Blade Tip-timing Measurement Mathematical Modeling and Simulation Without OPR Under the Condition of Rotating Speed Fluctuation

Author(s):  
Zhibo Liu ◽  
Fajie Duan ◽  
Xiuming Li ◽  
Jiajia Jiang ◽  
Guangyue Niu ◽  
...  
2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Zhongsheng Chen ◽  
Jing He ◽  
Chi Zhan

Blade tip-timing (BTT) is a promising method of online monitoring rotating blade vibrations. Since BTT-based vibration signals are typically undersampled, how to reconstruct characteristic vibrations from BTT signals is a big challenge. Existing reconstruction methods are mainly based on the assumption of constant rotation speeds. However, rotating speed fluctuation is inevitable in many engineering applications. In this case, the BTT sampling process should be nonuniform, which will cause existing reconstruction methods to be unavailable. In order to solve this problem, this paper proposes a new reconstruction method based on nonlinear time transformation (NTT). Firstly, the effects of rotating speed fluctuation on BTT vibration reconstruction are analyzed. Next, the NTT of BTT sampling times under rotating speed fluctuation is presented. Then, two NTT-based reconstruction algorithms are derived for uniform and nonuniform BTT sensor configurations, respectively. Also several evaluation metrics of BTT vibration reconstruction under rotating speed fluctuation are defined. Finally, numerical simulations are done to verify the proposed algorithms. The results testify that the proposed NTT-based reconstruction method can reduce effectively the influence of rotating speed fluctuation and decrease the reconstruction error. In addition, rotating speed fluctuation has more bad effects on the reconstruction method under nonuniform sensor configuration than under uniform sensor configuration. For nonuniform BTT signal reconstruction under rotating speed fluctuation, more attentions should be paid on selecting proper angles between BTT sensors. In summary, the proposed method will benefit for detecting early blade damages by reducing frequency aliasing.


Measurement ◽  
2021 ◽  
Vol 176 ◽  
pp. 109168
Author(s):  
Suiyu Chen ◽  
Yongmin Yang ◽  
Haifeng Hu ◽  
Fengjiao Guan ◽  
Guoji Shen ◽  
...  

2020 ◽  
Vol 16 (4) ◽  
pp. 135-170
Author(s):  
Eva Gupta ◽  
Nand Jee Kanu ◽  
Amartya Munot ◽  
Venkateshwara Sutar ◽  
Umesh Kumar Vates ◽  
...  

2021 ◽  
pp. 110870
Author(s):  
Mauricio M. Coletto ◽  
J. Alberto Bandoni ◽  
Aníbal M. Blanco

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