Yarn Spindle Detection Segmentation for Packaging Efficiency
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Solution Overview
Problem
In automatic packaging of yarn spindles, efficient detection of each spindle is necessary to improve production efficiency, but current methods are inefficient and prone to mixing abnormal spindles in packaging.
Innovation Solution
A control method that detects the appearance feature of yarn spindles entering a detection area and selectively detects the physical attribute feature of spindles that do not meet preset requirements, using sensors and RFID technology to optimize detection efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detection of each yarn spindle is performed to ensure quality, then detection accuracy is improved, but production efficiency deteriorates
Solution Approach 1:
The detection process is segmented into two stages: first detecting appearance features of all yarn spindles, then selectively detecting physical attribute features only for spindles that fail the appearance check. This segmentation avoids unnecessary full detection of all spindles, thereby maintaining detection accuracy while improving production efficiency.
Solution Approach 2:
Instead of performing complete detection on all yarn spindles, the system performs partial detection by first checking appearance features and only conducting full physical attribute detection on spindles that fail the initial appearance check. This partial action approach reduces overall detection time while ensuring quality through targeted full detection of problematic spindles.
2Reliability
If physical attribute feature detection is performed on all yarn spindles, then quality control is improved, but detection time increases
Solution Approach 1:
The system performs preliminary detection of appearance features for all yarn spindles before conducting physical attribute feature detection. This preliminary action identifies spindles that require further inspection, allowing the system to perform time-consuming physical attribute detection only on necessary spindles, thus reducing total detection time while maintaining quality control.
Solution Approach 2:
The system performs partial detection by conducting appearance feature detection on all spindles and only performing full physical attribute detection on spindles that fail the appearance check. This approach reduces detection time by avoiding redundant full detection of normal spindles while ensuring quality control through targeted detection of abnormal spindles.
3Productivity
If selective detection based on appearance features is implemented, then detection efficiency is improved, but detection complexity increases
Solution Approach 1:
The detection system is segmented into multiple detection modules: appearance feature detection and physical attribute feature detection. This segmentation allows the system to perform selective detection based on appearance results, improving efficiency while managing complexity through modular design where each module handles a specific detection task independently.
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 method significantly improves the detection efficiency of physical attribute features of yarn spindles, preventing the mixing of abnormal spindles and enhancing the overall quality of packaged spindles.
Implementation Method 1
obtaining the physical attribute feature of the target yarn spindle using a sensor provided in a sensing area
Implementation Method 2
detecting whether first response information for a radio frequency identification corresponding to the target yarn spindle is obtained
Data Source
AI summary
Provided is a control method, an electronic device and a storage medium. The method comprises: when determining that a yarn spindle transported on a transport channel enters a detection area, detecting the yarn spindle located in the detection area to obtain an appearance feature of the detected yarn spindle; wherein the transport channel is a channel for transporting yarn spindles in an automatic packaging workshop; and the detection area is at least a partial area on the transport channel; when the appearance feature of the detected yarn spindle does not meet a first preset requirement, determining the yarn spindle with the appearance feature not meeting the first preset requirement as a target yarn spindle; and detecting a physical attribute feature of the target yarn spindle.