Adaptive Filter for Automatic Identification of Multiple Faults in a Noisy OTDR Profile

We present a novel methodology able to distinguish meaningful level shifts from typical signal fluctuations. A two-stage regularization filtering can accurately identify the location of the significant level-shifts with an efficient parameter-free algorithm. The developed methodology demands low com...

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Published in:arXiv.org 2016-02
Main Authors: Jean Pierre von der Weid, Souto, Mario H, Garcia, Joaquim D, Amaral, Gustavo C
Format: Article
Language:English
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Adaptive filters
Algorithms
Fault detection
Methodology
Parameter identification
Regularization
Variations
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Souto, Mario H
Garcia, Joaquim D
Amaral, Gustavo C
description We present a novel methodology able to distinguish meaningful level shifts from typical signal fluctuations. A two-stage regularization filtering can accurately identify the location of the significant level-shifts with an efficient parameter-free algorithm. The developed methodology demands low computational effort and can easily be embedded in a dedicated processing unit. Our case studies compare the new methodology with current available ones and show that it is the most adequate technique for fast detection of multiple unknown level-shifts in a noisy OTDR profile.
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subjects Adaptive filters
Algorithms
Fault detection
Methodology
Parameter identification
Regularization
Variations
title Adaptive Filter for Automatic Identification of Multiple Faults in a Noisy OTDR Profile
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