Unleashing potentials with deep learning:decoding the complex events for distributed fiber optic sensing applications  

作　　者：Yujiao LI Liqin HU Kuanglu YU 

机构地区：[1]Institute of Information Science,School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China [2]Beijing Key Laboratory of Advanced Information Science and Network Technology,Beijing Jiaotong University,Beijing 100044,China

出　　处：《Science China(Information Sciences)》2024年第5期333-334,共2页中国科学（信息科学）（英文版）

基　　金：supported in part by National Key Research and Development Program of China(Grant No.2021YFB2900704);Fundamental Research Funds for Central Universities(Grant No.021314380211).

摘　　要：After decades of research,distributed fiber optic sensors have become essential tools for precise long-distance measurements.They are applied across various sectors such as railway transportation,gas and petroleum,and smart grids.Signal processing,particularly in phase-sensitive optical time domain reflectometry(Φ-OTDR)event recognition and classification,is a primary research focus.Traditionally,the full potential of unlabeled data has not been harnessed,necessitating a large number of labels and considerable human effort to obtain a high-performance model.

关 键 词：FIBER OTDR PRECISE 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP212[自动化与计算机技术—控制科学与工程]