Household air conditioner remote intelligent control practical training platform and control method

Abstract

The invention discloses a household air conditioner remote intelligent control practical training platform and a control method. Comprising a practical training rack, an R32 / R290 refrigerant air conditioner, a digital thermometer, a voltmeter, an ampere meter, an electric energy meter, a high pressure gauge, a low pressure gauge, a single-chip microcomputer air conditioner controller, a touch control upper computer module, an explosion-proof leakage protection switch, an explosion-proof vacuum pump, a combustible gas detector, a combustible gas probe, an exhaust device and a tool cabinet. The system is provided with an Internet of Things management system, a refrigeration digital twin system and an intelligent examination system. The household air conditioner practical training platform has the advantages of being safe in experiment, efficient in practical training teaching, convenient and rapid in remote monitoring, simple in thermodynamic parameter simulation and optimization, and capable of improving energy consumption optimization efficiency.

Description

Technical Field

[0001] The present invention relates to the field of refrigeration and air-conditioning technology experiments and teaching, and in particular to a remote intelligent control training platform for household air conditioners. The training platform combines Internet of Things remote intelligent control diagnosis and virtual simulation to enable technicians and students to deeply understand the physical principles and complex thermodynamic processes of air-conditioning operation. Through actual operation and data measurement and analysis, they can master the key technologies and methods for optimizing air-conditioning performance. The training platform is suitable for practical teaching and skills assessment of air-conditioning installation, commissioning, fault diagnosis and maintenance skills. Background Art

[0002] Existing training platforms (such as the new energy vehicle electric air conditioning training platform with patent number CN 210895977 U) only integrate air conditioners, electrical control circuits and fault simulation modules, support refrigeration system pressure detection, temperature measurement and fault point setting, lack remote control functions, and cannot simulate the communication protocols of modern smart air conditioners and interact with the cloud; the refrigerants used are R22 or R410A, which are not environmentally friendly; training equipment for new refrigerants R32 or R290 lacks explosion-proof design, combustible gas leak monitoring and emergency response modules, and poses safety hazards of combustion and explosion; existing equipment cannot simulate the dynamic operating status of real air-conditioning systems, lacks adaptive fault diagnosis, energy consumption optimization algorithms and digital twin simulation functions, and experimental analysis requires manual recording of parameters, which cannot achieve multi-station collaborative management and automated assessment through the Internet of Things. Summary of the Invention

[0003] The purpose of the present invention is to provide a household air conditioner remote intelligent control training platform and control method, which has the advantages of experimental safety, efficient training, remote monitoring, thermodynamic parameter simulation optimization, and improved energy consumption optimization efficiency.

[0004] In order to solve the above-mentioned background technical problems, the technical solution of the present invention is:

[0005] A household air conditioner remote intelligent control training platform and control method include a training platform, an R32 / R290 refrigerant air conditioner, a digital thermometer, a voltmeter, an ammeter, an electric energy meter, high and low pressure gauges, a single-chip air conditioner controller and a touch-screen host computer module, an explosion-proof leakage protection switch, an explosion-proof vacuum pump, a combustible gas detector, a combustible gas probe and exhaust device, and a tool cabinet. Its technical features are: using an explosion-proof electrical system, combined with an Internet of Things management system, a refrigeration digital twin system, and an intelligent assessment system.

[0006] IoT management system: includes a data acquisition module and a remote control module. The data acquisition module can obtain temperature, pressure, and voltage data in real time, supports historical data storage and abnormal alarm functions, and performs thermal analysis algorithms based on the collected data to generate curves and pressure-enthalpy diagrams. The remote control module issues instructions through the MQTT protocol to dynamically adjust the compressor frequency, electronic expansion valve opening, and fan speed.

