Automated phase offset correction using reflectometry in fault detection systems

Autor: Esteban Cabanillas, Christophe Layer
Přispěvatelé: Département d'Architectures, Conception et Logiciels Embarqués-LIST (DACLE-LIST), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Laboratoire d'Intégration des Systèmes et des Technologies (LIST)
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS)
2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), Aug 2017, Boston, United States. ⟨10.1109/MWSCAS.2017.8053197⟩
MWSCAS
Popis: International audience; Well established cable network diagnosis systems rely on reflectometry and transferometry principles to detect faults using specific signals within a frequency spectrum of a few hundreds MHz only. Huge performance improvements in terms of precision and sensitivity can be achieved with higher frequencies and signal modulation, hence revealing phase and amplitude response of the potential impedance discontinuities on the tested channel to better classify the defects. However, as for telecommunications, frequency translation requires a special care in signal processing and integrity, the relative complexity of which has discouraged its implementation in wire diagnosis systems for now. Crossing the domains with an ingenious phase-offset correction mechanism, we show that defects can be accurately detected and correctly analyzed with our system relying on quadrature modulation. The presented method provides several advantages over state-of-the-art techniques and is particularly well suited for implementations in distributed sensor networks. Accordingly, our measurements were performed using an FPGA-based embedded platform and discrete high-frequency components.
Databáze: OpenAIRE