Rehman, Anees ur and Rehman, Anees ur (2012) Vibration-Based Condition Monitoring of A Turbomachinery Bladed System. PhD thesis, University of Sheffield.Full text not available from this repository. (Request a copy)
Static and rotating blades in turbine engines are susceptible to vibration-induced failure because of the high dynamic operating loads. Excitation can be broadband or linked to the rotation speed. The accurate functioning of the complete turbomachinery system depends on the structural integrity of individual blades as any propagating damage, in the form of a fatigue crack, intimidates the functioning of the entire system. Because of this, there is growing interest in the early detection of damage in blades. Damage detection in mistuned turbomachinery bladed systems is addressed in this research utilising a statistical approach to vibration-based damage detection. Initially, a modal characteristics-based damage identification technique is developed by obtaining damage indices based on the differences in the Modal Assurance Criterion (MAC) that give a measure of the change in the mode shapes. These damage indices are then correlated to the depth/location of the damage and also to the level/pattern of the mistuning present. The possibility of characterising cracks from their nonlinear response is investigated by detecting and classifying nonlinearity arising from a breathing crack interface. Nonlinearity detection is achieved by obtaining the amplitude dependent Frequency Response Functions (FRFs) and classification is accomplished by obtaining their Hilbert transform (HT). The breathing crack nonlinear behaviour is numerically validated by drawing a comparison between experimental and numerical results. The Coulomb friction-induced damping at the crack interface is quantified by obtaining relationships between crack depth/coefficient of friction and damping levels/friction stress/crack face pressures. Based on the conclusions from the breathing crack nonlinear behaviour investigations, damage detection in the mistuned bladed disc is addressed utilising outlier analysis. The effect of noise on the damage detection is studied by obtaining the maximum, mean and minimum damage detectability levels for varying noise. Both, the frequency and time domain data from the bladed disc are considered for damage detection. For the frequency domain, FRFs for varying mistuning levels in the bladed disc are obtained and damage detection is addressed when the FRF peak of the crack mode cannot be distinguished from the cluster of mistuning modes. In the time domain, the effectiveness of the developed damage detection procedure is examined for reduced data sets from the blade tips (blade tip timing).
|Item Type:||Thesis (PhD)|
|Keywords:||Damage Detection, Turbomachinery Blading, Breathing Crack, Mistuning, Nonlinearity Detection and Classification, Crack Characterisation, Hilbert Transform, Outlier Analysis, Modal Assurance Criterion (MAC), Damage Index, Frequency Response Funstions, Blade Tip Timing, Friction Damping Models.|
|Academic Units:||The University of Sheffield > Faculty of Engineering (Sheffield) > Mechanical Engineering (Sheffield)|
|Depositing User:||Mr Anees ur Rehman|
|Date Deposited:||30 Jul 2012 15:56|
|Last Modified:||08 Aug 2013 08:49|