Fiber Layer Identification in Deformed Composites Using Moiré Mapping
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Solution Overview
Problem
Existing methods struggle to automatically identify the fiber layer in fiber-reinforced materials, particularly in bent portions, leading to time-consuming and costly manual inspections, and require extensive training for workers.
Innovation Solution
An identification device and method that generates data mapping physical quantities to an initial shape, performs binarization using a learning model, and maps labels to both initial and predetermined shapes, automating the identification process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification of fiber layers is performed, then identification accuracy can be maintained, but time consumption and cost increase enormously
Solution Approach 1:
The patent replaces the manual mechanical identification process with an automated image processing system using moire images and computational algorithms. The system automatically identifies fiber layers by processing moire patterns generated by X-ray Talbot imaging, eliminating the need for manual worker intervention while maintaining identification accuracy.
Solution Approach 2:
The patent introduces moire images as an intermediary medium between the fiber-reinforced material and the identification system. The moire images encode layer information that can be automatically decoded by the processing system, serving as a bridge that enables automated identification without direct manual inspection.
2Reliability
If manual identification of fiber layers is performed, then identification can be completed, but cost increases enormously
Solution Approach 1:
The patent replaces costly manual labor with an automated imaging and processing system. The X-ray Talbot imaging device combined with automated moire image processing eliminates the need for trained workers, significantly reducing labor costs while ensuring complete and reliable identification of all fiber layers.
Solution Approach 2:
The patent creates a visual copy of the fiber layer structure through moire images. These images serve as replicas that contain all necessary information for identification, allowing the system to analyze the layer structure without physically manipulating or destroying the original material, thereby ensuring complete identification at low cost.
3Measurement precision
If workers are trained to identify fiber layers, then identification proficiency can be achieved, but training time and cost increase
Solution Approach 1:
The patent replaces the need for trained human workers with an automated system that inherently possesses identification capabilities through its imaging and processing algorithms. The system requires no training time or cost because the identification logic is embedded in the software and hardware, eliminating the human element entirely.
Solution Approach 2:
The system performs self-identification of fiber layers without requiring external human expertise. The automated processing algorithms independently analyze the moire images and extract layer information, making the system self-sufficient and eliminating the need for trained operators or extensive training programs.
4Productivity
If automated identification is implemented, then time and cost are reduced, but complexity of the system increases
Solution Approach 1:
The patent employs an X-ray Talbot imaging device that serves multiple functions: it generates the moire images, provides the imaging mechanism, and enables the automated processing workflow. This multi-functional approach consolidates what could be multiple separate systems into one integrated device, reducing overall system complexity while maintaining high productivity.
Solution Approach 2:
The system performs preliminary encoding of layer information into moire images during the imaging process itself. This preliminary action prepares the data in a format that is ready for automated analysis, eliminating the need for complex post-processing steps or additional preparation equipment, thereby balancing automation with manageable system complexity.
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
Automates the identification of fiber layers, reducing time and cost, and improves accuracy in identifying fiber layers even in complex bent structures.
Implementation Method 1
acquiring a moire image by using an X-ray Talbot imaging device
Implementation Method 2
acquiring a moire image by using an X-ray Talbot imaging device
Data Source
AI summary
Regarding to a fiber-reinforced material formed by deforming a reinforcing material composed of a plurality of fiber layers from an initial shape and molding into a predetermined shape, an identification device, an identification method, and an identification program generate a first data in which a physical quantity distribution inside the fiber-reinforced material is mapped to the initial shape, perform binarization of the first data to generate a second data in which a label identifying the fiber layer is mapped to the initial shape, and map the second data to a predetermined shape, based on a deformation data.