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A joint reflectometry-optimization algorithm for mapping the topology of an unknown wire network

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  • معلومة اضافية
    • Contributors:
      Laboratoire Fiabilité et Intégration de Capteurs (CEA, LIST) (LFIC (CEA, LIST)); Département Métrologie Instrumentation & Information (CEA, LIST) (DM2I (CEA, 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)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)); Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay
    • بيانات النشر:
      HAL CCSD
      Institute of Electrical and Electronics Engineers Inc.
    • الموضوع:
      2017
    • Collection:
      HAL-CEA (Commissariat à l'énergie atomique et aux énergies alternatives)
    • الموضوع:
      Glasgow; United Kingdom
    • نبذة مختصرة :
      Conference of 16th IEEE SENSORS Conference, ICSENS 2017 Conference Code:132067 ; International audience ; Despite the fact that wireless systems are overwhelming most of nowadays applications, wiring networks are still forming a pivotal anchor in many controls and security units. Thus, ensuring the reliable operation of such networks necessitates investing in techniques dedicated for their protection. A vast majority of such methods rely on the presence of a reference model of the network. In this paper, we propose a nondestructive testing approach based on the tenets of reflectometry methods and genetic algorithms to retrieve the topology and load impedances of unknown embedded complex wiring networks.
    • Relation:
      cea-01817859; https://cea.hal.science/cea-01817859; https://cea.hal.science/cea-01817859/document; https://cea.hal.science/cea-01817859/file/article_MoussaKafal_ConfIEEESensors2017.pdf
    • الرقم المعرف:
      10.1109/ICSENS.2017.8234208
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.E5C2E1D9