A revised compressed sensing method to correct phase error caused by blade vibration in blade tip timing

Abstract Rotating blades are highly susceptible to large amplitude vibrations, which can disrupt normal operation, making vibration monitoring essential. Blade tip timing (BTT), a non-contact technology, has significantly advanced for this purpose. Compressed sensing (CS) has become a popular method for vibration parameter identification based on BTT. However, the traditional CS approach does not account for the blade’s own vibration during the identification process, leading to significant errors, particularly when identifying large amplitude or high engine-order vibrations. To address this limitation, this paper introduces a revised CS vibration parameter identification method based on BTT (RCS-BTT). Numerical experiments comparing the performance of traditional CS and RCS-BTT reveal that the error in traditional CS increases with amplitude and engine order, often exceeding 10% under the conditions set in this study. In contrast, RCS-BTT demonstrates a lower and more stable average error, generally around 5%. The synchronous and asynchronous verification test rigs using different excitation methods, equipped to collect reference data, were developed for experiments. The experimental results show that under both conditions, RCS-BTT consistently outperforms traditional CS, achieving lower identification errors regardless of vibration amplitude. Notably, in the synchronous vibration case with an amplitude of 2.247 mm and an engine order of 4, the accuracy of RCS-BTT improves by 1.69% relative to that of traditional CS compared to the reference amplitude obtained from laser displacement sensor. This validates that RCS-BTT provides more accurate vibration parameter identification compared to traditional CS. Moreover, RCS-BTT demonstrates greater stability than traditional CS.