The primary objective of the research reported in this thesis was the improvement of safety in helicopters by identifying and, where necessary, developing vibration analysis techniques for the detection and diagnosis of safety critical faults in helicopter transmission systems. A review and, where necessary, expansion of past research is made into (a) the mechanisms involved in the production of vibrations in mechanical systems, (b) the failure modes experienced in geared transmission systems, (c) which failure modes are critical to the safety of helicopters, (d) how the safety critical failure modes affect the vibration signature, and
e) the vibration analysis techniques currently used to detect safety critical failures. The effectiveness of the currently available vibration analysis techniques is investigated
using in-flight vibration data from Royal Australian Navy helicopters and seeded fault
data from a purpose built spur gear test rig.
Detailed analysis of techniques for synchronous signal averaging of gear vibration data is
undertaken, which includes the development of new methods of modelling and quantifying the effects of synchronous averaging on non-synchronous vibration. A study of digital resampling techniques is also made, including the development of two new methods which provide greater accuracy and/or efficiency (in computation) over previous methods. A new approach to fault diagnosis is proposed based on time-frequency signal analysis techniques. It is shown that these methods can provide significant improvement in diagnostic capabilities over existing vibration analysis techniques. Some limitations of general time-frequency analysis techniques are identified and a new technique is developed which overcomes these limitations. It is shown that the new technique provides a significant improvement in the concentration of energy about the instantaneous frequency of the individual components in the vibration signal, which allows the tracking of small short term amplitude and frequency modulations with a high
degree of accuracy. The new technique has the capability of 'zooming' in on features which may span only a small frequency range, providing an enhanced visual representation of the underlying structure of the signal.
| Identifer | oai:union.ndltd.org:ADTP/216495 |
| Date | January 1996 |
| Creators | Forrester, B. David, David.Forrester@dsto.defence.gov.au |
| Publisher | Swinburne University of Technology. |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | http://www.swin.edu.au/), Copyright B. David Forrester |
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