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首页> 外文期刊>Journal of Nondestructive Evaluation >Detectability of Crack Lengths from Acoustic Emissions Using Physics of Wave Propagation in Plate Structures
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Detectability of Crack Lengths from Acoustic Emissions Using Physics of Wave Propagation in Plate Structures

机译:使用波形结构中的波传播物理从声发射裂缝长度的可检测性

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摘要

This paper presents a study to understand the physical nature of fatigue crack growth as an acoustic emission source and detectability of the crack length form the recorded acoustic emission signal in plate structures. For most of the thin walled engineering structures, the acoustic emission detection through sensor network has been well established. However, the majority of the research is focused on prediction of the acoustic emission due to fatigue crack growth using stochastic methods. Where, stochastic models are used to predict the criticality of the damage. The scope of this research is to use predictive simulation method for acoustic emission signals and extract the damage related information from acoustic emission signals based on physics of material. This approach is in contrast with the traditional approach involving statistics of acoustic emissions and their relation with damage criticality. In this article, first, we present our approach to understand fatigue crack growth as source of acoustic emission using physics of guided wave propagation in FEM. Then, using this physical understanding, we present our investigation on detectability of crack lengths directly from crack-generated acoustic emission signals. Finally, we present our method to extract fatigue crack length information from acoustic emission signals recorded during fatigue crack growth.
机译:本文介绍了理解疲劳裂纹生长的物理性质作为声发射源的物理性质,并且裂缝长度的可检测性形成板结构的记录声发射信号。对于大多数薄壁工程结构,通过传感器网络的声学排放检测已经很好地建立了很好。然而,大多数研究的重点是使用随机方法引起的疲劳裂纹生长引起的声发射的预测。在哪里,随机模型用于预测损坏的临界性。该研究的范围是利用用于声发射信号的预测模拟方法,并根据材料物理从声发射信号中提取损坏相关信息。这种方法与涉及声排放统计及其与伤害临界关系的传统方法形成鲜明对比。在本文中,首先,我们介绍了我们使用FEM中的引导波传播物理学的疲劳裂缝增长作为声发射的源。然后,使用这种物理理解,我们向我们直接从裂缝产生的声发射信号展示了对裂缝长度的可检测性的研究。最后,我们介绍了从疲劳裂纹生长期间记录的声发射信号提取疲劳裂缝长度信息的方法。

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