Liquid dispenser sensing distance self-learning method, an electronic device, and a storage medium
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Solution Overview
Problem
Current liquid dispensers lack self-learning capabilities, making it difficult for installers and maintenance personnel to accurately set the sensing distance, leading to increased installation complexity, risk of abnormal liquid discharge, and higher maintenance costs due to the absence of intuitive feedback and ranging detection.
Innovation Solution
A liquid dispenser sensing distance self-learning method that enters a self-learning mode to determine and store the nearest distance between a reference object and a sensing component, using light indication devices to display the learning state and comparison results, allowing users to assess the correct setting of the sensing distance during installation and operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the sensing distance is manually adjusted without self-learning function, then the liquid dispenser can be installed, but the installation complexity increases and the risk of abnormal liquid discharge increases due to lack of accurate sensing distance setting
Solution Approach 1:
The liquid dispenser automatically performs self-learning to determine the sensing distance without requiring manual adjustment by installers. The control unit autonomously controls the sensing component to detect reference objects and calculate the nearest distance, storing it as the sensing distance. This self-service mechanism eliminates manual adjustment complexity while ensuring accurate sensing distance setting for reliable operation.
Solution Approach 2:
The liquid dispenser performs self-learning of the sensing distance during the installation phase before actual use. By pre-determining the optimal sensing distance through automatic detection of the nearest reference object, the system prepares the correct sensing parameters in advance, avoiding the need for complex manual adjustment during installation and ensuring reliable sensing from the start.
2Adaptability or versatility
If the sensing distance is set inside the program without learning function, then the device structure is simple, but the adaptability to complex installation environments deteriorates
Solution Approach 1:
The liquid dispenser automatically adapts to different installation environments by performing self-learning to determine the optimal sensing distance specific to each installation location. The control unit autonomously controls the sensing component to detect reference objects and calculate the nearest distance, storing it as the sensing distance. This self-service mechanism enables the device to adapt to complex and diverse installation environments without requiring complex pre-programming for each scenario.
Solution Approach 2:
The sensing distance is not fixed in the program but is dynamically determined through self-learning based on the actual installation environment. The system can adapt its sensing parameters to match the specific conditions of each installation location, making the liquid dispenser versatile and adaptable to various countertop configurations and reference object positions.
3Loss of information
If a board is used to set the sensing distance without reporting mechanism, then the learning process is simple, but the installation verification capability deteriorates due to lack of feedback
Solution Approach 1:
The control unit provides visual feedback through indication lights to show the self-learning state and sensing distance determination results. Different lighting patterns indicate different states (learning in progress, learning completed, sensing distance determined). This feedback mechanism allows installers to verify successful installation and sensing distance setting without complex reporting mechanisms, simply by observing the indication lights.
4Reliability
If the sensed nearest distance is taken as sensing distance without retraction distance adjustment, then the device operation is simple, but the reliability deteriorates due to critical sensing phenomenon causing abnormal liquid discharge
Solution Approach 1:
The system preemptively prevents critical sensing by calculating the sensing distance as the retraction distance plus a predetermined distance, rather than simply using the nearest detected distance. This preliminary anti-action ensures that the sensing threshold is set conservatively to avoid false triggering from objects at the critical boundary, preventing abnormal liquid discharge before it can occur.
Solution Approach 2:
The sensing distance parameter is calculated by adding a predetermined distance to the retraction distance, transforming the raw nearest distance measurement into a more reliable sensing threshold. This parameter transformation ensures that the sensing distance accounts for the retraction distance and provides a safety margin, preventing critical sensing issues while maintaining relatively simple operation.
Data Source
AI summary
A liquid dispenser sensing distance self-learning method includes in response to a self-learning request, entering a self-learning mode. The method also includes, in the self-learning mode, determining a shortest distance between a reference object and a sensing component; determining and storing a sensing distance based on the shortest distance; and identifying, by a first indication device, a state of the self-learning mode. The method also includes, in response to a sensing request, entering a sensing mode; obtaining a detected distance between the reference object and the sensing component; comparing the detected distance with the sensing distance; and identifying, by a second indication device, a comparison result of the detected distance and the sensing distance.