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Intelligent refrigeration comfortable air conditioner based on deep learning

A deep learning, air conditioning technology, applied in the control input involving air characteristics, space heating and ventilation, heating and ventilation control systems, etc., can solve problems such as poor user experience, secondary air conditioning refrigeration control can not be customized according to user needs and other problems , to reduce the number of operations, maintain stability and security, and improve experience

Active Publication Date: 2022-07-01
湖南大友恒集团有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Through the above analysis, the existing problems and defects of the prior art are: prior art 1 and prior art 2 air-conditioning refrigeration control cannot be customized according to the individual needs of users, and the user experience is poor

Method used

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  • Intelligent refrigeration comfortable air conditioner based on deep learning
  • Intelligent refrigeration comfortable air conditioner based on deep learning
  • Intelligent refrigeration comfortable air conditioner based on deep learning

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] like figure 1 As shown, the deep learning-based intelligent refrigeration and comfort air conditioner provided by the present invention includes:

[0060] User comfort temperature database establishment module, used to store user behavior habits, capture and assign weights to the stored user behavior habits data;

[0061] A data acquisition module is used to acquire environmental data and operation data when the air conditioner is working; wherein, the environmental data includes data corresponding to each influencing factor; a deep learning library is used to program and construct a corresponding deep learning model, based on the environmental data and operation data Data, train the deep learning model, determine the influence coefficient of each influence factor on the air conditioning and refrigeration effect, and construct the correlation function corresponding to each influence factor;

[0062] The depth generation model forming module is used to establish the thr...

Embodiment 2

[0066] On the basis of Embodiment 1, the user behavior habits of the user comfort temperature database establishment module of the embodiment of the present invention include: the customer routinely adjusts the air speed, air outlet temperature, cooling mode, heating mode, dehumidification mode, outlet air direction and operation of the air conditioner parameter. When the user turns on the machine as usual and adjusts the wind speed, air outlet temperature, cooling mode, heating mode, dehumidification mode, outlet air direction and operating parameters, the user comfort temperature database records the air speed, air outlet temperature, cooling mode, heating mode, dehumidification mode in real time The data of mode, outlet wind direction and operating parameters are stored. After storage, they are divided into different categories according to the different operating parameters. Record stack, and then import the user's comfortable temperature database. When the indoor temperatu...

Embodiment 3

[0069] like figure 2 As shown, on the basis of Embodiment 1, the user comfort temperature database establishment module provided by the embodiment of the present invention includes:

[0070] The first distribution weight sub-module is used to input the collected and stored data of user behavior habits into the first-level deep neural network, deploy and train the obtained first-level neural network model, and generate the stored user behavior habits of the first distribution weight. data;

[0071] The second assigning weight submodule is used to construct the second-level deep neural network model, the input is the data of the user's behavior and habits stored, and the output is the data of the user's behavior and habits stored in the second assigning weight;

[0072] The storage data processing sub-module is used to input the collected data of the stored user behavior habits of the first distribution weight and the stored user behavior habits of the second distribution weig...

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Abstract

The invention belongs to the technical field of automatic control of air conditioners, and discloses an intelligent refrigeration comfortable air conditioner based on deep learning, a user comfortable temperature database establishment module is used for storing user behavior habits, capturing the stored data of the user behavior habits and distributing weights; acquiring environment data and operation data when the air conditioner works; a deep learning model is trained, and the influence coefficient of each influence factor on the air conditioner refrigeration effect is determined; according to the parameters of the influence factors, a three-dimensional heat effect equation of the air conditioner is established, and the temperature field distribution condition of the air conditioner is solved; establishing a deep generation model, and forming the deep generation model of the air conditioner under the deep learning multilayer network according to the basic parameters of the air conditioner; and a depth generation model is selected and pre-trained, the air conditioner cooling schemes obtained through the ambiguity resolution methods and the corresponding simulation result data serve as input of the depth generation model, and a final air conditioner optimized refrigeration scheme is output. The invention provides an optimal refrigeration scheme.

Description

technical field [0001] The invention belongs to the technical field of automatic control of air conditioners, and in particular relates to an intelligent refrigeration and comfortable air conditioner based on deep learning. Background technique [0002] Deep Learning (DL, Deep Learning) is a new research direction in the field of Machine Learning (ML, Machine Learning), which is introduced into Machine Learning to make it closer to the original goal - Artificial Intelligence (AI, Artificial Intelligence). Deep learning is to learn the inherent laws and representation levels of sample data, and the information obtained during these learning processes is of great help to the interpretation of data such as text, images and sounds. Its ultimate goal is to enable machines to have the ability to analyze and learn like humans, and to recognize data such as words, images, and sounds. Deep learning is a complex machine learning algorithm that has achieved results in speech and image...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): F24F11/54F24F11/65F24F11/64F24F11/86F24F11/61F24F110/10F24F110/30
CPCF24F11/54F24F11/65F24F11/64F24F11/86F24F11/61F24F2110/10F24F2110/30Y02B30/70
Inventor 王旭
Owner 湖南大友恒集团有限公司
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