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Bath temperature prediction method and water heater

A water heater and predictive model technology, applied in neural learning methods, neural architecture, biological neural network models, etc., can solve the problems of low water consumption, waste of resources, large randomness, etc., to facilitate recording and storage, and save storage space. , easy to recall effect

Inactive Publication Date: 2018-04-17
QINGDAO ECONOMIC & TECHN DEV ZONE HAIER WATER HEATER
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Existing electric water heaters can only set the temperature on the display screen, and users don’t know how much water they need for bathing, and how much temperature they need to heat. The existing schemes that are relatively similar are based on the energy conservation law formula Q=CMΔt, to calculate M 混合水 ×T 混合水 =(M 混合水 -M 热水 )×T 冷水 +M 热水 ×T 热水 , the target temperature can be obtained
[0003] But in practical application, the hot water in the tank cannot be released completely, there must be a coefficient of hot water output rate, the size of the coefficient is related to the specific structure of the machine, the temperature of tap water, the size of the bathing flow, and whether there is energy supplement during the bathing process ( That is, whether the machine is reheated or whether the 3D function is turned on) and many other factors, purely relying on physical methods to analyze the target temperature has great limitations, and the prediction is very random

Method used

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  • Bath temperature prediction method and water heater
  • Bath temperature prediction method and water heater
  • Bath temperature prediction method and water heater

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Experimental program
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Effect test

Embodiment 1

[0070] like figure 2 As shown, the present embodiment proposes a method for predicting the bathing temperature, which is used for a water heater, and the steps include:

[0071] S1, obtain the water flow of the water heater, the inlet water temperature and the historical water consumption for bathing;

[0072] S2, input the water flow rate, inlet water temperature and historical bathing water consumption into the neural network prediction model, and obtain the target temperature value through the neural network prediction model processing.

[0073] In the above-mentioned technical solution, the water heater will record the recent user's water consumption in the storage system. Inlet water temperature and historical bathing water consumption stored in the storage system, the three values ​​are input into the neural network prediction model that has been set, so that the target temperature that the user needs to set can be obtained through the calculation of the neural network...

Embodiment 2

[0077] like image 3 As shown, when the neural network prediction model is a BP neural network, a step S0 is added on the basis of Embodiment 1, including:

[0078] S0, establish a BP neural network model, and obtain the relevant parameters of the BP neural network model. When using the BP neural network model, the BP neural network must first be trained, that is, a large amount of data is input into the established BP neural network, and the BP neural network is trained. Adjust the relevant variables in , and finally get the relevant parameters closest to the true value, including: the weight from the input layer to the hidden layer, the threshold from the input layer to the hidden layer, the weight from the hidden layer to the output layer, the hidden layer to the threshold of the output layer.

[0079] Because the BP neural network model has the ability to approach any nonlinear continuous function in theory, it is widely used in nonlinear system modeling. The BP neural ne...

Embodiment 3

[0107] like Figure 7 As shown, the embodiment of the present invention proposes a water heater, using the method for predicting bathing temperature described in the first embodiment above, including:

[0108] Box body 1, water flow sensor 2, water inlet temperature sensor 3, storage system (not shown in the figure), inner tank temperature sensor 4 and controller 5, water inlet and water outlet are provided on the box body 1, The water flow sensor 2 and the water inlet temperature sensor 3 are both arranged at the water inlet to detect the water flow and the inlet water temperature of the water inlet, the inner tank temperature sensor 4 is arranged inside the box body 1, and the controller 5 is arranged On the box body 1, the water flow sensor 2, the water inlet temperature sensor 3, the storage system and the inner tank temperature sensor 4 are all connected to the controller 5;

[0109] A neural network prediction model is stored in the controller 5, and the water flow, inl...

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Abstract

The invention discloses a bath temperature prediction method and a water heater. The bath temperature prediction method comprises the steps that S1, the water flow rate, the water inlet temperature and the historical water consumption for bath of the water heater are acquired; and S2, the water flow rate, the water inlet temperature and the historical water consumption for bath are inputted to a neural network prediction model so that the target temperature value is obtained through processing of the neural network prediction model. With application of the technical scheme, the neural networkprediction model integrated in the controller can be directly utilized to determine the target temperature and the water heater is enabled to perform automatic setting more intelligently according tothe target temperature so that the target temperature most suitable for the user demand can be provided for the user according to different bath habits of the user and the current condition of the water temperature and the water flow and use can be facilitated for the user.

Description

technical field [0001] The invention belongs to the field of home appliances, and in particular relates to a method for predicting bath temperature and a water heater. Background technique [0002] Existing electric water heaters can only set the temperature on the display screen, and users don’t know how much water they need for bathing, and how much temperature they need to heat. The existing schemes that are relatively similar are based on the energy conservation law formula Q=CMΔt, to calculate M 混合水 × T 混合水 =(M 混合水 -M 热水 )×T 冷水 +M 热水 × T 热水 , the target temperature can be obtained. [0003] But in practical application, the hot water in the tank cannot be released completely, there must be a coefficient of hot water output rate, the size of the coefficient is related to the specific structure of the machine, the temperature of tap water, the size of the bathing flow, and whether there is energy supplement during the bathing process ( That is, whether the machine...

Claims

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Application Information

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IPC IPC(8): G06N3/08G06N3/04
CPCG06N3/04G06N3/084G06N3/044
Inventor 王爽陈小雷张斌李雪
Owner QINGDAO ECONOMIC & TECHN DEV ZONE HAIER WATER HEATER
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