Fibrogram Curve Reconstruction for Accurate Cotton Fiber Length Distribution
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Solution Overview
Problem
Current methods for assessing fiber length distribution, such as HVI and AFIS, fail to capture complete fiber length variation and are prone to errors like fiber breakage and data imperfections, limiting their effectiveness in predicting yarn quality.
Innovation Solution
A computer-implemented method involving windowed curve-fitting and convex function-based reconstruction of fibrograms to smooth and estimate fiber length distribution, addressing issues like concavity and missing data, and adjusting fiber-related conditions based on the estimated distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods like HVI and AFIS are used to assess fiber length distribution, then measurement can be performed, but the complete fiber length variation cannot be captured and errors like fiber breakage occur
Solution Approach 1:
The patent replaces mechanical fiber assessment methods (HVI, AFIS) with a computational image analysis system. The fibrogram generation and curve-fitting process substitutes physical measurement mechanisms with digital image processing, eliminating mechanical fiber breakage while capturing complete length distribution through non-contact optical methods
Solution Approach 2:
The patent creates a digital representation (fibrogram) of the fiber bundle's length distribution from an image. This copy allows repeated analysis without physical manipulation of the actual fibers, preserving the original sample integrity while enabling precise measurement of complete length variation
2Device complexity
If fibrogram data is used directly without processing, then data processing is simple, but data imperfections and concavity issues remain
Solution Approach 1:
The patent applies preliminary data processing steps including windowed curve-fitting and convex function reconstruction before final analysis. These preprocessing actions correct concavity and smooth the fibrogram curve in advance, ensuring measurement precision is achieved without adding excessive complexity during the main analysis phase
Solution Approach 2:
The patent introduces curve-fitting functions as intermediary mathematical models between the raw fibrogram data and the final length distribution results. These intermediary functions bridge the gap by transforming imperfect raw data into accurate measurements through systematic mathematical transformation
Data Source
AI summary
Embodiments of the present disclosure pertain to computer-implemented methods of reconstructing a fiber length distribution of a fiber from its fibrogram by receiving the fibrogram; determining an end of the fibrogram; applying a windowed curve-fitting procedure to smoothen the fibrogram curvel and estimating the fiber length distribution of the fiber from the smoothened fibrogram curve. The methods may also include one or more steps of reconstructing an initial and missing portion of the fibrogram; assessing fiber quality based on the estimated fiber length distribution; adjusting one or more fiber-related conditions based on the estimated fiber length distribution; and repeating the method after the adjustment. Additional embodiments pertain to computing devices for reconstructing a fiber length distribution of a fiber from its fibrogram.