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Performance Degradation Assessment of Concrete Beams Based on Acoustic Emission Burst Features and Mahalanobis—Taguchi System

机译:基于声发射爆发特征和Mahalanobis-Taguchi系统的混凝土梁性能退化评估

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摘要

Acoustic emission (AE) has been used extensively for structural health monitoring based on the stress waves generated due to evolution of cracks in concrete structures. A major concern while using AE features is that each of them responds differently to the fractures in concrete structures. To tackle this problem, Mahalanobis—Taguchi system (MTS) is utilized, which fuses the AE feature space to provide comprehensive and reliable degradation indicator with a feature selection method to determine useful features. Further, majority of the existing investigations gave little attention to naturally occurring cracks, which are actually more difficult to detect. In this study, a novel degradation indicator (DI) based on AE features and MTS is proposed to indicate the performance degradation in reinforced concrete beams. The experimental results confirm that the MTS can successfully distinguish between healthy and faulty conditions. To alleviate the noise from the DI obtained through MTS, a noise-removal strategy based on Chebyshev inequality is suggested. The results show that the proposed DI based on AE features and MTS is capable of detecting early stage cracks as well as development of damage in concrete beams.
机译:基于混凝土结构中裂缝产生的应力波,声发射(AE)已广泛用于结构健康监测。使用AE功能时,一个主要问题是它们对混凝土结构中的裂缝的反应不同。为了解决这个问题,使用了Mahalanobis-Taguchi系统(MTS),该系统融合了AE特征空间,以提供综合可靠的性能指标,并通过一种特征选择方法来确定有用的特征。此外,大多数现有研究很少关注自然发生的裂缝,而实际上很难发现。在这项研究中,提出了一种基于AE特征和MTS的新型劣化指标(DI),以指示钢筋混凝土梁的性能劣化。实验结果证实,MTS可以成功地区分健康状况和错误状况。为了减轻通过MTS获得的DI产生的噪声,提出了一种基于Chebyshev不等式的噪声去除策略。结果表明,所提出的基于AE特征和MTS的DI能够检测早期裂缝以及混凝土梁损伤的发展。

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