Artificial intelligence washing machine and controlling method therefor

Patent metadata

Field	Value
Publication number	US-2020109506-A1
Application number	US-201916557411-A
Country	US
Kind code	A1
Filing date	Aug 30, 2019
Priority date	Aug 30, 2018
Publication date	Apr 9, 2020
Grant date	—

Abstract

A control method of washing machine includes: a first detection step of acquiring amount of laundry accommodated in a washing tub; a first washing step of performing washing based on a first laundry amount, when the first laundry amount acquired in the first detection step is equal to or larger than a preset first threshold value; a second detection step of, acquiring the laundry amount accommodated in the washing tub by an output of an output layer of an artificial neural network while using a current value inputted to a motor for rotating and acceleration of the washing tub as an input data of an input layer of the artificial neural network previously learned by machine learning; and a second washing step of performing washing based on a second laundry amount, when the second laundry amount acquired in the second detection step is smaller than the first threshold value.

First claim

What is claimed is:

1 . A method of controlling a washing machine, comprising:
acquiring, in a first detection step, a first laundry amount accommodated in a washing tub; determining that the first laundry amount acquired in the first detection step meets a threshold value; responsive to the determination that the first laundry amount acquired in the first detection step meets the threshold value, performing, in a first washing step, washing based on the first laundry amount; acquiring, in a second detection step, a second laundry amount accommodated in the washing tub, the second laundry amount being an output of an artificial neural network that uses a current value applied to a motor for rotating and accelerating the washing tub as input data, the artificial neural network having been previously trained by machine learning; determining that the second laundry amount acquired in the second detection step does not meet the threshold value; responsive to the determination that the second laundry amount acquired in the second detection step does not meet the threshold value, performing, in a second washing step, washing based on the second laundry amount.

2 . The method of claim 1 , wherein the second detection step comprises:
accelerating and rotating the washing tub from a first rotation speed up to a second rotation speed that is faster than the first rotation speed; acquiring the current value applied to the motor in a section in which the washing tub is accelerated and rotated to the second rotation speed; and acquiring the second laundry amount by the output of the artificial neural network while using the current value as the input for the artificial neural network.

3 . The method of claim 2 , wherein the second rotation speed is a rotation speed at which the laundry is rotated integrally with the washing tub.

4 . The method of claim 2 , wherein accelerating and rotating the washing tub comprises:
accelerating the washing tub at a constant acceleration from the first rotation speed up to the second rotation speed.

5 . The method of claim 2 , wherein acquiring the second laundry amount comprises:
using the current value applied to the motor as the input data in a section in which the rotation speed of the washing tub is accelerated from the first rotation speed up to the second rotation speed.

6 . The method of claim 2 , wherein the second detection step further comprises detecting a rotation speed of the washing tub.

7 . The method of claim 6 , wherein acquiring the second laundry amount comprises:
selecting a current value corresponding to a section in which the washing tub is accelerated from the first rotation speed up to the second rotation speed among current values acquired based on the detected rotation speed of the washing tub; and using the selected current value as the input data for the artificial neural network.

8 . The method of claim 1 , wherein the second detection step comprises:
acquiring a state of the laundry accommodated in the washing tub by the output of the artificial neural network based on applying the current value as the input data for the artificial neural network.

9 . The method of claim 8 , wherein the second washing step comprises performing washing based on the second laundry amount and the state of the laundry.

10 . The method of claim 8 , wherein the state of the laundry is classified by a risk of abrasion of the laundry and a washing intensity.

11 . The method of claim 8 , wherein the second washing step comprises:
selecting one of a plurality of washing modes classified by a risk of abrasion of the laundry and a washing intensity based on the second laundry amount and the laundry state; and performing washing according to the selected washing mode.

12 . A washing machine control apparatus, comprising:
acquiring, in a first detection step, a first laundry amount accommodated in a washing tub; determining that the first laundry amount acquired in the first detection step meets a threshold value; responsive to the determination that the first laundry amount acquired in the first detection step meets the threshold value, performing, in a first washing step, washing based on the first laundry amount; acquiring, in a second detection step, a second laundry amount accommodated in the washing tub, the second laundry amount being an output of an artificial neural network that uses a current value applied to a motor for rotating and accelerating the washing tub as input data, the artificial neural network having been previously trained by machine learning; determining that the second laundry amount acquired in the second detection step does not meet the threshold value; responsive to the determination that the second laundry amount acquired in the second detection step does not meet the threshold value, performing, in a second washing step, washing based on the second laundry amount.

13 . The apparatus of claim 12 , wherein the second detection step comprises:
accelerating and rotating the washing tub from a first rotation speed up to a second rotation speed that is faster than the first rotation speed; acquiring the current value applied to the motor in a section in which the washing tub is accelerated and rotated to the second rotation speed; and acquiring the second laundry amount by the output of the artificial neural network while using the current value as the input for the artificial neural network.

14 . The apparatus of claim 13 , wherein the second rotation speed is a rotation speed at which the laundry is rotated integrally with the washing tub.

15 . The apparatus of claim 13 , wherein the second detection step comprises detecting a rotation speed of the washing tub.

16 . The apparatus of claim 12 , wherein the second detection step comprises:
acquiring a state of the laundry accommodated in the washing tub by the output of the artificial neural network based on applying the current value as the input data for the artificial neural network.

17 . The apparatus of claim 16 , wherein the second washing step comprises performing washing based on the second laundry amount and the state of the laundry.

18 . The apparatus of claim 16 , wherein the state of the laundry is classified by a risk of abrasion of the laundry and a washing intensity.

19 . The apparatus of claim 16 , wherein the second washing step comprises:
selecting one of a plurality of washing modes classified by a risk of abrasion of the laundry and a washing intensity, based on the second laundry amount and the laundry state; and performing washing according to the selected washing mode.

20 . The apparatus of claim 13 , wherein the second detection step comprises:
accelerating the washing tub at a constant acceleration from the first rotation speed up to the second rotation speed.

Assignees

• Lg Electronics Inc

Inventors

• Im Myunghun
• Jung Hwanjin
• Yu Seonhwa
• Kim Sunggyun
• Woo Kyungchul

Classifications

• D06F34/18 Primary

  Condition of the laundry, e.g. nature or weight · CPC title

• D06F2103/04

  Quantity, e.g. weight or variation of weight · CPC title

• D06F2105/00

  Systems or parameters controlled or affected by the control systems of washing machines, washer-dryers or laundry dryers · CPC title

• G06N3/08

  Learning methods · CPC title

• D06F2202/10

  Textiles & Paper · mapped topic