Trends in Optical Span Loss Detected Using the Time Series Decomposition Method

• Published in: Journal of lightwave technology 2020-09, Vol.38 (18), p.5026-5035
• Main Authors: Yameogo, Banti Laure M., Charlton, Douglas W., Doucet, David, Desrosiers, Christian, O'Sullivan, Maurice, Tremblay, Christine
• Format: Article
• Language: English
• Subjects: Cables; Component reliability; Decomposition; Degradation; Linear regression; long term trend detection; Mann-Kendall; optical erbium-doped fiber amplifiers; Optical fiber amplifiers; Optical fiber cables; optical fiber communication; optical fiber losses; Optical fiber networks; Optical fibers; Regression models; sen's slope; STL; Time series analysis; time series decomposition method; Trends
• ISSN: 0733-8724; 1558-2213
• DOI: 10.1109/JLT.2020.3000967

Optical fiber cables deployed in the last 30 years have been considered to be long-lived components due to the generally high level of reliability of glass and the robustness of cable construction. Like all other components however, optical cables can change with age as a result of their construction or deployment characteristics as well as operational and environmental stress factors. In this article, we apply a time-series decomposition method on span loss data collected during 12 months in four bidirectional spans of a production network in order to detect long-term degradation of the fiber plant. After extracting the trend component, a Mann-Kendall test is applied to the span loss curves and a Sen's slope estimator test is used for determining the magnitude of span loss change. The method allows detecting a 1.3% increase in span loss over the 12-month period of observation in one of the fiber spans. This trend is confirmed using a linear regression model computed according to Theil Sen method applied to additional one-year data. The proposed method can allow the early detection of fiber plant degradation and the proactive planning of fiber replacement.