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This work reports a finite element analysis (FEA) model study of the stator current spectra of a commercial permanent magnet (PM) AC machine operating with rotor PM demagnetisation faults. A range of PM uniform and local demagnetisation fault scenarios at different severity conditions are examined. The aim of this study is to investigate the extent to which different modes of PM demagnetisation could be distinguished by inspecting the spectral signature patterns these generate in the stator current signal. To this end, a generalised mathematical characterisation of PM fault spectral signature in the stator current is examined and a 2D FEA software used to establish a model of the studied PM machine design. The FEA model was employed to predict the current signal spectral signature patterns of a range of different PM demagnetisation faults. These are then correlated with those arising from the derived expressions to examine whether the predicted and expected spectral trends are in agreement and whether their observation as the potential to provide diagnostic information.

This work reports a finite element analysis (FEA) model study of the stator current spectra of a commercial permanent magnet (PM) AC machine operating with rotor PM demagnetisation faults. A range of PM uniform and local demagnetisation fault scenarios at different severity conditions are examined. The aim of this study is to investigate the extent to which different modes of PM demagnetisation could be distinguished by inspecting the spectral signature patterns these generate in the stator current signal. To this end, a generalised mathematical characterisation of PM fault spectral signature in the stator current is examined and a 2D FEA software used to establish a model of the studied PM machine design. The FEA model was employed to predict the current signal spectral signature patterns of a range of different PM demagnetisation faults. These are then correlated with those arising from the derived expressions to examine whether the predicted and expected spectral trends are in agreement and whether their observation as the potential to provide diagnostic information. [ABSTRACT FROM AUTHOR]