Blade vibration parameter identification method based on blade tip-timing signals

Abstract Blade Tip Timing (BTT) is a widely used non-contact technology for vibration monitoring in rotating machinery. Due to its inherent issue of undersampling, traditional frequency identification methods often struggle to accurately identify asynchronous vibration frequencies of the blades. To address this issue, this paper proposes a frequency identification method for BTT signals based on the Multiple Signal Classification (MUSIC) algorithm. Experimental results show that the MUSIC algorithm significantly improves the accuracy of blade vibration parameter identification, providing reliable technical support for the health monitoring and fault diagnosis of rotating machinery.