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Probabilistic Diagnostic Algorithm-Based Damage Detection for Plates with Non-uniform Sections Using the Improved Weight Function

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Abstract

Introduction

The current studies on damage detection based on guided wave mainly focus on uniform-section plate-like structures. However, plates with non-uniform sections are also essential structures in some engineering applications, such as ships, bridges, aircraft, and buildings. It is essential to identify damage in the non-uniform-section plates (NUSPs).

Objectives

An improvement is put forward to make reconstruction algorithm for the probability inspection of damage (RAPID) feasible on NUSPs.

Methods

Reconstruction algorithm for the probability inspection of damage (RAPID) is a promising kind of tomography technique for detection and supervising of structures. The damage signatures based on the differences between the Lamb wave signals captured from the undamaged (reference) and damaged (present) states are used to assess the probability of the damage. The elliptical weight function commonly used in the RAPID algorithm limits the applications of the method in identifying damage in non-uniform-section plates. In this study, a novel method is proposed to choose the weight function that satisfies not only uniform-section plates but also NUSPs. A series of experiments on aluminum plates are carried out to validate the correctness of the method mentioned before.

Conclusion

The results indicate that the improvement considerably increases the precision of the localization of damage in NUSPs.

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Acknowledgements

The authors would like to gratefully acknowledge the supports received from the National Natural Science Foundation of China (NSFC Nos. 11372179 and 51405291) and Program for New Century Excellent Talents in University (NCET-13-0363).

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Correspondence to Jingjing Zhao.

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Zhao, J., Miao, X., Li, F. et al. Probabilistic Diagnostic Algorithm-Based Damage Detection for Plates with Non-uniform Sections Using the Improved Weight Function. J. Vib. Eng. Technol. 6, 249–260 (2018). https://doi.org/10.1007/s42417-018-0032-5

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  • DOI: https://doi.org/10.1007/s42417-018-0032-5

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