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Damage Identification Based on the Nodal Line Active Modulation Method

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Abstract

A novel vibration-based method (VBM) for damage identification, nodal line active modulation (NLAM), is proposed in this study. Unlike traditional VBMs, the NLAM can identify damage by taking advantage of the nodal line effect, which is that when a defect is located on the nodal lines, the dynamic responses of the structure remain nearly unchanged. The basic idea of NLAM is introduced through a simply supported beam. In numerical study, we have discussed the detection steps of the method in detail by detecting a cleft detection in an aluminum plate. In experimental research, piezoelectric transducers work as both actuators and sensors for an added mass damaged detection in carbon fiber reinforced plastic laminates, while a scanning laser Doppler vibrometer is employed for measuring the full-field dynamic response. The damage is visualized from the highlighted nodal lines of the modulated operational deflection shapes. The present investigation provides a new idea for VBM damage detection, which will have practical applications for structural health monitoring.

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The data and material analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (Grant No: 11702118, 12102092 and 12232001)

Funding

This research is supported by the National Natural Science Foundation of China, (Grant Nos: 11702118, 12102092, 12232001)

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All authors contributed to the study conception and design. Kan Feng proposed and fulfilled the method and wrote the main manuscript. Rong Li, Jing Yan and Xu Hu helped with the experiment and the numerical analysis. Jie Zhou and Zheng Li provided constructive opinions on the method and revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Kan Feng.

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Feng, K., Li, R., Yan, J. et al. Damage Identification Based on the Nodal Line Active Modulation Method. J Nondestruct Eval 42, 70 (2023). https://doi.org/10.1007/s10921-023-00979-1

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