Blade tip timing for monitoring crack propagation of rotor blades using Block-AOLS

Abstract

Blade tip timing (BTT) as a non-contact measurement technique can identify the blade vibration parameters. However, the signal recorded by BTT usually does not satisfy the Nyquist sampling theorem. To monitor blade crack propagation, it is important to accurately reconstruct the BTT signal to track the natural frequency shift of the rotor blade. In this paper, a sparse reconstruction method named block-accelerated orthogonal least-squares (Block-AOLS) is proposed to reconstruct the undersampled BTT signal in the time-frequency domain. Block-AOLS not only inherits the advantage of the high accuracy of AOLS but also makes use of the characteristic of block sparsity to reduce the interference components in the BTT signal. Furthermore, Block-AOLS is used to reconstruct the undersampled BTT signal to track the natural frequencies of cracked blades. The advantage of Block-AOLS is illustrated through simulation by comparing with the classical orthogonal matching pursuit. In the spin testing, the vibration of a blisk with eight blades is measured by both BTT and strain gauges, where two symmetrical blades without artificial cracks suddenly broke. The process of crack propagation can be inferred according to the shift of natural frequencies between the perfect and cracked blades. Moreover, a vibration frequency prediction method is provided to avoid comparing the natural frequencies among different blades for crack propagation monitoring, which is suitable to monitor the mistuning blades. To verify the reliability of the crack propagation monitoring using BTT, the strain signal with interval sample is analyzed by synchroextracting transform. Compared the natural frequency of the perfect blade with that of the cracked blade, the time when the natural frequency of the cracked blade shift is the same as that of the BTT result.