Laundry washing machine color composition analysis during loading
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Solution Overview
Problem
Laundry washing machines often experience suboptimal performance due to user inattentiveness in load type selection and varying environmental conditions, leading to inefficient energy and water consumption.
Innovation Solution
A laundry washing machine equipped with a color detection sensor and weight sensor automates the selection of operational settings based on color composition data and stable weight detection, using a controller to initiate color composition data captures and set wash cycle settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual load type selection is provided, then user control over wash settings is improved, but user inattentiveness or lack of understanding leads to suboptimal performance
Solution Approach 1:
The washing machine automatically performs load type detection and setting selection without requiring user intervention. The color detection sensor captures images of the load, and the controller automatically analyzes the color composition to determine the appropriate load type and configure wash settings, making the system self-sufficient in the detection and decision-making process.
Solution Approach 2:
The manual mechanical selection process by the user is replaced with an automated optical detection system. The color detection sensor captures visual information about the load, and the controller processes this data to automatically determine load type, substituting the manual selection mechanism with an automated sensing and processing system.
2Reliability
If control methodologies are optimized for particular environmental conditions, then washing performance is improved, but performance degrades when installed in different environmental conditions
Solution Approach 1:
The control methodology dynamically adapts to different environmental conditions by using real-time color detection data. The system adjusts its load type determination based on the actual visual characteristics of the load and environmental factors captured by the sensor, rather than relying on fixed optimized settings for specific conditions.
Solution Approach 2:
The system changes its operational parameters based on detected environmental conditions and load characteristics. The controller modifies wash settings such as water temperature, cycle duration, and agitation level based on the color composition analysis, allowing the system to adapt to varying environmental conditions while maintaining optimal performance.
3Measurement precision
If color composition data is captured continuously, then load type detection accuracy is improved, but energy and water consumption increase
Solution Approach 1:
The color detection sensor captures images at periodic intervals during the loading process rather than continuously. The controller initiates color composition data captures at specific moments based on weight sensor triggers, performing detection periodically when loads are added or removed, which reduces energy consumption while maintaining adequate detection accuracy.
Solution Approach 2:
The system performs color detection during the loading phase before the wash cycle begins. By capturing and analyzing color composition data in advance during loading, the system determines load type and configures settings beforehand, eliminating the need for continuous monitoring during the actual wash cycle and reducing overall energy consumption.
4Measurement precision
If multiple color composition data captures are initiated, then load characterization accuracy is improved, but device complexity increases
Solution Approach 1:
The control process is segmented into distinct phases: loading phase detection, wash phase execution, and rinse phase adjustment. The controller captures color composition data at specific segments (when weight changes indicate loading/unloading), processes this segmented information to determine load type, and applies appropriate settings, reducing overall control complexity through structured phase-based operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances washing machine performance by optimizing settings for different load types and environmental conditions, reducing user burden and improving efficiency.
Implementation Method 1
a color detection sensor positioned to capture color composition data of a load of articles as the load of articles is added to the wash tub
Implementation Method 2
a weight sensor operatively coupled to the wash tub to sense a weight of the load of articles as the load of articles is added to the wash tub
Data Source
AI summary
A laundry washing machine and method automate the selection of various operational settings for a wash cycle based in part on color composition data collected from a load of articles using a color detection sensor. In some instances, the capture of color composition data is triggered by detected weight changes sensed by a weight sensor as the load of articles is added to a wash tub, and is based in part on the detection of a stable weight in the wash tub for at least a predetermined duration. In addition, in some instances, color compensation data may be used to characterize a load of articles based in part on a color decision algorithm that assigns pixels in the color compensation data to different color categories.