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使用导波评估复合材料压力容器的损伤。

Assessment of Damage in Composite Pressure Vessels Using Guided Waves.

机构信息

Department of Industrial Engineering, University of Naples "Federico II", Via Claudio 21, 80125 Naples, Italy.

出版信息

Sensors (Basel). 2022 Jul 11;22(14):5182. doi: 10.3390/s22145182.

Abstract

This paper deals with guided wave-based structural health monitoring of composite overwrapped pressure vessels adopted for space application. Indeed, they are well suited for this scope thanks to their improved performance compared with metallic tanks. However, they are characterized by a complex damage mechanics and suffer from impact induced damage, e.g., due to space debris. After reviewing the limited progress in this specific application, the paper thoroughly covers all the steps needed to design and verify guided wave structural health monitoring system, including methodology, digital modelling, reliability, and noise estimation for a correct decision-making process in a virtual environment. In particular, propagation characteristics of the fundamental anti-symmetric mode are derived experimentally on a real specimen to validate a variety of finite element models useful to investigate wave interaction with damage. Different signal processing techniques are demonstrated sensitive to defect and linearly dependent upon damage severity, showing promising reliability. Those features can be implemented in a probability-based diagnostic imaging in order to detect and localized impact induce damage. A multi-parameter approach is achieved by metrics fusion demonstrating increased capability in damage detection with promising implication in enhancing probability of detection.

摘要

本文针对用于空间应用的复合材料缠绕压力容器的导波结构健康监测进行了研究。事实上,与金属罐相比,它们具有更好的性能,非常适合这一领域。然而,它们的损伤力学比较复杂,并且容易受到冲击损伤的影响,例如,由于空间碎片。在回顾了这一特定应用中的有限进展之后,本文全面涵盖了设计和验证导波结构健康监测系统所需的所有步骤,包括方法学、数字建模、可靠性和噪声估计,以便在虚拟环境中进行正确的决策过程。特别是,在真实试件上实验推导了基本反对称模态的传播特性,验证了各种有限元模型,这些模型可用于研究波与损伤的相互作用。不同的信号处理技术被证明对缺陷敏感,并且与损伤严重程度呈线性关系,显示出可靠的性能。这些特性可以在基于概率的诊断成像中实现,以便检测和定位冲击引起的损伤。通过指标融合实现了多参数方法,证明了在损伤检测方面具有更高的能力,对提高检测概率具有很好的应用前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e03b/9322626/13eafb19414f/sensors-22-05182-g001.jpg

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