described below;
the flow heat coefficient calculation formula adopts the relation between Nusselt number Nu, reynolds number Re and Plantain number Pr, and the calculation formula is specifically as follows:
wherein C, m, n are empirical parameters derived from expert analysis and actual engineering practices in the field.
4. An air conditioner monitoring system as set forth in claim 1 wherein the data processing and analysis techniques in the data processing system further comprise:
step 4, determining the surface area and the temperature difference
The user autonomously inputs the wall surface area A, and the data processing system determines the wall surface temperature difference delta T according to the acquired data for subsequent calculation of convection heat transfer quantity;
step 5, calculating the convection heat transfer quantity
Using the convective heat transfer coefficient α, the surface area a, and the temperature difference Δt, the convective heat transfer quantity q_conv is calculated by the following specific calculation formula:
the convection heat transfer quantity q_conv represents heat transfer caused by natural convection.
5. An air conditioner monitoring system as set forth in claim 1 wherein the data processing and analysis techniques in the data processing system further comprise:
step 6, determining the conduction heat transfer quantity
The conduction heat transfer quantity Q is determined by adopting a Fourier law, and the specific formula is as follows:
wherein k represents the heat conductivity coefficient of the wall material, A represents the surface area, namely the effective heat transfer area, T1 and T2 respectively represent the temperatures of two sides of the wall contacting the surface, and d represents the heat transfer thickness, namely the wall thickness;
step 7, indoor temperature regulation algorithm
The influence of radiation heat transfer, convection heat transfer and conduction heat transfer is synthesized, and the indoor temperature regulating quantity is calculated, wherein the specific calculation formula is as follows:
wherein Δt represents an adjustment amount of indoor temperature, E represents radiant energy transfer, a represents a surface area of a wall, h represents a heat radiation heat transfer coefficient, α represents a convection heat transfer coefficient, t_ext and t_i represent temperatures inside and outside the room, respectively, Q represents a conduction heat transfer amount, Δt represents a time step, m represents a mass of indoor air, and C represents a specific heat capacity of indoor air.
6. The air conditioner monitoring system according to claim 1, wherein in the data acquisition system, a single board computer is selected from the group consisting of a Raspberry Pi and an Arduino;
the data processing unit comprises an embedded processor and a microcontroller and is used for processing the sensor data and executing an algorithm in real time;
the storage device comprises a hard disk and a Solid State Drive (SSD) and is used for storing the acquired data;
the data transmission module is selected from a Wi-Fi module, a Bluetooth module and an internet of things (IoT) communication module and is used for transmitting data from the sensor to the data processing system;
the sensor interface comprises an analog input, a digital input and output and a serial port and is used for connecting a sensor;
the data processing frame and library select NumPy, pandas and Scikit-learn of Python for data processing, analysis and modeling;
the data visualization tool is selected from Matplotlib and Plotly, and is used for visualizing and displaying the processed data.
