基于声辐射信号分解的复合结构的多模式合损坏分类方法
Yinmin Zhu1, Wenhao Li2, Jing Lin3
1School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China.
Ultrasonics
|November 23, 2025
概括
这项研究引入了一种新的框架,用于使用声辐射 (AE) 信号分解来分类复合结构损伤. 该方法准确地识别损伤模式,改善结构健康监测.
科学领域:
- 材料科学 材料科学 材料科学
- 结构健康监测 结构健康监测
- 声波辐射测试试验 声波辐射测试试验
背景情况:
- 多模式损坏合使复合结构中损坏的准确分类变得复杂.
- 由于信号干扰,现有的方法难以区分各种损坏类型.
研究的目的:
- 开发一个强大的损害分类框架,用于复合结构使用声辐射 (AE) 信号分解.
- 准确识别和量化不同损坏模式,即使多种损坏类型同时发生.
主要方法:
- 通过皮尔森相关性,主要组件分析和等级聚类来生成峰值频率规范化计数频谱.
- 为AE信号分析开发定制的波形包分解过器.
- 通过对粘合复合材料接头的拉力测试进行验证,并与K-means方法进行比较.
主要成果:
- 拟议的方法可以在三种损伤类型中实现一致的能量比例 (30%-40%).
- 粘合剂解接的正常化能量比率达到或超过了50%,表明高精度.
- 该框架有效地减轻了多模式损坏合的影响,性能优于K-means.
结论:
- 开发的框架更准确地反映了复合结构中真正的损伤状况.
- 这种方法为加强复合材料的健康监测提供了一个新的视角.
- 该方法处理损坏合的能力对于可靠的结构完整性评估至关重要.
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