Multicore Optical Fiber Imaging for Core Element Identification
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Solution Overview
Problem
Existing methods for identifying core elements in multicore optical fibers are inefficient and costly, often requiring marker elements that complicate manufacturing and are difficult to detect, especially in heterogeneous fibers where core elements differ in refractive index, dimension, and configuration.
Innovation Solution
A method using lateral and end-face image processing to capture and analyze images of multicore optical fibers at various rotational orientations, determining average intensities, and compiling datasets to identify core elements based on their relative sizes and positions, eliminating the need for marker elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If marker elements are included in homogeneous multicore optical fibers to enable core element identification, then core element correspondence can be determined, but manufacturing complexity and cost increase
Solution Approach 1:
The patent extracts the identification function from separate marker elements and integrates it into the core elements themselves through heterogeneous design. By making at least one core element different (in size, position, or refractive index), the identification capability is built into the fundamental structure, eliminating the need for additional marker elements while maintaining core element correspondence determination.
Solution Approach 2:
The heterogeneous core element serves multiple functions: it acts as both a signal transmission channel and an identification marker. This multi-functional design allows the core element to perform its primary communication role while simultaneously providing the reference needed for alignment, thereby eliminating the need for separate marker elements.
2Measurement precision
If marker elements are used for core element alignment, then splicing accuracy is improved, but detection difficulty increases for field technicians
Solution Approach 1:
The patent applies local quality by creating a distinct difference in specific core elements rather than using separate marker elements. The heterogeneous core element (different size, position, or refractive index) creates a locally distinguishable feature that is inherently visible and detectable during splicing operations, eliminating the visibility issues associated with traditional marker elements.
3Ease of manufacture
If heterogeneous core elements are used instead of homogeneous core elements with markers, then manufacturing cost is reduced, but core element identification complexity increases
Solution Approach 1:
The patent employs asymmetry by designing at least one core element with different characteristics (size, position, or refractive index) compared to others. This asymmetric design provides inherent identification capability that simplifies the overall process, as the heterogeneous element naturally stands out during imaging and alignment without requiring complex identification algorithms or additional components.
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
Enables accurate and efficient identification of core elements in heterogeneous fibers, simplifying the splicing process and reducing manufacturing costs by relying on image processing algorithms to distinguish core elements without additional markers.
Implementation Method 1
capturing, by an imaging system, a first lateral image of a heterogeneous multicore optical fiber at a first rotational orientation
Implementation Method 2
determining, by a processor, a first average intensity of each of the first plurality of horizontal rows
Data Source
AI summary
Methods and algorithms are described herein for identifying core elements within a multicore optical fiber using single end-face image processing and/or lateral image processing. A method includes capturing a plurality of lateral images of the multicore optical fiber at various rotational orientations, determining an average intensity of each horizontal row from each of the lateral images, and compiling the average intensity of each of the plurality of horizontal rows into a plurality of datasets, each plurality of datasets corresponding to one of the lateral images. The plurality of datasets are compounded into a compounded image, a subset of the plurality of datasets is selected from the compounded image, and an image intensity of the subset of the plurality of datasets is analyzed. Based on the analysis, at least one structural component of each of at least two core elements present within the multicore optical fiber is identified.