Automated Edge Detection for Laundry Feeding to Treatment Machines
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for feeding laundry to treatment machines, such as mangles and folding machines, are not fully automated, requiring manual identification of longer and shorter edges to optimize machine usage, which limits efficiency and automation.
Innovation Solution
A method for automatically determining the longer and shorter edges of laundry by analyzing the angles and lengths of edge areas extending from a freely hanging corner, using image analysis and edge detection devices to orient the edges correctly for automated feeding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification of longer and shorter edges is used to optimize machine usage, then feeding accuracy is improved, but automation extent deteriorates
Solution Approach 1:
The patent replaces manual mechanical identification with an automated image processing system. The control unit captures images of the laundry item, processes them to identify edge orientations, and determines longer/shorter edges automatically, eliminating the need for manual corner hanging while maintaining feeding accuracy.
Solution Approach 2:
The laundry treatment machine performs self-identification of edge orientations through its own imaging and processing capabilities. The system autonomously determines which edges are longer or shorter without external human intervention, enabling the machine to serve itself in the identification task.
2Measurement precision
If manual corner hanging is used to identify edges, then edge identification accuracy is improved, but productivity deteriorates
Solution Approach 1:
The manual mechanical process of hanging corners is replaced by an automated image capture and processing system. The control unit quickly captures images and processes them to identify edges, dramatically reducing the time required per laundry item while maintaining identification accuracy through digital image analysis.
Solution Approach 2:
The system performs preliminary image capture and processing before the actual feeding operation. By pre-identifying edge orientations through imaging, the system prepares the information needed for accurate feeding without requiring time-consuming manual manipulation during the feeding process itself.
3Productivity
If automated edge determination is implemented, then productivity is improved, but measurement precision may deteriorate
Solution Approach 1:
The patent employs sophisticated image processing algorithms that analyze captured images to accurately determine edge orientations and identify longer/shorter edges. The control unit processes image data to calculate edge angles and lengths, achieving high measurement precision through digital analysis rather than mechanical methods.
Solution Approach 2:
The system creates a digital copy of the laundry item through imaging, then analyzes this copy to determine edge characteristics. This allows multiple measurements and analyses of the same item without physical manipulation, enabling both high speed and high precision in edge determination.
Data Source
AI summary
A method that facilitates the automatic identification of the long edge or the short edge of the item of laundry by determining the lengths or the angles of the edge areas of the item of laundry extending from a lower corner of the item of laundry. It may be derived from the determined angles or lengths of the edge areas whether the respective edge area belongs to the long edge or to the short edge of the item of laundry. With this information, a targeted transverse or longitudinal feed of rectangular items of laundry may be carried out to a downstream inserting machine. The fully automated feeding of items of laundry to, for example, an inserting machine is carried out in a targeted way with either the long edge of the item of laundry extending transversely to the feed direction or the short edge extending transversely to the feed direction.