S0 Mode Selective Metamaterial-Based Ultrasonic Guided Wave Damage Detection in Thin-Walled Metal Plate
The application of ultrasonic guided wave technology in damage detection in thin-walled metal plates presents multi-modal complexities that result in imaging artifacts, thereby complicating damage assessment. To address this challenge, this paper proposes a layered S0 mode selective metamaterial for extracting the S0 mode Lamb wave in order to detect damage in thin-walled metal plates. The regulatory layer of metamaterial can generate a single S0 mode region, allowing the excited guided wave within this frequency range to selectively propagate the S0 mode while suppressing other modes. In order to obtain a better single S0 mode region, a genetic algorithm is used to optimize the structure of the regulatory layer. The effectiveness of the S0 mode selective metamaterial is substantiated through both numerical simulations and experimental validation. Finally, a Metamaterial-based Reconstruction Algorithm for Probabilistic Inspection of Damage (M-RAPID) method is proposed, which uses the S0 mode wave in the array ultrasonic guided wave to accurately detect the damage of thin-walled metal plate, reducing interference form the other modal imaging artifacts. This study represents the use of metamaterial for single mode selection and damage imaging in nondestructive testing, highlighting the significant potential of metamaterial in this field.
Authors
- Jiangbo Chen (ORCID: https://orcid.org/0000-0002-9928-8109)
- Xiaobin Hong (ORCID: https://orcid.org/0000-0002-2392-2556)
- Ao Zhang (ORCID: https://orcid.org/0009-0007-3863-4817)
- Dingmin Yang (ORCID: https://orcid.org/0000-0001-5680-5674)
- Weiguo Chen (ORCID: https://orcid.org/0009-0009-1681-3675)
- Jikang Yue (ORCID: https://orcid.org/0000-0002-8648-9171)
Institutions
- South China University of Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Instrumentation and Measurement
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tim.2025.3588934
- Citations
- 3
- Primary Topic
- Engineering Applied Research
- Type
- article
- Field-Weighted Citation Impact
- 2.86
Funders
- National Natural Science Foundation of China