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• Theoretical derivations explored SFPR errors in BTT, confirmed by rigorous experiments and simulations. • Simulation and experimentation verified errors from speed fluctuation on blade frequency spectrum analysis. • An actual angle of arrival fitting method is proposed to correct speed fluctuation errors in BTT. • Simulation and experiment results show the proposed method is more accurate and robust than the conventional method. Blade tip timing (BTT) serves as an innovative non-contact technique for measuring blade tip vibration displacement, offering the capability to conduct online measurements of blade vibrations during operation. Despite its potential, the conventional BTT calculation method encounters significant inaccuracies attributable to speed fluctuation per revolution (SFPR), posing challenges for identifying blade vibration parameters accurately. To address this issue, extensive theoretical derivations were undertaken to comprehensively investigate the factors influencing the error magnitude induced by speed fluctuation. In response to the identified challenges, an innovative approach known as the actual angle of arrival fitting BTT method (AAF) was proposed. This method, grounded in a least square approach, aims to reduce errors caused by SFPR and enhance the precision of blade vibration measurement. The correctness of theoretical derivations and the effectiveness of the AAF BTT method were validated through thorough numerical simulations and experimental verifications, providing valuable insights into improving measurement accuracy. Results from these validations underscored the simplicity, efficiency, and enhanced accuracy afforded by the AAF method in measuring blade tip vibrations. By overcoming the limitations of conventional BTT calculation methods, the AAF approach offers a promising avenue for more accurate and reliable blade tip vibration measurements in various operational contexts. [ABSTRACT FROM AUTHOR]

Blade tip timing (BTT) is a noncontacting vibration measurement method for rotating blade condition monitoring. The BTT sampling frequency is proportional to the number of probes under uniform probe layout and constant rotating speed. However, the limitation of the probe installation space in aeroengines causes the lack of probes, which leads to the inherent undersampled feature of the BTT signal. Thus, frequency identification of nonuniform undersampled signal has become a popular field in BTT signal processing. Multiple signal classification (MUSIC) is an array signal processing method that has been applied to this field. Nevertheless, the frequency traversal in MUSIC is a time-consuming process that will affect the online monitoring performance. Its running time is highly related to the dimension of the noise subspace. The subspace dimension reduced MUSIC (SDR-MUSIC) is proposed in this article to reduce the running time of MUSIC by reducing the dimension of noise subspace. Simulations and experiments are conducted to testify that SDR-MUSIC can significantly reduce the running time of MUSIC while ensuring accuracy. [ABSTRACT FROM AUTHOR]

The harsh working environment of compressor threats the integrality of bladed disk. Crack is one of the most fatal faults of rotating blades. Detecting the crack of blades at early stage could ensure the safe operation of gas turbine and save economic costs. Blade tip timing (BTT) is a noncontact blade vibration measurement technique, which is widely used in recent years. In this article, a procedure of crack detection using BTT data is proposed. First, some typical parameters are taken into consideration, including resonance frequency, amplitude change of natural frequency, amplitude of blade tip, phase, and interblade spacing. It has been found that the frequency of the blade will decrease with the increment of crack length and reduction of crack height. In addition, the resonance frequency of the bladed disk will split when the blade cracks. The amplitude of different orders of resonance frequency varies with cracks. The amplitude of the first order changes very slightly, whereas the second and third orders are relatively obvious. The blade tip vibration amplitude and phase change with cracks without obvious regularity. The interblade distance will change due to the appearance of cracks. According to the above rules, the frequency and the interblade distance are adopted as crack diagnosis indicators. First, we use the Lomb–Scargle periodogram to quickly determine whether the crack appears and then use the blade frequency and interblade distance to locate the number of the blade having crack. In the experimental test, BTT data measured on a titanium bladed disk is used to verify the effectiveness of our method. [ABSTRACT FROM AUTHOR]