Robust diagnostics of stator insulation based on high frequency resonances measurements

The stator insulation breakdown is a major cause of AC machine failures. Ground insulation defaults are easily detected by classical systems based on leakage current measurements, however the turn-to-turn insulation degradations are more difficult to detect. For large machines, on-line methods, based on partial discharge detection and analysis, give good results but they cannot be used for low-voltage machines fed by adjustable speed drives (ASD). Previously, it has been shown by some of the authors that it was possible to estimate the aging of an AC machine winding thanks to HF measurements of current or magnetic field. In this paper, it is proposed to exploit conjointly all these different estimations to obtain a more robust and reliable diagnostic. The merging of the different estimations being realized through the belief functions framework, this approach is tested on real measurements.