A Performance Analysis of Optimization Algorithms for Wiring Network Reconstruction and Diagnosis based on Reflectometry

Moussa Kafal (1) , Wafa Ben Hassen (1) , Jaume Benoit (1)

1 LFIC - Laboratoire Fiabilité et Intégration de Capteurs

During the last decade, time domain reflectometry (TDR) methods have formed the cornerstone for the diagnosis of transmission line networks. They have been adopted recently to the blind characterization of networks, thanks to graph theory and optimization based algorithms. Using a single testing point, it became possible to reconstruct the topology of a black-boxed network while returning precise estimates of branch lengths and most importantly load impedances. In other words, disconnecting the network for testing purposes is no longer needed. In this paper, we opted to perform a comparative analysis to study the effect of different optimisation based algorithms on the applicability of the aforementioned method. Particularly, we designed CAN bus networks based on real aeronautical cables of increased complexity to investigate their performance in terms of precision and computational burden.

Keywords: cable; diagnosis; defect; Reflectometry; Transferometry; fault diagnosis; graph theory; optimisation; time-domain reflectometry; transmission lines; wiring; Complex wire networks; topology reconstruction; inverse problems; optimisation algorithm; signal processing; branch length estimation; CAN bus networks; real aeronautical cable; network blind characterization; transmission line network diagnosis; TDR methods; wiring network diagnosis; black-boxed network; single testing point; time domain reflectometry methods; wiring network reconstruction; performance analysis; bus networks; testing purposes; load impedances

Domains: Instrumentation and Detectors [physics.ins-det]; Electromagnetism

Moussa Kafal, Wafa Ben Hassen, Jaume Benoit. A Performance Analysis of Optimization Algorithms for Wiring Network Reconstruction and Diagnosis based on Reflectometry. 2019 International Automatic Testing Conference (AUTOTESTCON), Aug 2019, National Harbor, United States. pp.8961070, ⟨10.1109/AUTOTESTCON43700.2019.8961070⟩. ⟨cea-03049343⟩