Variable amplitude Compression Compression fatigue tests on single stiffener aerospace structures 核心 · 已核验
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This dataset contains health monitoring data collected during compression compression fatigue tests of single stiffener (Level 1) aerospace composite panels. The coupons were initially damaged either by a low velocity impact or by an artificial disbond, located between the stiffener and the skin (a pdf file highlights the locations). Five coupons were tested in variable amplitude fatigue until failure and the folders contain Acoustic Emission (.DTA), Lamb waves and optical fibres (FBGs) data. This dataset is the second series of the 4 testing campaigns.
本卡描述如含来自官方页的原文片段,其版权归原作者,不在本站 CC-BY 4.0 许可范围(见关于与许可)。
- 落地页
- https://doi.org/10.34894/WCDRLW
- 许可证
- CC-BY-SA-4.0 (置信:verified_official)
- 国内可访问性
-
国内直连:可达 (2026-07-11 检测)
非直连:可达 (2026-07-11 检测)
「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。 - 发布年份
- 2025
- 设备类型
composite_structure- PHM 任务
health_state_assessment
故障工况
| fault_type: delamination |
传感器
| sensor_type: fiber_bragg_grating_sensor |
| sensor_type: acoustic_emission_sensor |
运行工况
| condition_type: load |
关联论文(39 篇)
仅表示这篇论文与本数据集在文献网络中相邻, 不代表该论文确实使用了本数据集。
- Health Monitoring of Aerospace Structures Utilizing Novel Health Indicators Extracted from Complex Strain and Acoustic Emission Data 2021 · 首发该数据集
- UAV Assisted Wireless Sensor Network Architecture with Compressive Sensing and TCN based Damage Classification for Aircraft Structural Health Monitoring 2026 · 候选引用(未核验)
- Artificial intelligence-driven glaucoma screening in ophthalmology: The GlaucoNet deep learning framework 2026 · 候选引用(未核验)
- Health indicator modeling leveraging time-independent and time-dependent subtasks with adaptive standardization and physics-based Bayesian optimization for aeronautical structures 2025 · 用于方法验证
- Graph neural networks for SHM: exploiting spatial interdependencies of strain data for diagnostics and prognostics 2025 · 用于方法验证
- Introduction and background 2025 · 候选引用(未核验)
- Characterization, analysis and prediction of damage onset in adhesively bonded joints using fracture mechanics and acoustic emission monitoring technique 2025 · 候选引用(未核验)
- An Overview of Damage Identification in Composite Structures—From Computational Methods to Machine Learning 2025 · 候选引用(未核验)
- Machine Health Indicators and Digital Twins 2025 · 候选引用(未核验)
- Non-Destructive Testing and Evaluation of Hybrid and Advanced Structures: A Comprehensive Review of Methods, Applications, and Emerging Trends 2025 · 候选引用(未核验)
- Machine Learning for Structural Health Monitoring of Aerospace Structures: A Review 2025 · 候选引用(未核验)
- A novel intelligent health indicator using acoustic waves: CEEMDAN-driven semi-supervised ensemble deep learning 2024 · 用于方法验证
- Intelligent Computational Methods for Damage Detection of Laminated Composite Structures for Mobility Applications: A Comprehensive Review 2024 · 候选引用(未核验)
- Advances in FBG sensor systems for SHM of composite aerospace structures 2024 · 候选引用(未核验)
- Damage indicators in unidirectional natural fibre composites under fatigue loading 2024 · 候选引用(未核验)
- Failure modes and non-destructive testing techniques for fiber-reinforced polymer composites 2024 · 候选引用(未核验)
- Critical States of Laminated Polymer Composite under Quasi-Static Deformation after Preliminary Low-Velocity Impact Loads 2024 · 候选引用(未核验)
- Enhanced Performance of Morphing Wing Through Composite Fabrication and Structural Health Monitoring 2024 · 候选引用(未核验)
- Automated Crack Detection in Monolithic Zirconia Crowns Using Acoustic Emission and Deep Learning Techniques 2024 · 候选引用(未核验)
- A data driven methodology for upscaling remaining useful life predictions: From single- to multi-stiffened composite panels 2023 · 用于迁移/跨工况
仅列前 20 篇(首发/综述优先,按年份倒序);全量见 API。
溯源(12 条)
| 来源链接: https://doi.org/10.34894/WCDRLW 日期: 2026-07-09 |
| 日期: 2026-07-10 |
| 日期: 2026-07-10 |
| 日期: 2026-07-10 |
| 日期: 2026-07-10 |
| 日期: 2026-07-10 |
| 日期: 2026-07-10 |
| 日期: 2026-07-11 |
| 日期: 2026-07-11 |
| 日期: 2026-07-14 |
| 日期: 2026-07-25 |
| 日期: 2026-07-26 |