A metamaterial beam with multi-piezoelectric patches (MB-MPP) for weak vibration enhancement in rotating machinery fault diagnostics

Condition monitoring of rotating machinery constitutes essential approaches for enhancing the reliability and safety of mechanical systems. Vibration signal sensing technology has emerged as a pivotal tool in rotating machinery fault diagnosis, offering advantages of rich information content and accessibility. However, conventional fault diagnosis approaches heavily depend on high-performance sensors and advanced signal processing to determine optimal resonance bands for high signal-to-noise ratio (SNR) fault characteristics, which suffers from high cost and intricate algorithm deployments. To address these limitations, this paper proposed a new vibration sensing method based on a gradient metamaterial beam, which is shorten as metamaterial beam with multi-piezoelectric patches (MB-MPP) for brevity. The MB-MPP structure is designed to have multiple frequency bands for weak fault signal enhancement, and multiple piezoelectric patches are integrated into MB-MPP to convert the dynamic stress into voltage signals, achieving a multi-band sensing system. The design and optimization of MB-MPP for desired frequency bands was first carried out based on the mechanism of the rainbow trapping. Subsequently, the frequency band characteristics and the signal enhancement were tuned and validated by finite element simulations so that MB-MPP can achieve multiple discrete frequency bands which meet the need for monitoring commonly used machines. Finally, experiment evaluations were conducted based on the rotating machinery to prove the performance of the designed metamaterial. The results show that the SNRs of fault signals can be improved by over 50% in diagnosing common faults in rolling bearings and gears, which ensures the accuracy and reliability of diagnostics significantly.