Power Cable Network Topology Reconstruction Using Multi-carrier Reflectometry for Fault Detection and Location in Live Smart Grids

Wafa Ben Hassen (1) , Moussa Kafal (1) , Esteban Cabanillas (1, 2) , Jaume Benoit (1)

1 LFIC - Laboratoire Fiabilité et Intégration de Capteurs
2 CEA-LETI - Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information

Several approaches have been proposed and applied for reconstructing the topology of an unknown network. Although, promising results have been obtained, offline passive testing was only accessible. On the other hand, a wide range of wiring networks embedded in critical systems as power grids and power-plants can not be easily shutdown for testing purposes. Accordingly, we will propose in this paper an approach for diagnosing obscured networks in an on-line live mode, thanks to the Orthogonal Multi-tone Time Domain Reflectometry (OMTDR). Optimization techniques namely the genetic algorithm will be integrated with the OMTDR method to enable revealing the topology of the black-boxed tested network. Practical real-life experimental setups are dedicated to validate the proposed approach.

Keywords: Time-domain analysis; time-domain reflectometry; reflectrometry; transferometry; multicarrier reflectometry; Network topology; topology; topology reconstruction; graph theory; Testing; offline passive testing; testing purposes; Genetic algorithm; OFDM; power-plants; critical system; power cable network; live smart grids; obscured networks; Power cable; smart power grid; cable; complex network; Wiring network; power grid; black-boxed tested network; on-line live mode; Orthogonal Multitone Time Domain Reflectometry; optimization techniques; OMTDR method; fault diagnosis; fault location; defect; diagnosis; fault detection

Domains: Signal and Image Processing; Electromagnetism

Wafa Ben Hassen, Moussa Kafal, Esteban Cabanillas, Jaume Benoit. Power Cable Network Topology Reconstruction Using Multi-carrier Reflectometry for Fault Detection and Location in Live Smart Grids. 2018 Condition Monitoring and Diagnosis (CMD), Sep 2018, Perth, Australia. pp.8535596, ⟨10.1109/CMD.2018.8535596⟩. ⟨cea-03122256⟩