Extracting useful higher order features for condition monitoring using artificial neural networks
Vibration data from an induction machine is employed to investigate higher order properties associated with electrical machine faults. Three fault conditions are investigated together with all possible permutations. By considering combinations of faults, interesting higher order properties are identified and presented, ultimately resulting in improved ANN diagnoses of faults.