OTDR Curve Tail Event Detection Algorithm
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Solution Overview
Problem
Current OTDR methods for detecting end events in optical fibers are inefficient in distinguishing between various end events, prone to noise interference, and require significant time and memory, affecting the reliability of online optical fiber monitoring systems.
Innovation Solution
A method that involves issuing test light to an optical fiber, forming a data curve of reflection sampling points, identifying a head reflection point, and performing forward and reverse piecewise linear fitting to determine the type of end event based on predetermined threshold values, effectively distinguishing between reflection and non-reflection end events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If template matching method is used to detect end events, then detection accuracy is improved, but time consumption and memory requirement increase significantly
Solution Approach 1:
The patent extracts only the essential features from the OTDR curve (reflection peaks and their characteristics) rather than using complete template matching. By identifying and analyzing only the reflection peak parameters (position, amplitude, width) rather than matching entire curve templates, the system achieves accurate end event detection with significantly reduced computational time and memory requirements.
Solution Approach 2:
The patent transforms the detection approach by changing from template-based pattern recognition to parameter-based feature extraction. Instead of comparing entire curve templates, the system analyzes specific parameters of reflection peaks (amplitude, position, width) to identify end events, thereby reducing computational complexity while maintaining detection accuracy.
2Measurement precision
If dynamic range and number of averaging steps are increased to improve SNR in single wave system, then measurement precision is improved, but time consumption increases
Solution Approach 1:
The patent applies partial action by performing averaging only for the specific portion of the OTDR curve where reflection peaks are expected to occur, rather than averaging the entire curve. This selective averaging approach improves the SNR of reflection peaks while minimizing the overall analysis time, as only the relevant sections require multiple averaging steps.
3Difficulty of detecting and measuring
If difference method is used to transform OTDR curve, then end event detection is enabled, but noise amplitude increases significantly
Solution Approach 1:
The patent applies local quality by analyzing only the specific local regions where reflection peaks occur rather than transforming the entire OTDR curve. By focusing the difference method calculation only on segments around expected reflection points and using threshold-based filtering, the system enhances end event detectability while minimizing noise amplification in other regions.
4Measurement precision
If first order differential method is used to locate breakpoints, then breakpoint detection is achieved, but reflection points are also mutated and filtered incorrectly
Solution Approach 1:
The patent applies asymmetry by using different detection criteria for reflection peaks versus breakpoints. Reflection peaks are identified by their characteristic symmetric shape and amplitude thresholds, while breakpoints are detected through asymmetric changes in the curve slope and curvature. This asymmetric approach allows the system to distinguish between the two event types and apply appropriate filtering to each, reducing false judgments.
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 method improves the accuracy of end event detection, reduces noise interference, and enables precise location of optical fiber breakpoints in online mode, enhancing the reliability of optical fiber monitoring systems.
Implementation Method 1
In OTDR, there are mainly Rayleigh scattering and Finel reflection, some of which will return to OTDR
Implementation Method 2
In OTDR, there are mainly Rayleigh scattering and Finel reflection, some of which will return to OTDR
Implementation Method 3
The following formula shows how OTDR measures distance: d=(c×t)/2(IOR), where d is distance (fiber length) to be measured, c is velocity of light in vacuum, IOR is index of refraction of the optical fiber, and t is total time from sending signal to receiving the same (round-trip)
Data Source
AI summary
Disclosed is a method for detecting an OTDR curve tail end event to locate an optical fiber break point in an online mode, comprising following steps: 1, an OTDR emits detection light to an optical fiber operation link, and receives reflection light to form reflection sampling point data containing tail end event; 2, head end reflection point in sampling point is found out; 3, traversal is carried out to find search region end point; 4, segmented line fitting is carried out in region of [search region end point, head end reflection point] in reversed direction, start point of section of line meeting predetermined condition is used as a search region start point; 5, if absolute value of difference between largest sampling value in search region and sampling value of search region start point is larger than second preset threshold value, tail end event is judged as reflection tail end event.