A novel method to improve the precision of BTT under rapid speed fluctuation conditions. (1st September 2022) - Wang, Weimin; Chen, Kang; Zhang, Xulong; Li, Weibo
Graphical abstract: Highlights: The influence of speed fluctuation on the theoretical arrival time is investigated. The influence of rotational speed fluctuation on the measurement of blades' vibration displacement is basically eliminated. The speed measurement error is not more than 0.6 rpm as the accelerating speed as high as 1200 rpm/s. The new method has been verified by the numerical simulation, multi-blades test-rig and largescale industry turbo fan. Abstract: It is ultra-important to evaluate the turbine machine blade dynamic stress under abnormal conditions such as rapid rotating speed fluctuation result from surge, rub and foreign object impact. The blade tip timing (BTT) based non-contact dynamic stress measurement method is the most promising technology to replace rotating blade strain gauge. However, there are great challenges to precisely monitor the blade vibration as the rotating speed rapidly fluctuated. It limits the application of BTT considerably. Here, a novel BTT method is proposed to achieve high-precision blade vibration measurement under rapid speed fluctuation conditions. The influence of speed fluctuation on the theoretical arrival time is investigated based on the relationship between blade theoretical arrival time and installation angle. Further, using of the SG filter greatly reduces the computational complexity. The effectiveness of the method is verified by numerical simulation, academic test rig and large industrial turbo fan. The results indicate that the speed measurement error is not more than 0.6 rpm as the accelerating speed as high as 1200 rpm/s. The blade vibration displacement error caused by the rapid speed change can be less than 10 μm. Comparing with existing BTT methods, the average and standard deviation of the blade vibration measurement error are greatly reduced. The method has great value for the application of the blade health monitor and predictive maintenance in turbomachines.