[0007] Refrigeration digital twin system: Builds a virtual air conditioner model based on C# and WPF, supports 2D / 3D view switching and real-time mapping of physical parameters (such as cooling capacity and energy efficiency ratio); is compatible with Mitsubishi FX, Siemens S7 series PLCs and STM32 microcontrollers, and supports signal synchronization between virtual models and real equipment.

[0008] Intelligent Assessment System: This system features an AI scoring engine that analyzes energy efficiency optimization results based on the LSTM power consumption prediction model and generates multi-objective optimization recommendations using the NSGA-II algorithm. This system also features an automated assessment process: the teacher configures the fault scenario, the student performs remote diagnosis, and the system automatically generates a scoring report (including indicators such as fault location accuracy and repair time).

[0009] Explosion-proof electrical system: In view of the flammable characteristics of R290 / R32 refrigerants, explosion-proof electrical components, leakage protection switches, and flammable refrigerant detection devices are used. The explosion-proof vacuum pump, air conditioner outdoor unit, and combustible gas detector are placed on the table of the training platform. The combustible gas detection head and exhaust device are installed at the bottom of the training platform.

[0010] The above technical solution has the following beneficial effects:

[0011] The present invention provides a household air-conditioning remote intelligent control training platform and control method, introduces an Internet of Things management system, a refrigeration digital twin system, and an intelligent assessment system into a traditional training platform, and configures an explosion-proof electrical system, so that the household air-conditioning training platform has the advantages of safe experiments, efficient training and teaching, convenient and fast remote monitoring, simple thermodynamic parameter simulation and optimization, and improved energy consumption optimization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other implementation drawings based on the provided drawings without inventive effort.

[0013] The structures, proportions, sizes, etc. illustrated in this specification are intended only to complement the contents disclosed herein and to facilitate understanding and reading by persons familiar with the art. They are not intended to limit the conditions under which the present invention may be implemented and therefore have no substantive technical significance. Any structural modifications, changes in proportions, or adjustments in sizes, without affecting the efficacy and objectives of the present invention, shall still fall within the scope of the technical contents disclosed herein.

[0014] Figure 1 This is a structural diagram of a household air conditioner remote intelligent control training platform and control method example 1 of the present invention;

[0015] Figure 2 This is a structural diagram of a second example of a household air conditioner remote intelligent control training platform and control method according to the present invention; DETAILED DESCRIPTION

[0016] The following is a further description of specific embodiments of the present invention in conjunction with the accompanying drawings. It should be noted that the description of these embodiments is intended to facilitate understanding of the present invention and does not constitute a limitation of the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0017] See also Figure 1-Figure 2 As shown, the present invention discloses a remote intelligent control training platform for household air conditioners and a control method. The platform includes a training stand 15, an R32 / R290 refrigerant air conditioner 2 or 14, high and low pressure gauges 1, a digital thermometer 3, a voltmeter 4, an ammeter 5, an energy meter 6, an explosion-proof leakage protection switch 7, a single-chip air conditioner controller and a touch-screen host computer module 8, a combustible gas detector 9, a combustible gas probe 11 and an exhaust device 12, an explosion-proof vacuum pump 13, and a tool cabinet 10. The platform is technically characterized by employing an explosion-proof electrical system, an Internet of Things management system, a refrigeration digital twin system, and an intelligent assessment system.

[0018] Example 1

[0019] refer to Figure 1 The indoor unit and central control module of the wall-mounted household air conditioner are placed above the training table.

[0020] Due to the flammability of R290 / R32 refrigerants, electrical components are designed and manufactured to be explosion-proof. An explosion-proof vacuum pump, an R290 / R32 air conditioner (outdoor unit) 14, and a combustible gas detector 9 are placed on the training table. A combustible gas detector 11 and an exhaust device 12 are installed at the bottom of the training table (both refrigerants R32 and R290 have a higher density than air) to ensure safe operation.