7. The air conditioner monitoring system according to claim 1, wherein in the control strategy formulation system, a control strategy is applied to a controller of the air conditioner system, and the controller adjusts the operation parameters of the air conditioner system in real time, and controls the operation state of the air conditioner system according to the predicted temperature change of the model and the actually monitored indoor temperature.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310920859.3A CN116624971A (en) | 2023-07-26 | 2023-07-26 | Air conditioner monitoring system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310920859.3A CN116624971A (en) | 2023-07-26 | 2023-07-26 | Air conditioner monitoring system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116624971A true CN116624971A (en) | 2023-08-22 |
Family
ID=87597736
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310920859.3A Pending CN116624971A (en) | 2023-07-26 | 2023-07-26 | Air conditioner monitoring system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116624971A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117928068A (en) * | 2024-03-14 | 2024-04-26 | 江门市宝士制冷电器有限公司 | Energy-saving temperature air quantity control method and system for mobile air conditioner |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106524404A (en) * | 2016-10-27 | 2017-03-22 | 邯郸美的制冷设备有限公司 | Air conditioner control method and system and air conditioner |
| CN112050397A (en) * | 2020-08-27 | 2020-12-08 | 浙江省邮电工程建设有限公司 | Method and system for regulating and controlling temperature of machine room |
| CN113819596A (en) * | 2021-08-23 | 2021-12-21 | 青岛海尔空调器有限总公司 | Air conditioner control method and air conditioner |
| CN114893859A (en) * | 2022-05-13 | 2022-08-12 | 武汉理工大学 | Ocean platform cabin air conditioning control system and method and storage medium |
| CN115129095A (en) * | 2022-07-08 | 2022-09-30 | 无锡市广盈电力设计有限公司 | Peak-shifting temperature regulating method for transformer substation |
-
2023
- 2023-07-26 CN CN202310920859.3A patent/CN116624971A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106524404A (en) * | 2016-10-27 | 2017-03-22 | 邯郸美的制冷设备有限公司 | Air conditioner control method and system and air conditioner |
| CN112050397A (en) * | 2020-08-27 | 2020-12-08 | 浙江省邮电工程建设有限公司 | Method and system for regulating and controlling temperature of machine room |
| CN113819596A (en) * | 2021-08-23 | 2021-12-21 | 青岛海尔空调器有限总公司 | Air conditioner control method and air conditioner |
| CN114893859A (en) * | 2022-05-13 | 2022-08-12 | 武汉理工大学 | Ocean platform cabin air conditioning control system and method and storage medium |
| CN115129095A (en) * | 2022-07-08 | 2022-09-30 | 无锡市广盈电力设计有限公司 | Peak-shifting temperature regulating method for transformer substation |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117928068A (en) * | 2024-03-14 | 2024-04-26 | 江门市宝士制冷电器有限公司 | Energy-saving temperature air quantity control method and system for mobile air conditioner |
| CN117928068B (en) * | 2024-03-14 | 2024-06-07 | 江门市宝士制冷电器有限公司 | Energy-saving temperature air quantity control method and system for mobile air conditioner |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11366438B2 (en) | Environment control system and environment control method | |
| EP3891441B1 (en) | System and method for personalized thermal comfort control | |
| Ku et al. | Automatic control system for thermal comfort based on predicted mean vote and energy saving | |
| CN108105844B (en) | Intelligent heat exchange station control method based on indoor and outdoor temperature combined compensation | |
| US20150025693A1 (en) | System and method of temperature control | |
| CN110709796B (en) | Heating control parameter optimization method and device based on Internet | |
| CN116624971A (en) | Air conditioner monitoring system | |
| CN107726562A (en) | A kind of computer-readable recording medium and air-conditioning for being used to control temperature | |
| WO2016035121A1 (en) | Air conditioning system control device and air conditioning system control method | |
| EP3769014B1 (en) | Machine-learning method for conditioning individual or shared areas | |
| CN112254287B (en) | Variable-weight multi-model comprehensive prediction central air conditioner tail end air supply control method | |
| US20190360716A1 (en) | Environment estimation device and environment estimation method | |
| CN108644968B (en) | Control method for air conditioning system | |
| CN105157183A (en) | Adjusting and control method for air conditioner | |
| US20180180302A1 (en) | System and method for balancing temperature within a building | |
| CN108592353B (en) | Control method for air conditioning system | |
| CN108826599B (en) | Control method for air conditioning system | |
| CN110726209B (en) | Air conditioner control method and device, storage medium and processor | |
| CN110986249B (en) | Self-adjustment control method and system of air conditioner and air conditioner | |
| Lei et al. | Predictive control of multi-zone variable air volume air-conditioning system based on radial basis function neural network | |
| CN109857177B (en) | Building electrical energy-saving monitoring method | |
| CN108291734A (en) | Method and system for operating heat energy exchanger | |
| TWI746087B (en) | Air conditioning system control method | |
| CN111520867B (en) | Control method and air conditioner | |
| CN114396717B (en) | Fresh air conditioner control method and device, fresh air conditioner, system and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20230822 |