Yarn Characterization via Event Field Segmentation
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Solution Overview
Problem
Existing yarn quality control methods produce confusing graphic representations and excessive data transmission, overwhelming operators and straining data processing capacity with excessive information, making it difficult to set an optimal clearing limit efficiently.
Innovation Solution
A method and device that process and summarize yarn data into a simplified event field with distinct regions, allowing operators to intuitively understand yarn characteristics and set a clear, optimal clearing limit, reducing unnecessary data transmission and processing by categorizing events into 'yarn body', 'defect region', and 'insignificant region', using a two-dimensional Cartesian coordinate system with threshold event densities to define allowable and unallowable events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all measured yarn events are represented in the classification field, then complete yarn quality information is obtained, but the graphic representation becomes confusing and data processing capacity is exceeded
Solution Approach 1:
The patent segments the classification field into distinct regions: a first region for representing yarn defects and a second region for representing the yarn body. This segmentation allows the system to process and display only relevant defect information in the first region while aggregating yarn body characteristics in the second region, thereby reducing graphic confusion and data processing complexity while preserving essential quality information.
Solution Approach 2:
The patent extracts and separates defect events from normal yarn body events by representing them in different regions of the classification field. Defect events are taken out and highlighted in the first region, while the majority of normal yarn body events are aggregated in the second region. This extraction approach eliminates unnecessary visual clutter and reduces the data processing burden on the central computation unit.
2Manufacturing precision
If a clearing limit is set to remove all detected defects, then yarn quality is improved, but productivity decreases due to excessive removal of allowable events
Solution Approach 1:
The patent applies local quality by setting different representation criteria for different regions of the classification field. The first region uses strict criteria to highlight only significant defects that require removal, while the second region uses aggregated representation for normal yarn body variations. This allows the clearing limit to be optimized for quality without unnecessarily removing allowable events, thereby maintaining productivity.
Solution Approach 2:
The patent implements feedback by continuously monitoring the distribution of events in the classification field and using this information to optimize the clearing limit. The system analyzes the density and distribution of events in both regions, providing feedback that enables dynamic adjustment of the clearing limit to achieve the optimal balance between yarn quality and productivity.
3Extent of automation
If the clearing limit is set automatically based on defect density, then optimal quality control is achieved, but large quantities of data must be transmitted to the central computation unit
Solution Approach 1:
The patent merges multiple normal yarn body events into an aggregated representation in the second region of the classification field. Instead of transmitting individual coordinates for each normal event, the system transmits aggregated data representing the yarn body characteristics. This merging approach enables automatic clearing limit setting while significantly reducing the volume of data that must be transmitted to the central computation unit.
Solution Approach 2:
The patent inverts the traditional approach by representing the majority of normal yarn body events in an aggregated manner rather than as individual points. This inversion allows the system to maintain automatic clearing limit setting capabilities while minimizing data transmission requirements, as only essential defect information and aggregated yarn body characteristics need to be transmitted.
Data Source
AI summary
Readings of a characteristic of the yarn along the longitudinal direction of the yarn are detected. Values of a yarn parameter are determined from the readings. An event field contains a quadrant of a two-dimensional Cartesian coordinate system, whose abscissa defines an extension of yarn parameter values in the longitudinal direction and whose ordinate defines a deviation of the yarn parameter from a desired value. Densities of events in the event field are determined from the values of the yarn parameter and their extensions in the longitudinal direction. A yarn body is represented as an area in the event field. The area on the one hand is delimited by the abscissa, on the other hand by the ordinate and further by a line in the event field that substantially follows a constant event density. The representation of the yarn body permits a clearing limit to be defined in a rapid and rational manner.