Yarn Color Parameter Monitoring for Defect Detection
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Solution Overview
Problem
Existing yarn manufacturing processes struggle to effectively control and assess defects, leading to time and material losses during the rewinding process.
Innovation Solution
A method and apparatus that utilize multiple sensor heads to measure color parameters of yarns, forming time-series data and clustering values to identify defects and assess process control, allowing for real-time monitoring and decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If yarn clearing is performed to remove color-defective sections, then yarn quality is improved, but time and material are lost
Solution Approach 1:
The patent applies preliminary action by measuring color parameters continuously during the yarn manufacturing process and forming time-series data before the rewinding stage. This allows defects to be identified early, enabling proactive process adjustments that prevent defective yarn from reaching the clearing stage, thus avoiding time loss while maintaining quality.
Solution Approach 2:
The patent implements feedback by using measured color parameter values to control or assess the yarn manufacturing process in real-time. The system feeds back process information and defect patterns to operators or control systems, enabling continuous improvement and adjustment of manufacturing parameters to prevent defects, thereby reducing both time loss and material waste.
2Reliability
If yarn clearing is performed to remove color-defective sections, then yarn quality is improved, but material is lost
Solution Approach 1:
The patent applies preliminary action by continuously monitoring color parameters during manufacturing and using clustering algorithms to identify defect patterns before rewinding. This early detection enables process corrections that prevent defective sections from being produced, eliminating the need to remove material during clearing and thus reducing material loss.
Solution Approach 2:
The patent implements feedback by using measured color data to assess and control the manufacturing process in real-time. This feedback loop allows operators to adjust process parameters to prevent defect formation, thereby maintaining yarn quality without the need to remove defective sections, thus preventing material loss.
3Manufacturing precision
If color parameters are measured and analyzed in real-time, then process control is improved, but measurement and data processing complexity increases
Solution Approach 1:
The patent applies the extraction principle by isolating and measuring only the relevant color parameters (such as L*, a*, b* values) that directly affect yarn quality. By extracting and focusing on these specific parameters rather than analyzing all possible characteristics, the system achieves improved process control while keeping the measurement and data processing complexity manageable.
Solution Approach 2:
The patent applies parameter changes by transforming raw color measurement data into meaningful metrics through clustering algorithms and time-series analysis. This transformation converts complex raw data into simplified defect patterns and quality indicators that are easier to interpret and act upon, thereby improving process control without proportionally increasing processing complexity.
4Measurement precision
If multiple sensor heads are used to measure color parameters, then measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The patent applies the merging principle by combining multiple sensor heads into an integrated measurement system that simultaneously captures color parameters. The sensors work together to provide comprehensive color data, and their results are processed collectively through clustering algorithms, achieving improved measurement accuracy while managing system complexity through unified data handling.
Solution Approach 2:
The patent applies multi-functionality by designing sensor heads that can measure multiple color parameters (L*, a*, b* and other characteristics) simultaneously. This universal measurement capability allows a single sensor system to perform multiple measurement functions, improving overall measurement precision without proportionally increasing device complexity compared to using separate specialized sensors for each parameter.
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 approach enables better control and assessment of the yarn manufacturing process, allowing for timely identification and removal of defects, reducing material loss and improving overall process efficiency.
Implementation Method 1
Measuring, at a first plurality of times, by means of the first sensor head, at least one color parameter of the textile body
Data Source
Figure 1
Figure 2~4(C)
AI summary
A yarn is manufactured in a yarn manufacturing apparatus having a plurality of sensor heads (20, 18, 24, 30; 44). In order to control and/or assess the manufacturing process, an elongate textile body (52) is run past a first sensor head (20, 18, 24, 30; 44). At a first plurality of times, a color parameter (Pk) of the textile body (52) is measured by means of the first sensor head, and the values are stored. At least one variation parameter is determined from the color parameter (Pk) and used for assessing or controlling the process. In particular, the values of the color parameter (Pk) may be processed by clustering, and/or they may be correlated with operating parameters (Om) of the apparatus. The technique may e.g. be used for detecting cross-contamination or the correlation of machine parameters with color values and number of faulty segments.