Study of vibration effects on electrical cable diagnosis using reflectometry

This thesis focuses on the effect of vibrations on the diagnosis of electrical cables using reflectometry. Cable systems, which are present in many critical infrastructures such as aeronautics, railways, space systems, and nuclear facilities, are exposed to mechanical and environmental stresses that may lead to soft and intermittent faults. Under vibration, these faults may appear, disappear, or modify their electrical signature, making their detection particularly challenging.

One of the main challenges concerns No Fault Found situations, in which a fault observed during operation becomes non-reproducible once the vibration conditions disappear. Another important issue is the temporary masking of certain faults by vibrations, which may lead to false negatives during diagnosis and delay the detection of latent degradation.

The objective of this thesis is to better understand and model the electromechanical behavior of cable faults subjected to vibrational stress, in order to link vibration profiles, the mechanical and electrical evolution of the fault, and the signatures measured by reflectometry. The work will be based on experiments combining fast reflectometry and a high-speed camera, as well as on the development of models and analysis tools. Experimental and simulated data will then be used to improve the detection, characterization, and prediction of fault evolution, with a view to advanced diagnosis and predictive maintenance.

Multi-scale approach for ultrasonic propagation in inhomogeneous multiple-scattering media

Ultrasonic waves are strongly influenced by the microstructure of the materials through which they propagate, leading to attenuation, dispersion, and noise. Modeling these effects is essential, particularly in non-destructive testing, where they may either hinder defect detection or provide valuable information about the material. Analytical and numerical models help to better predict and interpret these phenomena. Homogeneous statistical properties are generally assumed in such approaches. In practice, however, microstructures often exhibit significant spatial variations, for instance due to manufacturing processes. Depending on the scale of these variations relative to the wavelength, they may induce either abrupt or gradual changes in effective properties. This PhD aims to establish a theoretical framework that accounts for both microstructural randomness and its spatial variations, in order to propose relevant simulation strategies depending on the scales involved. The approach will first be developed in 1D, then extended to 2D and 3D using tools developed in the laboratory, with numerical and possibly experimental validations.