Washing Machine Rinse Operation Selection Using Fluid Property Sensing
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Solution Overview
Problem
Laundry washing machines often experience suboptimal performance due to user inattentiveness or lack of understanding when manually selecting load types, leading to inefficient energy and water consumption.
Innovation Solution
A laundry washing machine equipped with a fluid property sensor, such as a turbidity sensor, and a controller that dynamically selects between fill rinse and spray rinse operations based on sensed fluid properties, along with weight and fluid level sensors to automatically determine the load type and adjust wash cycle settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual load type selection is provided, then user interaction is simplified, but suboptimal performance occurs due to user inattentiveness or lack of understanding
Solution Approach 1:
The washing machine automatically detects load type using sensors (weight sensor for load weight, fluid level sensor for water absorption rate) and selects appropriate wash cycle settings without requiring user input. The system serves itself by autonomously determining wash parameters based on sensed characteristics, eliminating the reliability issues associated with manual user selection.
Solution Approach 2:
The system continuously monitors fluid properties (turbidity, conductivity) during the wash cycle and uses this feedback to dynamically adjust rinse operation selection. The controller compares sensed fluid property values against thresholds to automatically determine when to switch between fill rinse and spray rinse operations, ensuring optimal performance based on real-time conditions.
2Ease of operation
If manual load type selection is provided, then user interaction is simplified, but energy and water consumption efficiency deteriorates
Solution Approach 1:
The system dynamically selects rinse operation types based on real-time fluid property measurements rather than using fixed manual settings. The controller continuously adapts the wash cycle by switching between fill rinse and spray rinse operations according to sensed turbidity and conductivity values, optimizing energy and water consumption throughout the cycle.
Solution Approach 2:
The system changes operational parameters (rinse operation type, water temperature, agitation speed) based on detected load characteristics and fluid properties. By automatically adjusting these parameters according to sensed data, the system achieves efficient energy and water usage without requiring user expertise in setting parameters manually.
3Reliability
If automatic rinse operation selection based on fluid properties is implemented, then wash performance is optimized, but device complexity increases
Solution Approach 1:
The fluid property sensor serves multiple functions: it measures both turbidity and conductivity to determine rinse operation selection, and can also monitor detergent concentration and soil levels throughout the wash cycle. This multi-functionality reduces the need for separate sensors for each measurement, thereby limiting the increase in device complexity.
Solution Approach 2:
The system replaces complex mechanical load type classification mechanisms with electronic sensing and digital signal processing. The controller uses software algorithms to interpret sensor data and automatically select wash parameters, substituting mechanical complexity with programmable logic that can be updated and adjusted without physical modifications.
4Use of energy by moving object
If dynamic rinse operation selection is implemented, then energy and water efficiency is improved, but control system complexity increases
Solution Approach 1:
The system performs preliminary sensing of load weight and water absorption rate during the initial fill phase to pre-determine the load type before the main wash cycle begins. This preliminary action allows the controller to prepare appropriate wash parameters in advance, reducing the complexity of real-time decision-making during the cycle while maintaining energy and water efficiency.
Solution Approach 2:
The system measures multiple fluid properties (turbidity, conductivity, temperature) but uses only the most critical measurements for rinse operation selection. By focusing on key parameters rather than processing all available data, the controller reduces computational complexity while still achieving optimal energy and water efficiency through informed decision-making.
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 performance by automatically selecting the appropriate load type and rinse operations, reducing user burden and improving energy and water efficiency by dynamically adjusting wash cycle settings based on real-time sensor data.
Implementation Method 1
a fluid property sensor such as a turbidity dispenser to dynamically select between different types of rinse operations
Implementation Method 2
the turbidity sensor is further configured to measure conductivity of the fluid from the wash tub
Data Source
AI summary
A laundry washing machine and method utilize a fluid property sensor to dynamically select between different types of rinse operations, e.g., fill rinse operations or spin rinse operations, performed during a wash cycle.