Article: Methodologies for modeling and identification of breathing crack: A review.
2023 Volume 11, Page(s) 102420
Abstract: Swift development of technology for monitoring complex structures demands major attention on the precision of damage detection methods. The early detection of any type of deterioration or degradation of structures is of paramount importance to avoid ... ...
| Abstract | Swift development of technology for monitoring complex structures demands major attention on the precision of damage detection methods. The early detection of any type of deterioration or degradation of structures is of paramount importance to avoid sudden catastrophic failure. It warns users about the impending state of the system. At the initiation of a crack or some other system faults, the system may generate a time-varying state of crack under ambient vibration. It represents the nonlinear breathing phenomena of crack. An assessment of this degree of nonlinearity can be utilized for the detection, localization, and quantification of breathing cracks. Appropriate modeling of such cracks is thus necessary to capture distinctive nonlinear features. Recognizing this importance, various methods of modeling and nonlinear system identification which have been employed in the past for the detection of breathing crack are reviewed. The present study also explores some of the available vibration as well as acoustic-based damage identification techniques, chronologically connecting their evolutions. It summarizes the advantages and limitations of the methods to inspect potential future applications. The future scopes drawn from this review are highlighted to pave the path of wide-spread applications of nonlinear features of crack. |
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| Language | English |
| Publishing date | 2023-10-11 |
| Publishing country | Netherlands |
| Document type | Journal Article ; Review |
| ZDB-ID | 2830212-6 |
| ISSN | 2215-0161 |
| ISSN | 2215-0161 |
| DOI | 10.1016/j.mex.2023.102420 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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