Blade tip timing (BTT) is an effective non-contact measurement technology for rotating blade health monitoring. However, due to the mismatching between the high-speed rotation and the limited amount of probes, the signal collected from BTT system is severely under-sampled, which induces the difficulty in feature extraction. Multiple signal classification (MUSIC) has the potential to overcome the under-sampled problem once the probes are properly placed. Whereas, if traditional MUSIC is directly used in BTT, the accuracy of frequency identification cannot be high enough and the identified numbers of frequency components are also severely restrained. To address these two problems, an improved MUSIC is proposed as an alternative methodology to extract the blade vibration frequency for BTT. Based on the orthogonality of the signal subspace and the noise subspace from under-sampled signal, the presented method can effectively identify the vibration frequency components from the under-sampled signal of BTT.

Multiple signal classification (MUSIC) has gained prominence in frequency estimation with the virtue of overcoming the undersampling problem of blade tip timing (BTT). However, as a crucial vibration feature, the amplitude cannot be estimated by MUSIC. Existing amplitude extraction methods for MUSIC are performed as postprocessing methods not related to MUSIC. Additionally, existing derivations of MUSIC for real signals use Euler’s formula to transform real signals into complex exponential signals. Therefore, this article rederives MUSIC based solely on real signals and further proposes an amplitude-identifiable MUSIC (Aid-MUSIC) approach to recover the amplitude information hidden in the eigenvalue decomposition of MUSIC. Combined with the proposed formulaic explanation of MUSIC’s asynchronous-pass ability, Aid-MUSIC is adapted according to the characteristics of BTT signal. The simulations and experiments show that Aid-MUSIC can achieve the simultaneous and stable extraction of amplitude and frequency for asynchronous frequency components without the interference of synchronous frequency components.

Blades are weak and essential parts of an aeroengine. Monitoring the running state of blades is essential for ensuring the safety of aeroengine operation. Blade tip timing (BTT) is considered a promising technique for operational blade vibration monitoring for turbomachinery; however, it is difficult to analyze the BTT signal because of the inherent undersampled limitation. To overcome this limitation, the minimal sensor layout scheme is restricted to be “three.” Usually, more than five probes are required for good signal revolution. This requirement is an installation restriction that limits the application of BTT; however, for users, the conflict between probe layout optimization and real installation restriction is also a serious problem. Motivated by these issues, a single-probe BTT (SP-BTT) method is proposed; the SP-BTT method could extract the shift between natural frequencies, which could be used as a damage index for blade condition monitoring. To validate the effectiveness of the proposed method, numerical simulations and experimental tests are performed.

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.