Optical Fiber Cut Risk Detection via Polarization Signature Analysis
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Solution Overview
Problem
Fiber optic transmission systems face significant downtime due to cuts or damage from nearby digging work, with existing reactive mechanisms taking tens of milliseconds to reroute traffic, resulting in data loss and unavailability.
Innovation Solution
A method for early detection of optical fiber cuts by measuring variations in characteristic parameters, such as polarization, and using similarity analysis and AI algorithms to identify potential cutting risks, allowing for proactive rerouting of optical signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reactive mechanisms (MS-SPRing protection, fast reroute) are used to reroute traffic after fiber cut detection, then traffic can be restored, but data loss occurs during the tens of milliseconds detection and switching time
Solution Approach 1:
The system performs preliminary detection of fiber cut risks by monitoring characteristic parameters (polarization, temperature, vibration) before the actual cut occurs. When risk is detected, traffic is proactively rerouted to protection paths before the fiber fails, eliminating data loss that would occur during reactive switching.
Solution Approach 2:
The system continuously monitors characteristic parameters of the optical fiber and provides feedback about the fiber's health status. This feedback loop enables early warning of potential cuts, allowing the system to take preventive action rather than reacting after failure occurs.
2Object-affected harmful factors
If fiber optic cables are buried deeply to protect them from digging damage, then physical protection is improved, but detection of nearby digging work becomes more difficult
Solution Approach 1:
The system uses intermediary physical phenomena (polarization changes, temperature variations, vibration) that occur in the fiber itself as mediators to detect nearby digging work. These intermediaries provide indirect but reliable information about external threats without requiring direct observation of the digging activity.
Solution Approach 2:
The system replaces direct mechanical detection methods with optical field-based detection by monitoring polarization and other optical characteristics of the fiber. This substitution enables detection of subtle environmental changes caused by nearby digging that would be imperceptible to mechanical sensors.
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 approach significantly reduces unavailability by enabling early detection and prevention of fiber cuts, minimizing data loss and downtime through proactive rerouting of optical signals.
Implementation Method 1
measuring the variation of at least one characteristic parameter of an optical signal passing through the optical fiber
Implementation Method 2
measuring the variation of at least one characteristic parameter of an optical signal passing through the optical fiber
Data Source
Figure 1
Figure 2A~2B
Figure 2C~2D
AI summary
The method involves detecting an event causing risk of disconnection of an optical fiber including a similarity searching between a signature of a current event, obtained from measured variation of a characteristic parameter and a characteristic signature of the event resulting in the risk of disconnection obtained from a predetermined variation of the characteristic parameter during a time interval when the event causes the risk of disconnection. Independent claims are also included for the following: (1) a method for routing an optical signal in an optical transmission network (2) an optical transmission network comprising a system for detecting a risk of disconnection of an optical fiber.