High-Precision Extraction Method for Blade Tip-Timing Signal with Eddy Current Sensor

Zhang, Jiwang; Ding, Keqin; Chen, Guang

doi:10.1155/2020/8882858

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…In recent years, more and more researchers have begun to dedicate themselves to the research on the blade tip clearance measurement of the engine. Tey have proposed several tip clearance measurement methods, including the probe method [6], optical fber method [7], capacitance method [8], eddy current method [9], and microwave method [10]. Among them, the technical principles of different measurement methods are diferent, and each has its advantages and disadvantages.…”

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

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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.

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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

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“…So far, among the many rotating blade monitoring technologies, the blade tip timing (BTT) technology has the advantages of being non-contact and noninvasive, and it can monitor the vibration information of all blades at the same time with only a few sensors. Thus, it has become the most promising monitoring technology for rotating blades [5][6][7][8]. With this method, the timing sensor installed on the outer casing of the rotating blade records the arrival time of the blade and then compares it with the time when there is no vibration to indirectly measure the vibration information of the rotating blade.…”

Section: Introductionmentioning

confidence: 99%

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.

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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.

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“…However, this method does not consider the influence of the blade vibration phase on the measurement results. Zhang et al [14] proposed an error compensation method based on the eddy current sensor.…”

Section: Introductionmentioning

confidence: 99%

An Improved Blade Vibration Parameter Identification Method considering Tip Clearance Variation

Zhang

Wang

2021

Shock and Vibration

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Blade tip timing (BTT) technology is the most effective means for real-time monitoring of blade vibration. Accurately extracting the time of blade tip reaching the sensors is the key to ensure the accuracy of the BTT system. The tip clearance changes due to various complex forces during high-speed rotation. The traditional BTT signal extraction method does not consider the influence of tip clearance change on timing accuracy and introduces large timing errors. To solve this problem, a quadratic curve fitting timing method was proposed. In addition, based on the measurement principle of the eddy current sensors, the relationship among the output voltage of the eddy current sensor, tip clearance, and the blade cutting magnetic line angle was calibrated. A multisensor vibration parameter identification algorithm based on arbitrary angular distribution was introduced. Finally, the experiments were conducted to prove the effectiveness of the proposed method. The results show that in the range of 0.4 to 1.05 mm tip clearance change, the maximum absolute error of the timing values calculated by the proposed method is 26.0359 us, which is much lower than the calculated error of 203.7459 us when using the traditional timing method. When the tip clearance changed, the constant speed synchronous vibration parameters of No. 0 blade were identified. The average value of the vibration amplitude is 1.0881 mm. Compared with the identification results without changing tip clearance, the average value error of the vibration amplitude is 0.0017 mm. It is proved that within the blade tip clearance variation of 0.4 to 0.9 mm, the timing values obtained by the proposed timing method can accurately identify the vibration parameters of the blade.

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High-Precision Extraction Method for Blade Tip-Timing Signal with Eddy Current Sensor

Cited by 5 publications

References 21 publications

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

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

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

An Improved Blade Vibration Parameter Identification Method considering Tip Clearance Variation

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