Rotating blade frequency identification by single-probe blade tip timing

Cao, Jiahui; Yang, Zhibo; Li, Haoqi; Teng, Guangrong; Tian, Shu; Li, Wenbo; Chen, Xuefeng

doi:10.1016/j.ymssp.2022.108961

Cited by 38 publications

(4 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the low-order vibration of the rotating blade, the vibration equation of the blade is shown in formula (2). In addition, since the phase does not affect the frequency and amplitude of the vibration, in order to simplify the derivation process of the formula, the phase is set to 0 here, and the formula (2) will be simplified to the formula (22):…”

Section: Reconstruction Of Blade Vibration Signalmentioning

confidence: 99%

“…We only need to interpolate the time series data of these n sensors in turn to obtain the sampling time series of n sensors, and then bring this sampling time series into formula (22) to obtain the sampling signal of the rotating blade vibration of the BTT system. Considering the problems of timing error and amplitude measurement error in actual measurement, the mean value of 0 is added to the sampling time series.…”

Section: Mathematical Modelingmentioning

confidence: 99%

“…Chen et al [21] derived a blind interpolation method for multifrequency BTT signals. Cao et al [22] developed a novel frequency identification method via a single BTT probe by considering arrangement, cost, and safety restrictions. The above research has greatly promoted the analysis of BTT signals and solved the identification problem of blade vibration parameters based on BTT under certain limited conditions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Parameter identification method of nonuniform and under-sampled blade tip timing based on extended DFT and compressed sensing

Zhang,

Ding

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

Vibration amplitude and frequency are the two most important indicators that characterize the health status of high-speed rotating blades, but the signal obtained by blade tip timing (BTT) technology, one of the best rotating blade vibration monitoring methods, is seriously nonuniform and under-sampled, which makes these two indicators difficult to identify. In view of this problem, the paper proposes a parameter identification method for the nonuniform and under-sampled BTT signal based on extended Discrete Fourier transform (EDFT) and Compressed Sensing (CS), with the Fourier integral transformation as the goal. It realizes the frequency analysis of nonuniform under-sampled signals by constructing and optimizing the transformation basis function instead of the exponential basis in the traditional FFT transformation in the extended frequency range, and then constructs a CS model through the obtained blade vibration frequency. The complete waveform of the blade vibration is restored by using a small number of under-sampled signals, thus obtaining the blade vibration amplitude and vibration frequency. On the one hand, the method proposed in this paper breaks through the limitation of Nyquist's sampling theorem, and the number of analytical spectral lines is no longer limited to the number of sampling points, which improves the frequency resolution. On the other hand, only a small number of measurement signals can be reconstructed to achieve a complete vibration signal. The feasibility and reliability of the proposed method are verified by mathematical modeling, simulation analysis, and experimental testing. The results indicate that when the number of sensors is greater than or equal to four, the time domain and frequency domain signals of blade vibration can be accurately analyzed based on the proposed method, the vibration amplitude error is less than 0.01 mm, the frequency error is less than 0.1 Hz, and it has good anti-interference performance.

show abstract

Section: Reconstruction Of Blade Vibration Signalmentioning

confidence: 99%

Section: Mathematical Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Parameter identification method of nonuniform and under-sampled blade tip timing based on extended DFT and compressed sensing

Zhang,

Ding

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…Te efect of blade tip clearance and rotational speed on the accuracy of blade tip-timing measurement was shown through a parametric study. Cao et al [15] proposed the short-time Fourier transform with adaptive window length, which extracted natural frequencies from a single blade tip-timing measurement based on a samplingaliasing frequency map and corresponding engine order. Mandache et al [16] developed a pulsed eddy current technique to detect engine blade and disk damage by monitoring blade tip displacement.…”

Section: Introductionmentioning

confidence: 99%

Waveform Prediction of Blade Tip‐Timing Sensor Based on Kriging Model and Static Calibration Data

Zhang

Wang

2023

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Blade tip clearance is an important parameter affecting the efficiency, stability, and safety of aero-engines. During the high-speed rotation of the blade, the blade tip clearance changes, which leads to changes in signal amplitude collected by the tip timing sensor. When the rotor is rotating at high speed, it is impractical to measure the tip-timing signal under each tip clearance. Aiming at the previous problems, a prediction method of blade tip-timing sensor waveform based on the combination of the Kriging model and static calibration data are proposed. The relationship between the output voltage of the tip timing sensor and the blade tip clearance and the angle of the blade tip cutting magnetic line is obtained by collecting the data of static calibration. Based on the collected static calibration experimental data and compared with the polynomial fit method and the RBF model, the accuracy of the Kriging model in predicting the waveform of the blade tip timing sensor was verified. The results show that the prediction accuracy of the Kriging model is basically the same as that of the RBF model, but the Kriging model has more advantages in predicting the waveform when the blade tip clearance is unknown. In contrast, the prediction accuracy of the polynomial fit is lower than that of the Kriging and RBF models, and the polynomial fit is prone to significant prediction errors.

show abstract

Research on dynamic characteristics of three-dimensional tip clearance with regard to blade crack depth and location of rotary blade-disk-shaft coupling system

Zhang,

Xiong,

Fan

et al. 2024

Nonlinear Dyn

View full text Add to dashboard Cite

Rotating blade frequency identification by single-probe blade tip timing

Cited by 38 publications

References 23 publications

Parameter identification method of nonuniform and under-sampled blade tip timing based on extended DFT and compressed sensing

Parameter identification method of nonuniform and under-sampled blade tip timing based on extended DFT and compressed sensing

Waveform Prediction of Blade Tip‐Timing Sensor Based on Kriging Model and Static Calibration Data

Research on dynamic characteristics of three-dimensional tip clearance with regard to blade crack depth and location of rotary blade-disk-shaft coupling system

Contact Info

Product

Resources

About