Washing Machine Load Detection Using AI Motor Current Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional washing machines struggle to accurately detect laundry amount and type, leading to inadequate washing performance and potential damage to laundry, as they rely solely on measured laundry amount without considering material characteristics.
Innovation Solution
A washing machine employing machine learning and an artificial neural network to detect laundry amount and type by analyzing motor current patterns during accelerated rotation, allowing for adaptive washing mode selection based on laundry state and material classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional washing machines rely solely on measured laundry amount without considering material characteristics, then the device complexity is low, but the washing performance is insufficient and laundry damage occurs
Solution Approach 1:
The patent replaces conventional mechanical measurement methods with an artificial neural network-based detection system that analyzes motor current patterns. The controller uses machine learning models to infer laundry amount and material type from electrical characteristics, eliminating the need for physical sensors and achieving both high reliability and low device complexity
Solution Approach 2:
The patent introduces motor current as an intermediary parameter that indirectly reflects laundry characteristics. By analyzing the current drawn by the motor during drum rotation, the system infers information about laundry amount and material type without direct contact or additional sensing hardware
2Measurement precision
If washing machines use only laundry amount measurement, then the ease of operation is high, but the measurement precision of laundry characteristics is insufficient
Solution Approach 1:
The system performs self-detection by automatically analyzing motor current patterns without requiring user input. The artificial neural network autonomously processes the electrical signals to determine laundry characteristics, eliminating manual measurement steps while maintaining operational simplicity
Solution Approach 2:
The patent transforms the detection approach by changing from direct physical measurement to indirect electrical parameter analysis. By monitoring motor current variations during drum acceleration and rotation, the system extracts detailed laundry characteristics that reveal both amount and material type with high precision
3Manufacturing precision
If washing machines set washing operation based only on laundry amount, then the productivity is high, but the manufacturing precision of washing quality is insufficient
Solution Approach 1:
The patent implements dynamic washing parameter adjustment based on real-time laundry characterization. The system modifies washing intensity, water volume, and cycle duration according to the specific laundry material type and amount detected, ensuring optimal washing quality for each load while maintaining efficient operation through automated decision-making
Data Source
AI summary
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.