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接接头的疲劳特性数据集
Caiyan Deng1,2, Chenyu Luo1, Baoming Gong1
1Department of Materials Science and Engineering, Tianjin University, Tianjin, 300350, China.
Scientific data
|November 18, 2025
概括
一个新的数据集收集了接接头的疲劳性能数据,解决了工程研究中的不一致性. 这种结构化资源有助于理解疲劳行为和开发机器学习模型,以提高结构可靠性.
科学领域:
- 材料科学 材料科学 材料科学
- 机械工程 机械工程
- 数据科学数据科学数据科学
背景情况:
- 接接头的疲劳故障对工程应用中的结构可靠性和使用寿命产生重大影响.
- 现有的疲劳研究经常受到数据碎片化和不一致的影响,阻碍了全面的分析.
- 结构化数据集对于进一步了解接接头的疲劳行为至关重要.
研究的目的:
- 为接接头建立一个结构化,全面的疲劳性能数据集.
- 整合各种疲劳数据,包括应力寿命 (S-N) 和应变寿命 (ε-N) 数据,以及材料,加工,接和测试参数.
- 促进数据标准化和在研究界公开共享.
主要方法:
- 从1666个同行评审的出版物中系统地提取数据,使用自然语言处理,图像识别和表格解析.
- 将提取的数据组织成一个统一的格式,以便访问和分析.
- 量化评估以确保数据的完整性和可用性.
主要成果:
- 对接接头的结构化疲劳性能数据集已成功创建并部署在一个开放访问平台上.
- 该数据集集成了S-N和ε-N数据与关键的上下文信息,促进模式识别.
- 数据集经过质量,完整性和可用性验证,支持高级分析应用.
结论:
- 开发的数据集为识别接接头的疲劳行为模式提供了可靠的基础.
- 这个资源对于训练和验证机器学习模型来预测疲劳寿命是有价值的.
- 数据集和相关工具的开放可访问性促进了数据标准化和疲劳分析的协作研究.
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