Washing Machine Motor Current Sensing for Laundry Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional washing machines often fail to accurately sense laundry weight and quality, leading to variations in washing performance and potential damage to laundry, as they primarily rely on weight-based settings without considering the material, water content, and composition of the laundry.
Innovation Solution
A washing machine utilizing an artificial neural network based on machine learning to rapidly and accurately sense laundry weight and quality by analyzing current patterns during accelerated rotation, allowing for customized washing cycles based on the hardness, water content, and composition of the laundry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If washing operation is set based on laundry weight alone, then washing machine operation is simplified, but washing performance becomes insufficient and laundry may be damaged
Solution Approach 1:
The patent changes the sensing parameters from only weight-based measurements to multiple parameters including current patterns during accelerated rotation, hardness, water content, and composition. This allows the washing machine to differentiate between various laundry types (e.g., denim vs. synthetic) and adjust washing operations accordingly, improving washing performance while maintaining ease of operation through automated multi-parameter analysis
2Device complexity
If conventional sensing methods are used, then device complexity is low, but measurement precision of laundry weight and quality is insufficient
Solution Approach 1:
The patent replaces conventional mechanical weight-sensing methods with an artificial neural network-based sensing system that analyzes current patterns during motor acceleration. This substitution enables more precise measurement of both laundry weight and quality characteristics (hardness, water content, composition) without requiring complex mechanical sensing hardware, thereby improving measurement precision while keeping device complexity manageable
Data Source
AI summary
Disclosed is a method of controlling a washing machine, the method including determining the state of laundry received in a washing tub from output of an output layer of an artificial neural network pre-trained based on machine learning using a current value supplied to a motor configured to rotate the washing tub during accelerated rotation of the washing tub as input data of an input layer of the artificial neural network (a first sensing step), selecting one of a plurality of washing modes classified in consideration of the wear degree of laundry or washing strength based on the state of the laundry, and performing washing according to the selected washing mode (a washing cycle step).