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A method of online fault identification in rotor/ magnetic bearing systems is presented using wavelet analysis. A filter bank approach is taken to identify the discrete time wavelet coefficients of the rotor displacement signals. From artifacts present in the discrete time wavelet series associated with specific faults, it is shown that it is possible to identify both the onset time and the fault type. This method is demonstrated for simulations of a flexible rotor/active magnetic bearing assembly during auxiliary bearing contact and direct synchronous forcing for a range of running speeds covering flexural critical speeds.

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Booktitle: Proceedings of ISMB9