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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Bibliographic Details
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
Subjects:
Adaptive filters
Algorithms
Fault detection
Methodology
Parameter identification
Regularization
Variations
Online Access:Get full text
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Summary: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.
ISSN:2331-8422
DOI:10.48550/arxiv.1602.04379