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Acoustic Metamaterial Sensing System for Bearing Fault Detection in Rotate Vector Reducers

  • Shiqing Huang,
  • Yubin Lin,
  • Weijie Tang,
  • Rongfeng Deng,
  • Baoshan Huang,
  • Yousif Muhamedsalih,
  • Fengshou Gu,
  • Andrew D. Ball

摘要

The escalating use of precision components in industrial robots necessitates the development of effective Condition Monitoring (CM) techniques tailored specifically for Rotate Vector (RV) reducers. While vibration and acoustic emission techniques have been extensively studied and validated for fault diagnosis in RV reducers, the potential of airborne acoustic sensing analysis remains largely unexplored. This study introduces a groundbreaking detection method that leverages the distinctive properties of acoustic metamaterials to create a compact sensing system with frequency selective capabilities and sound pressure enhancement. The novel system is applied to the detection of bearing faults of RV reducers. Experimental results demonstrate the remarkable effectiveness of the proposed acoustic metamaterial sensing system in detecting outer race faults measuring 0.5 mm in size in RV reducer supporting bearings. Furthermore, the system’s performance is rigorously validated by subjecting it to varying levels of white Gaussian noise during experiments, thereby showcasing its robustness in accurately extracting bearing fault characteristics. The successful application of the acoustic metamaterial sensing system for fault detection in RV reducers not only opens up new possibilities in diverse detection fields but also underscores the vast application potential of metamaterial-based systems for fault diagnosis in precision components.