Predictive Diagnostic Based on HF Modeling of Electrical Machines Windings

Early aging of electrical machines is most commonly due to Electrical Insulation System (EIS) faults. Depending on the applications the electrical machine is used for, the EIS is subject to different stress factors, such as thermal, mechanical and electrical stresses, which can lead to a progressive deterioration of the organic materials it is made of, especially in terms of insulative properties. The aim of this paper is to show that it is possible to anticipate the change of those insulative properties in order to implement it in a predictive diagnostic tool allowing to highlight the parameters which are the best to monitor while the electrical machine is running under normal operation conditions.