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During the working process of the turbine, some types of faults can cause changes in the vibration characteristics of the blades. The real-time vibration monitoring of the blades is of great significance to the stable operation and state-based maintenance. Torsional vibration is a kind of blade vibration modes and results in failures such as cracks easily. Thus, it is important to measure it due to the harmfulness of torsional vibration. Firstly, the principle of blade tip timing (BTT) is introduced, and the models of the blade are built to analyze the characteristics of torsional vibration. Then, the compressed sensing theory is introduced, and its related parameters are determined according to the measurement requirements. Next, based on the condition that the blade rigidity axis is not bent and bent, respectively, the layout method of sensors is proposed and the numerical simulation of the measurement process is performed. The results of the above two types of numerical simulation verify the proposed measurement method. Finally, by analyzing the influencing factors of measurement uncertainty, the optimization method of sensors’ layout is further proposed. This study can provide important theoretical guidance for the measurement of blade torsional vibration.

Cracks are common failures of aeroengine rotated blades. Online monitoring of rotated blades through their vibration to identify cracks early in various working conditions is significant for operational safety. Breathing crack is a practical form of early cracks and results in nonlinear vibration response. Tenon connection and shroud contact are common structures in aeroengine rotated blades, which can also lead blades to vibrate nonlinearly and seriously interfere online identification of early cracks. Thus, it is important to extract vibration features due to breathing crack considering these two structures. Firstly, a blade with tenon and shroud is simplified and a lumped parameter model of the bladed disk is built. Then, dry friction and coupling force on a blade are analyzed and dynamics equations of the lumped parameter model are established. Next, the stiffness of the blade trunk with a breathing crack is analyzed. Finally, the vibration response of blade trunks with the occurrence of breathing crack is analyzed in time and frequency domains by numerical simulation. Effective features due to breathing crack for online identification are extracted. 2x components of spectrums can be the criterion to judge whether breathing crack occurs. Besides, by comparing the changes in vibration amplitudes with 1x component peaks of spectrums, the cracked blade trunk can be distinguished. These findings can provide important theoretical guidance for online identification of early cracks in aeroengine rotated blades.