Article Details

Title · Authors · Abstract · Keywords · DOI · References

Remaining Life Prediction of OPGW Cable under Multi-Factor Meteorological Conditions Based on Autoformer

XIONG Yi

(Guangdong Provincial Railway Planning and Design Institute Co., Ltd., Guangzhou 510699, China)

Section：Communication Engineering · Vol. 2026, Issue 8 · Pages：1-6 · 2096-4706（2026）08-0001-06 · CLC number：TP183；TN818 · Document code：A · DOI：10.19850/j.cnki.2096-4706.2026.08.001

Abstract

To improve the accuracy of OPGW cable remaining life prediction, multi-factor meteorological data from Guangzhou between 2011 and 2023 are utilized to investigate cable degradation under temperature fluctuations and wind loads. A time series of cable length variation is constructed based on thermal expansion and contraction and mechanical load models, and an Autoformer-based remaining life prediction method is developed. Lagrange interpolation is applied to repair anomalous values, and Min-Max normalization is used for feature scaling. Comparison with LSTM, Bi-LSTM and Bi-LSTM+Attention models shows that Autoformer achieves optimal performance across RMSE, MAE, and MSE metrics, demonstrating a superior capability in capturing long-term variation trends of cable remaining length. The findings indicate that the proposed method enhances prediction accuracy and provides data-driven support for OPGW operation, maintenance, and replacement decision-making.

Keywords

OPGW; remaining life prediction; Autoformer; time series forecasting

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About the authors

Xiong Yi (1997-), male, Han ethnicity, from Wuhan, Hubei, assistant engineer, master's degree, research direction: communication engineering.