Eulerian laser Doppler vibrometry: Online blade damage identification on a multi-blade test rotor
Laser Doppler vibrometry enables the telemetry-free measurement of online turbomachinery blade vibration. Specifically, the Eulerian or fixed reference frame implementation of laser vibrometry provides a practical solution to the condition monitoring of rotating blades. The short data samples that are characteristic of this measurement approach do however negate the use of traditional frequency domain signal processing techniques. It is therefore necessary to employ techniques such as time domain analysis and non-harmonic Fourier analysis to obtain useful information from the blade vibration signatures. The latter analysis technique allows the calculation of phase angle trends which can be used as indicators of blade health deterioration, as has been shown in previous work for a single-blade rotor. This article presents the results from tests conducted on a five-blade axial-flow test rotor at different rotor speeds and measurement positions. With the aid of artificial neural networks, it is demonstrated that the parameters obtained from non-harmonic Fourier analysis and time domain signal processing on Eulerian laser Doppler vibrometry signals can successfully be used to identify and quantify blade damage from among healthy blades. It is also shown that the natural frequencies of individual blades can be approximated from the Eulerian signatures recorded during rotor run-up and run-down.
eulerian laser doppler vibrometry time domain analysis non-harmonic fourier analysis artificial neural networks online blade condition monitoring multi-blade rotor