The Blade Tip Timing method (BTT) is a well-known approach permitting individual blade vibration behavior characterization. The technique is becoming increasingly popular among turbomachinery vibration specialists. Its advantages include its non-intrusive nature and its capability of being used for long-term monitoring, both in on-line and offline analysis. However, the main drawback of BTT is frequency aliasing. Frequency aliasing effects in tip timing can be reduced by means of the application of different methods from digital signal analysis that can exploit the non-uniform nature of the data sampled by BTT. This non-uniformity is due to the fact that an optimization of the circumferential distribution of BTT probes is usually required in order to improve the data quality for targeted modes of blade vibration and/or orders of excitation. The BTT data analysis methods considered in this study are the non-uniform Fourier transform, the minimum variance spectrum estimator approach, a multi-channel technique using in-between samples interpolation, the Lombe-Scargle periodogram and an iterative variable threshold procedure. These methods will be applied to measured data representing quite a large scope of events occurring during gas-turbine compressor operation, e.g. synchronous engine order resonance crossing, rotating stall, suspected limit-cycle oscillations. Finally, the frequency estimates obtained from all these methods will be summarized.
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