DAS Signal Loss Detection via Dual Photodetector Power Statistics
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Solution Overview
Problem
Existing DAS systems face challenges in detecting and locating undesired levels of signal loss in optical fiber cables, which requires shutting down the system and using expensive OTDR meters.
Innovation Solution
A method utilizing dual photodetectors to receive raw DAS signals, process them to obtain statistical data, and apply a change detection algorithm to identify and locate signal loss based on power statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If OTDR meters are used to detect signal loss in fiber optic cables, then measurement precision is improved, but the system must be shut down and expensive equipment is required
Solution Approach 1:
The DAS system uses its own operational data to detect signal loss without requiring external specialized equipment or system shutdown. The photodetectors continuously monitor power statistics during normal operation, enabling the system to self-diagnose fiber cable issues while remaining functional.
Solution Approach 2:
The photodetectors serve dual purposes: their primary function for DAS operation and a secondary function for signal loss detection. This eliminates the need for separate OTDR equipment, allowing the same hardware to perform multiple measurement tasks.
2Measurement precision
If OTDR meters are used to detect signal loss, then measurement precision is improved, but device cost increases
Solution Approach 1:
The photodetectors serve dual purposes: their primary function for DAS operation and a secondary function for signal loss detection. This eliminates the need for separate OTDR equipment, allowing the same hardware to perform multiple measurement tasks.
Solution Approach 2:
The DAS system uses its own operational data to detect signal loss without requiring external specialized equipment or system shutdown. The photodetectors continuously monitor power statistics during normal operation, enabling the system to self-diagnose fiber cable issues while remaining functional.
3Productivity
If dual photodetectors are used to enable real-time detection, then productivity is improved, but device complexity increases
Solution Approach 1:
The system continuously monitors power statistics from the photodetectors during normal DAS operation without interruption. This continuous data collection enables real-time signal loss detection while maintaining uninterrupted fiber optic cable functionality for its primary purpose.
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 real-time detection and localization of signal loss in DAS systems without shutting them down, improving efficiency and reducing costs compared to traditional methods.
Implementation Method 1
Fiber cable signal has losses from absorption and back reflection of the light caused by impurities in the glass
Implementation Method 2
Fiber cable signal has losses from absorption and back reflection of the light caused by impurities in the glass
Implementation Method 3
Rayleigh-Scattering based DAS systems use fiber optic cables to provide distributed strain sensing over large distances
Implementation Method 4
raw DAS signals are received from an optical fiber of a DAS system with dual photodetector positioned at the end(s) of the optical fiber
Data Source
AI summary
A method that detects locations of undesired levels of signal loss in DAS systems that use optical fibers. In the method, raw DAS signals are received from an optical fiber of a DAS system with dual photodetector positioned at the end(s) of the optical fiber. Locations on the optical fiber are named “channels” having a certain length on the optical fiber and are numbered according to distances of the channels from the photodetector. The raw DAS signals received from each channel are processed by the dual photodetector to obtain raw DAS statistical data for each channel. The obtained raw DAS statistical data are then reconstructed to produce reconstructed DAS statistical data in which noise has been removed. The reconstructed DAS statistical data form power statistics for each channel. The power statistics is expected to be linearly decreasing with a farther distance of each channel from the photodetector. A change detection algorithm is provided to detect possible undesired levels of signal loss and to find the locations of the signal loss based on the power statistics.

