In this thesis, topics of importance to the fault diagnosis of rotating machinery in the power generation industry have been addressed, including a review of the relevant literature and an overview of the associated rotordynamics modelling and analysis techniques. For faults involving rotor-stator interaction it has been shown that the inclusion of torsion in mathematical models used for rotor-stator contract analyses can have a significant influence on the dynamic behaviour of the system. A 3 degrees-of-freedom model based on the Jeffcott rotor was developed and, for physically realistic systems, it was shown that very different results were obtained when including torsion, compared to when torsion was neglected, as has generally been the case in the past. An identification method for estimating both the excitation and flexible support parameters of a rotor-bearings-foundations system has been presented. Excitation due to both mass unbalance and a bent rotor were included in the analysis, which has been verified both in simulation and experimentally. The method has great practical potential, since it allows balancing to be performed using data obtained from just a single run-up or run-down, which has obvious benefits for field balancing. Using this single-shot balancing technique in experiment, vibration levels were successfully reduced by as much as 92% of their original levels. A bent rotor has been accurately identified in both simulation and experiment. It was also shown that including bend identification in those cases where only unbalance forcing was present in no way detracted from the accuracy of the estimated unbalance or foundation parameters. The identification of the flexible foundation parameters was generally successful, with measured and estimated parameters matching very closely in most cases. The identification method was tested for a wide range of conditions and proved suitably robust to changes in the system configuration, noisy data and modelling error.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:636771 |
Date | January 1999 |
Creators | Edwards, S. |
Publisher | Swansea University |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
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