Noninvasive Fault Monitoring of Electrical Machines by Solving the Steady-State Magnetic Inverse Problem

This paper proposes an original approach for detection, localization, and quantification of faults appearing in electrical machines. The used method in this work deals with the analysis of the external magnetic field of a machine. This approach is already known, but until now, classical methods only detect if a fault is present or not. Thus, we propose a new approach based on the theory of inverse problems. From magnetic measurements realized on sensors located around the machine, a numerical model of the machine is inverted to get the distribution of the flux in the air gap. Therefore, the analysis of this distribution can allow us not only to identify a faulty mode, but also to quantify its importance.