Time-domain spectra of ultrasonic wave transmitted through granite and gypsum samples containing artificial defects

IF 3.3 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY Geoscience Data Journal Pub Date : 2024-10-31 DOI:10.1002/gdj3.281
Zhuoran Tian, Chunjiang Zou, Yun Wu
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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.

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岩体的内部缺陷会严重影响岩土工程的质量和安全。机械波作为一种常见的无损检测(NDT)方法,可以反映岩石或岩体的外部和内部结构。通过对反射波和透射波进行分析,可以对岩石内部的潜在缺陷进行无损识别和评估。以往的研究主要集中在完整样本和非完整样本之间单一或有限波形特征的变化,如主频、振幅和能量。事实上,波形中包含的大部分信息都被忽略了。数据挖掘技术可以为揭示这些信息提供强有力的工具,从而更准确地确定内部结构。在这项研究中,超声波生成和收集系统记录了来自 14 种不同截面形状和不同缺陷类型的花岗岩和石膏样品的 995 412 个无损检测数据。该数据集不仅可用作无损检测中缺陷分类的训练数据,还可作为常规无损检测分析的良好参考。此外,时间序列数据分析是一个机遇与挑战并存的问题,因此该数据集具有在一般时间序列分类分析中进行更广泛应用的巨大潜力。
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来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
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