Abstract: Faults in rotating machines can be diagnosed or detected using two radio frequency (RF) sensing modes. RF sensing phenomenon can be used to detect the presence of undesirable behavior in rotating machines including excessive bending, vibration, eccentricity, torsion, and longitudinal strain. RF based sensors represent a non-invasive solution. The sensing modes are based on RF metamaterials and Doppler effect influence and radar cross section evaluation all coupled with a machine learning algorithm. The system is based on monitoring resonance shift, negative permeability and return loss magnitudes. Electromagnetic numerical simulations showed a significant change in those magnitudes upon applied mechanical strains as compared to original reference unstrained cases. Metamaterial texturing design can be controlled by controlling the cells scale and substrate materials.