Gear Fault Detection via Deep‐Subwavelength Rainbow Trapping Effect of Higher‐Order Topological Mechanical Metamaterials
Source abstract
Abstract
Abstract Gear fault diagnosis is crucial for ensuring the reliable and safe operation of machinery. Recent studies explore detecting weak acoustic signals from faulty gears by designing acoustic metamaterials with defect modes or high refractive indices. These methods are constrained by low robustness and the classical diffraction limit of sound waves. Vibration analysis is the most commonly used technique in gear fault diagnosis. However, the amplification of weak vibration signals from faulty gears using higher‐order topological mechanical metamaterials (HOTMMs) remains unexplored. This study introduces a synthetic HOTMM with rainbow‐trapping effects for gear fault diagnosis. This metamaterial can enhance weak vibration signals across multiple frequencies, expanding the detection frequency range of fault signals. Additionally, it confines elastic waves to deep‐subwavelength scales, which facilitates the detection of low‐frequency fault signals. Furthermore, owing to its topological protection, the metamaterial exhibits exceptional robustness against structural defects. Exploiting the HOTMM to enhance the simulated and acquired weak gear fault signals in experiments, the fault feature signals are successfully captured, and their sources are identified. This strategy can be further applied to other rotating machinery fault diagnosis, as well as in fields such as communication, sensing, and energy harvesting.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Acoustic Wave Phenomena Research · Speech and Audio Processing · Underwater Acoustics Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Mechanical and Vehicle Engineering Hunan University Changsha 410082 China
State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha 410082 China
Funding
National Natural Science Foundation of China · Science Fund for Distinguished Young Scholars of Hunan Province · Hunan Provincial Innovation Foundation for Postgraduate
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