Fan Zhenfang, Li Hongkun, Huang Jinying, Liu Siyuan
School of Mechanical Engineering, North University of China, Taiyuan 030051, China.
School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China.
Sensors (Basel). 2024 Dec 18;24(24):8083. doi: 10.3390/s24248083.
Blades are the core components of rotating machinery, and the blade vibration status directly impacts the working efficiency and safe operation of the equipment. The blade tip timing (BTT) technique provides a solution for blade vibration monitoring and is currently a prominent topic in research on blade vibration issues. Nevertheless, the non-stationary factors present in actual engineering applications introduce inaccuracies in the BTT technique, resulting in blade vibration measurement errors. The theory of blade vibration difference offers a new perspective for high-precision BTT techniques. This paper optimizes the traditional circumferential Fourier fitting (CFF) algorithm. According to the blade departure time measurement mechanism, four sets of BTT signals are obtained by two probes, six sets of blade vibration differences are established, and, then, a blade vibration difference-based circumferential Fourier fitting (BVD-CFF) algorithm for blade synchronous vibration parameter identification is proposed. Simulation studies demonstrate that the BVD-CFF algorithm exhibits superior anti-noise performance. Moreover, experimental investigations on a high-speed rotation blade vibration test rig and a large-scale centrifugal compressor test rig display that the engine order of blade synchronous vibrations obtained by the BVD-CFF algorithm are essentially the same as those obtained by the strain gauge method.
