Laundry Washer Color Detection for Automated Load Type Selection
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Solution Overview
Problem
Laundry washing machines often experience suboptimal performance due to user inattentiveness or lack of understanding in selecting manual load types, and existing control methodologies may not be optimal for varying environmental conditions, leading to inefficiencies in energy and water consumption.
Innovation Solution
A laundry washing machine that automates the selection of operational settings using a color detection sensor to capture color composition data, triggered by weight changes, and a controller that initiates color composition data captures when a stable weight is detected, characterizing the load using a color decision algorithm to set appropriate 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 burden and potential for suboptimal performance increase
Solution Approach 1:
The washing machine automatically performs load type classification using color detection sensors and image processing algorithms, eliminating the need for manual user input. The system self-determines the appropriate wash settings based on detected load characteristics, making the system serve itself rather than requiring continuous user intervention.
Solution Approach 2:
The patent replaces manual mechanical selection (buttons, dials, or touch interface for load type selection) with an automated optical detection system. Color sensors capture images of the load, and software algorithms automatically classify the load type, substituting human action with sensor-based detection and computational analysis.
2Reliability
If color detection sensor is used to automate load type selection, then performance optimization is improved, but device complexity increases
Solution Approach 1:
The color detection sensor system serves multiple functions: it detects load type for wash setting optimization, determines appropriate detergent dosage, and can identify fabric care requirements. This multi-functionality justifies the added complexity by providing several benefits from a single sensor integration.
Solution Approach 2:
The patent introduces an image processing algorithm as an intermediary between the color sensor and the control system. This software layer processes the raw sensor data, extracts relevant features, and translates them into actionable load type classifications, simplifying the integration between hardware sensor and control logic.
3Measurement precision
If multiple color composition data captures are initiated, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system performs color composition data captures at periodic intervals during the loading phase, rather than continuously. Multiple captures are taken at strategically spaced moments, and the results are aggregated to improve measurement precision while limiting total energy consumption through controlled, periodic operation.
Solution Approach 2:
The patent takes more color composition measurements than the single minimum required, capturing color data multiple times during loading. This excessive action improves measurement precision and robustness against variability, with the energy cost being acceptable given the significant improvement in load classification accuracy.
4Ease of operation
If weight sensor triggering is implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The weight sensor is used to detect when loading is complete or when significant additions occur, triggering the color detection system in advance of the actual need for load type determination. This preliminary triggering ensures the color data is captured at the optimal moment without requiring continuous monitoring or complex coordination.
Solution Approach 2:
The weight sensor provides feedback about load mass changes, which the control system uses to determine when to activate the color detection sensor. This feedback loop creates an automatic triggering mechanism that adapts to user loading behavior, simplifying operation while managing system complexity through event-driven activation.
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
This solution optimizes wash cycle performance by accurately determining load types and adapting to environmental conditions, reducing user burden and improving energy and water 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.