[0021] IoT Management System: Data Acquisition Module: Acquires temperature, pressure, and voltage data in real time, supporting historical data storage and anomaly alarms (such as setting pressure anomaly thresholds). Data Analysis: Runs thermal analysis algorithms on real-time data acquired by the data acquisition module, generating graphs and pressure-enthalpy diagrams that are displayed on the touchscreen, providing operators with real-time data support and facilitating equipment monitoring and optimization decisions. Remote Control Module: Issues commands via the MQTT protocol to dynamically adjust compressor frequency, electronic expansion valve opening, and fan speed. Students are guided to analyze the received data, enabling remote practical teaching and training.

[0022] Refrigeration digital twin system: Model construction: Build an air conditioning virtual model based on C#+WPF, supporting 2D / 3D view switching and real-time mapping of physical parameters (such as cooling capacity and energy efficiency ratio); IO interactive interface: compatible with Mitsubishi FX, Siemens S7 series PLCs and STM32 microcontrollers, supporting signal synchronization between virtual models and real equipment.

[0023] Intelligent Assessment System: AI Scoring Engine: Analyzes energy efficiency optimization results based on the LSTM power consumption prediction model and generates multi-objective optimization recommendations using the NSGA-II algorithm. Automated Assessment Process: Teacher configures fault scenarios → Student performs remote diagnosis → The system automatically generates a scoring report (including indicators such as fault location accuracy and repair time).

[0024] Example 2

[0025] refer to Figure 2 The indoor unit of the cabinet-type household air conditioner is placed independently on the side of the training table.

[0026] The remaining structures and principles are the same as those in the first embodiment and will not be described again here.

[0027] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. It is apparent to those skilled in the art that various changes, modifications, substitutions, and variations to these embodiments may be made without departing from the principles and spirit of the present invention, and these changes and modifications still fall within the scope of protection of the present invention.

Claims

1. A household air conditioner remote intelligent control training platform and control method, comprising a training platform (15), an R32 / R290 refrigerant air conditioner (2, 14), high and low pressure gauges (1), a digital thermometer (3), a voltmeter (4), an ammeter (5), an electric energy meter (6), an explosion-proof leakage protection switch (7), a single-chip air conditioner controller and a touch screen module (8), a combustible gas detector (9), a combustible gas probe (11) and an exhaust device (12), an explosion-proof vacuum pump (13), and a tool cabinet (10). The technical features of the training platform are: an explosion-proof electrical system is used, and an Internet of Things management system, a refrigeration digital twin system, and an intelligent assessment system are used.

2. A household air conditioner remote intelligent control training platform and control method according to claim 1, characterized in that: The Internet of Things management system is equipped with a data acquisition module and a remote control module. The data acquisition module has the function of acquiring temperature, pressure, and voltage data in real time, can perform data analysis, store alarms, and generate pressure-enthalpy diagram curves; the remote control module issues instructions through the MQTT protocol, can dynamically adjust the frequency, speed, and expansion valve opening, and perform data analysis and simulation.

3. The household air conditioner remote intelligent control training platform and control method according to claim 1, characterized in that: The refrigeration digital twin system can establish a virtual thermodynamic model of air conditioning based on C#+WPF, supports switching between 2D and 3D views, and has real-time mapping functions for cooling capacity and energy efficiency ratio parameters.

4. The household air conditioner remote intelligent control training platform and control method according to claim 1, characterized in that: The intelligent assessment system has the function of analyzing energy consumption optimization effects based on the LSTM electricity consumption prediction model, generating optimization plans in combination with the NSGA-II algorithm, and automating the assessment process.

5. The household air conditioner remote intelligent control training platform and control method according to claim 1, characterized in that: The explosion-proof electrical system comprises an explosion-proof vacuum pump (13), an R32 / 290 refrigerant air-conditioning outdoor unit (14), and a combustible gas detector (9) placed together on the table of a training platform. The combustible gas detection head (11) and the exhaust device (12) are installed at the bottom of the training platform. Other electrical components are all designed to be explosion-proof.

Images