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Integrated Non-destructive Testing Approach for Damage Detection and Quantification in Structural Components

机译:综合无损检测方法,用于结构部件的损伤检测和定量

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Reliable damage detection and quantification is a difficult process because of its dynamic and multi-scale nature, which combined with material complexities and countless other sources of uncertainty often inhibits a single non-destructive testing (NDT) technique to successfully evaluate the extension of deterioration in critical structural components. This paper presents an integrated non-destructive testing approach (INDT) for effective damage identification relying on the intelligent integration of the Acoustic Emission (AE), Guided Ultrasonic Waves (GUW) and Digital Image Correlation (DIC) methods. The proposed system has been utilized to identify wire breaks in seven-wire steel strands and crack initiation and development in masonry concrete walls and is based on the cross-correlation of heterogeneous damage-related NDT features. Conventional AE monitoring relies on damage monitoring by evaluating multiple extracted and/or computed features as a function of load/time. In addition, advanced post-processing methods including mathematical algorithms for statistical analysis and classification have been suggested to improve the robustness of AE in damage identification. Unfortunately, such approaches are often found to be unsuccessful, due to challenging environmental and operational conditions, as well as when used on actual civil structural components, such as bridge cables and masonry walls. This paper presents the framework for successful correlation of AE features with GUW and mechanical parameters such as full field strain maps, which can provide a route towards actual cross-validated damage assessment, capable to detect the initiation and track the development of damage in structures. The presented INDT approach could lead to reliable damage identification approaches in mechanical, aerospace and civil infrastructure applications.
机译:可靠的损坏检测和量化是一种难度的过程,因为它的动态和多尺度性质,其与材料复杂性相结合,无数的其他不确定性源通常抑制单一的无损检测(NDT)技术来成功评估劣化的延伸临界结构组件。本文提出了一种集成的非破坏性测试方法(INDT),用于依赖于声发射(AE),引导超声波(GUW)和数字图像相关(DIC)方法的智能集成的有效损坏识别。所提出的系统已被利用来识别七线钢绞线和砌体混凝土墙壁的裂纹启动和发育的焊丝,并且基于异质损伤相关的NDT特征的互相关。传统的AE监测通过评估作为负载/时间的函数来评估多个提取的和/或计算的特征来依赖于损坏监测。此外,已经提出了包括用于统计分析和分类的数学算法的先进后处理方法,以改善损害识别中AE的稳健性。不幸的是,由于挑战环境和运营条件,以及在实际的民用结构部件(如桥电缆和砌体墙上)的情况下,这种方法通常被发现不成功。本文介绍了AE功能与GUW和机械参数成功相关的框架,如全场应变映射,可以为实际交叉验证损伤评估提供途径,能够检测到启动并跟踪结构损坏的发展。所呈现的INDT方法可能导致机械,航空航天和民用基础设施应用中可靠的损坏识别方法。

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