Single-Probe Blade Tip Timing: A Novel Method for Anomaly Identification Based on Frequency Shift

Cao, Jiahui; Yang, Zhibo; Li, Haoqi; Wang, Zengkun; Tian, Shu; Yang, Laihao; Chen, Xuefeng

doi:10.1109/tim.2021.3112794

Cited by 11 publications

(2 citation statements)

References 28 publications

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“…To overcome the frequency aliasing caused by low sampling frequency, five to seven BTT probes are usually installed. However, multiple probes have additional installation requirements and higher costs [4]. The more probes used, the less secure the entire BTT system.…”

Section: Introductionmentioning

confidence: 99%

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Single-probe blade tip timing based on sparse Bayesian learning

Yang²,

Tian³

et al. 2023

Meas. Sci. Technol.

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Blade tip timing (BTT) has become the most promising online monitoring method for turbine blade health. Current BTT data analysis algorithms are extremely sensitive to the number of BTT probes installed and the accuracy of prior information, limiting the practical application of BTT. In this article, a BTT data analysis algorithm is proposed based on a sparse Bayesian learning framework. It requires fewer BTT probes and less prior information than previous algorithms. Different degrees of noise were added to the numerically simulated BTT signal, and the results show that the method has high accuracy and reliability under high-noise conditions. The experimental results demonstrate the feasibility of the method with a single BTT probe without any prior information. Furthermore, the characteristics of the signal of a single BTT probe were investigated from a theoretical perspective.

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Section: Introductionmentioning

confidence: 99%

“…For single-probe BTT, there has been little research. Cao et al proposed a single-probe method to extract the vibration frequency difference between two blades [4]. However, this method cannot extract the natural frequency of the blade independently.…”

Section: Introductionmentioning

confidence: 99%