Optical Fiber Inspection Using Pattern Distortion Analysis
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Solution Overview
Problem
Optical fibers can be contaminated and/or damaged during manufacturing, leading to reduced signal quality and issues during termination and mating, with existing methods failing to effectively detect distortions and contaminants.
Innovation Solution
A visual inspection system is employed, utilizing a pattern source and imaging sensor to analyze patterns visible through the optical fiber, with axial and radial illumination sources to detect distortions and contaminants, and an optical monoblock reflector to efficiently redirect light for comprehensive inspection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional inspection methods are used, then the inspection process is simple, but the detection precision of distortions and contaminants is insufficient
Solution Approach 1:
A pattern source is introduced as an intermediary element placed behind the optical fiber. The pattern acts as a reference that, when viewed through the fiber, reveals distortions caused by contaminants or damage. This intermediary pattern enables precise detection without requiring complex direct measurement equipment.
Solution Approach 2:
The patent replaces traditional mechanical or direct optical inspection methods with a visual pattern-based detection system. By using a pattern source and imaging sensor to capture and analyze visual patterns through the fiber, the system substitutes complex mechanical scanning or direct microscopic examination with a simpler optical visualization approach.
2Reliability
If multiple inspection angles are used, then the detection completeness improves, but the inspection time increases
Solution Approach 1:
The patent employs illumination sources positioned at multiple angles (axial and radial directions) to illuminate the optical fiber from different dimensions simultaneously. This multi-dimensional illumination approach allows comprehensive detection of contaminants and damage without requiring sequential inspection from multiple angles, thus reducing inspection time while maintaining detection completeness.
3Measurement precision
If axial and radial illumination are used, then the contamination detection capability improves, but the energy consumption increases
Solution Approach 1:
The system uses axial and radial illumination sources that provide targeted lighting only where needed for inspection. Rather than illuminating the entire fiber uniformly, the illumination is concentrated in specific directions (axial and radial) relevant to detecting contaminants, thereby reducing overall energy consumption while maintaining high detection capability.
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
The system effectively detects damage and contamination on optical fibers, improving signal quality by ensuring accurate inspection and maintenance, thereby enhancing the reliability of optical connections.
Implementation Method 1
positioning an optical fiber so that a pattern source produces a pattern visible through the optical fiber when viewed through an annular side of the optical fiber
Implementation Method 2
positioning a sensor relative to the optical monoblock reflector so that the optical monoblock reflector directs light from the fiber towards the sensor
Data Source
AI summary
A visual inspection system (100, 200) for optical fibers (150) includes at least a pattern source (120, 220A, 220B, 220C, 520); at least a first illumination source (130, 230A, 230B, 230C, 510, 522) to direct light towards an optical fiber (150); and at least a first camera (140, 240A, 240B, 240C, 540) positioned at an opposite side of the fiber (150) from the pattern source (120, 220A, 220B, 220C, 520). At least one image (170, 180, 190) of the optical fiber (150) is taken and a pattern visible through the optical fiber (150) in the image (170, 180, 190) may be analyzed to detect distortions in the pattern.