Effective tactics to reliably anatomize and troubleshoot complex transmission line networks
Electrical cables are extensively used in nearly all modern systems. They play a primary role in energy and signal distribution where wiring networks are fundamental subsystems whose proper functioning is of critical importance. Eventually, a cable may show signs of weakness, which can lead to the appearance of defects and eventually faults. Ensuring the reliable use of cables requires the availability of techniques capable of detecting the presence of faults that could potentially put in jeopardy a whole system. While several electric and nonelectric wire diagnosis methods have been studied and developed, reflectometry-based techniques are still in the center stage of research and industrial applications in this domain. Essentially, based on a time-domain approach, reflectometry methods inject a test signal into the network under test and monitor the reflected one in order to detect the presence, position, and nature of an impedance discontinuity. The diagnosis of complex topology networks may require the use of several diagnosis systems in parallel, each one providing a different view of the network, thus eliminating location ambiguities. This has been made possible by the adoption of spread spectrum techniques enabling several reflectometers to work concurrently without interfering. For safety critical systems, it may be necessary to monitor the health of the cables during their normal operation. Online diagnosis is then used, requiring harmlessness: diagnosis signals must not interfere with communication signals, and useful signals must not trigger any false alarm. We proposed and have been developing at the LFIC lab of CEA wire testing methods since more than 10 years. Significantly, we developed three novel variants of reflectometry that allow online wire troubleshooting, the Multi Carrier Time Domain Reflectometry (MCTDR), Orthogonal Multi-Tone Time Domain Reflectometry (OMTDR), and the Chaos Time Domain Reflectometry (CTDR). In this talk, I will address these three methods in addition to four of our key reflectometry assets:
- Network characterization including data acquisition by VNA, cable RLCG parameters extraction, blind topology reconstruction, etc.
- Transmission line simulation and modelling tools for guided wave propagation analysis with easy user interfaces.
- Novel signal processing approaches for fault signature enhancements allowing better detection, location and characterization.
- Hardware implementation for specific I/O boards for reflectometry methods.
Moussa Kafal (SM’2014, M’2017) received a double B.Sc. degree in physics and electronics and the M.Sc. degree in telecommunication from the Lebanese University, Beirut, Lebanon, in 2010 and 2012 respectively. He then received the Ph.D. degree in electrical engineering from the French engineering school Centralesupélec at the University of Paris Saclay in 2016. From October 2016 to December 2017, he served as a postdoctoral researcher at the French Alternative Energies and Atomic Energy Commission (CEA). Currently, he is a full-time research and development engineer at CEA. His research interests include troubleshooting of complex transmission line networks, application of optimization and machine learning algorithms, and the application of time reversal to electromagnetics. Dr. Kafal was a recipient of the Best Student Technical Paper Award at the IEEE AUTOTEST Conference, Washington, DC, USA, in 2015. He has authored or coauthored over 25 papers in international conferences and peer-reviewed journals and is currently chairing special sessions dedicated for fault diagnostics in wire networks in international conferences. He serves as an associate editor at the IEEE Sensors journal and is a reviewer for several IEEE and non-IEEE scientific transactions.