Laundry treating appliance with load surface area detection
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Solution Overview
Problem
Laundry treating appliances often require manual selection of cycles by users, which can lead to inefficient use of resources and suboptimal treatment due to the lack of real-time data on laundry load size and distribution, especially for smaller loads where manual settings may result in inappropriate amounts of treating chemistry and energy usage.
Innovation Solution
Incorporating an imaging device and controller that determine the surface area and number of items in the treating chamber, allowing for automatic adjustment of operational parameters such as rotational speed, temperature, and chemistry dispensing to optimize the drying process based on real-time image analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual cycle selection is used, then device complexity is reduced, but treatment precision deteriorates due to lack of real-time load data
Solution Approach 1:
The patent replaces manual mechanical cycle selection with an automated optical imaging system. The imaging device captures images of the laundry load, and image analysis automatically determines load characteristics, substituting the mechanical act of manual cycle selection with an optical-mechanical system that provides precise, data-driven treatment parameters.
Solution Approach 2:
The system enables self-service by allowing the laundry treating appliance to automatically determine treatment parameters based on image analysis of the load. The controller autonomously selects appropriate cycles and adjusts treatment conditions without requiring user knowledge or manual intervention, making the system self-optimizing.
2Ease of operation
If default treatment parameters are used, then ease of operation is improved, but energy efficiency deteriorates due to inappropriate chemistry and energy usage
Solution Approach 1:
The system implements feedback by using image analysis to continuously assess the actual laundry load characteristics and automatically adjusting treatment parameters accordingly. The controller receives visual feedback about the load size, density, and composition, then optimizes energy and chemistry usage based on this real-time information, eliminating waste associated with default settings.
Solution Approach 2:
The patent dynamically changes treatment parameters including temperature, rotational speed, and chemistry dispensing based on image analysis results. The system adjusts these parameters in real-time according to the detected load characteristics, optimizing energy efficiency and treatment effectiveness for each specific laundry load.
3Measurement precision
If imaging device and image analysis are added, then measurement precision is improved for load detection, but device complexity increases
Solution Approach 1:
The imaging device serves multiple functions: it detects load presence, determines load size, assesses load density, and identifies fabric types. This single optical system provides comprehensive load characterization that would otherwise require multiple separate sensors and detection mechanisms, reducing overall system complexity while maintaining high measurement precision.
Solution Approach 2:
The patent uses image analysis as an intermediary process that translates visual information into actionable treatment parameters. Rather than directly measuring physical properties with complex sensors, the system captures images and uses computational analysis to derive load characteristics, serving as a versatile intermediary between the optical domain and control decisions.
4Productivity
If automatic parameter adjustment based on image analysis is implemented, then productivity is improved through optimized treatment, but device complexity increases due to additional components
Solution Approach 1:
The system performs preliminary action by capturing images of the laundry load at the beginning of the treatment cycle and analyzing these images to determine optimal treatment parameters before the actual treatment begins. This advance assessment allows the controller to pre-configure the most efficient treatment parameters, maximizing productivity from the start of the cycle.
Solution Approach 2:
The patent implements dynamic adjustment of treatment parameters throughout the cycle based on image analysis results. The system adapts rotational speed, temperature, and chemistry dispensing in real-time according to the detected load characteristics, making the treatment process dynamic and responsive rather than static, thereby optimizing productivity for each specific load.
Data Source
AI summary
The invention relates to a laundry treating appliance and method for controlling the operation of the laundry treating appliance by determining the surface area of the laundry based on image data of the laundry.