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Title: | Time-domain spectra of ultrasonic wave transmitted through granite and gypsum samples containing artificial defects |
Authors: | Tian, Z Zou, C Wu, Y |
Keywords: | artificial defects;nondestructive testing;rock defects;stress wave;time-domain spectra;time-series data;ultrasonic wave |
Issue Date: | 31-Oct-2024 |
Publisher: | Wiley on behalf of the Royal Meteorological Society |
Citation: | Tian, Z., Zou, C. and Wu,Y. (2025) 'Time-domain spectra of ultrasonic wave transmitted through granite and gypsum samples containing artificial defects', Geoscience Data Journal, 12 (1), e281, pp. 1 - 13. doi: 10.1002/gdj3.281. |
Abstract: | The internal defects in rock masses can significantly impact the quality and safety of geotechnical projects. Mechanical waves, as a common nondestructive testing (NDT) method, can reflect the external and internal structures of rock or rock masses. Analyses on the reflected and transmitted waves enable nondestructive identification and assessment of potential defects within rocks. Previous studies mainly focused on the variation of single or limited wave features like main frequency, amplitude and energy between the intact and non-intact samples. In fact, most information contained in the waveforms is neglected. Techniques of data mining can provide a powerful tool to reveal this information and therefore a more accurate determination of the internal structures. In this study, 995,412 NDT data from 14 types of granite and gypsum samples with different cross-section shapes and different types of defects are recorded by an ultrasonic wave generation and collection system. This dataset can be used not only as the training data for defect classification in NDT but also as a good reference for conventional NDT analyses. Besides, time-series data analysis is an opportunity and challenging issue, this dataset holds great potential for broader application in general time-series classification analysis. |
Description: | Data Availability Statement: The dataset is open-source via FigShare: https://doi.org/10.6084/m9.figshare.24954945. We welcome researchers to use this dataset for their research. |
URI: | https://bura.brunel.ac.uk/handle/2438/30587 |
DOI: | https://doi.org/10.1002/gdj3.281 |
Other Identifiers: | ORCiD: Zhuoran Tian https://orcid.org/0009-0006-1889-6521 ORCiD: Chunjiang Zou https://orcid.org/0000-0001-9646-0236 e281 |
Appears in Collections: | Dept of Civil and Environmental Engineering Research Papers |
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