Blade tip timing: From raw data to parameters identification

Blade Tip Timing (BTT) methods have been increasingly implemented for blade health monitoring. However, most of them are based on the prior knowledge that the resonance's location is known. Since real BTT test usually takes more than ten hours, it's unrealistic to Figure out every resonance from the measured raw data manually. Furthermore, BTT data analysis suffers from its inherent under-sampled and non-uniform shortcoming. In this paper, we present a simple yet effective method for BTT-based blade health monitoring. The method starts with an automatic resonance recognition, where cross-correlation and Savitzky Golay filter are used to locate the resonance region. Then an adaptively reweighted least-squares periodogram algorithm is designed to identify parameters of the resonant vibration. The effectiveness of the algorithm was tested using both simulation and real test data.