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Applying Concepts of Complexity to Structural Health Monitoring

机译:应用复杂性概念对结构健康监测

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The process of implementing a damage detection strategy for aerospace, civil, and mechanical engineering infrastructure is referred to as structural health monitoring (SHM). The SHM method complements traditional nondestructive evaluation by extending these concepts to online, in situ, system monitoring on a more global scale. For long term SHM, the output is periodically updated information that provides details on the continual deterioration of a system. After severe events, SHM is used for short term rapid condition screening and aims to provide reliable, near real-time information on structural integrity. The hypothesis of this paper is that structural degradation increases the complexity of a system, and that SHM can be used to detect this change over both long and short-term periods. Various measures of complexity were investigated, including Shannon and spectral entropies of accelerometer readings for real time damage detection and gradient measures for image-based corrosion detection. It was concluded that different measures of complexity were more appropriate for varying types of damage, i.e. spectral entropy was more appropriate for identifying cracks in a structure, while Shannon entropy was more appropriate for identifying corrosion on a plate.
机译:实施航空航天,民用和机械工程基础设施损坏检测策略的过程被称为结构健康监测(SHM)。 SHM方法通过将这些概念扩展到在线,原位,对更全球范围内的系统监控来补充传统的非破坏性评估。对于长期SHM,输出是周期性更新的信息,提供有关系统持续恶化的详细信息。严重事件后,SHM用于短期快速条件筛选,并旨在提供可靠的,近实时信息有关结构完整性的实时信息。本文的假设是结构降解增加了系统的复杂性,并且SHM可用于检测长期短期和短期期间的这种变化。研究了各种复杂度,包括Shannon和加速度计读数的谱熵,用于实时损伤检测和基于图像腐蚀检测的梯度措施。得出结论,不同的复杂度对于不同类型的损伤,即频谱熵更适合于识别结构中的裂缝,而香农熵更适合识别板上的腐蚀。

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