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Vibration-based Structural Damage Identification under Interval Uncertainty

机译:间隔不确定性下基于振动的结构损伤识别

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Identifying damages in mechanical structures in advance is essential part of preventing catastrophic losses. Among several non-destructive methods, the vibration-based method, which utilizes global characteristics of the structures, has several advantages such as not requiring prior information on possible damage location and physical access to it. In the meantime, the mechanical structures are inevitably subject to uncertainties, whose distribution is often unknown in practical situations due to such as limited amount of available data. Uncertainties are treated as interval uncertainty in such cases. In this regard, this study presents vibration-based damage identification under interval uncertainty. To obtain reliable result, this research does not assume any random distribution, e.g., uniform distribution, inside interval. Since detected damage is not assumed to be monotonic function with respect to interval uncertainty either, traditional fuzzy interval arithmetic is not applicable. Instead, we first carry out exhaustive search to see the effect of the interval uncertainty on the identified damage; i.e., discretizing interval uncertainty into sub-intervals and executing damage identification under all possible combinations to see the effect of the interval uncertainty on the identified damage. We then develop the unique algorithm based on M-H algorithm to facility computational efficiency.
机译:预先确定机械结构中的损坏是防止灾难性损失的重要组成部分。在几种非破坏性方法中,利用结构的全局特性的基于振动的方法具有若干优点,例如不需要先前的信息可​​能损坏位置和物理访问。同时,机械结构不可避免地受到不确定性的影响,其分布在实际情况下通常是未知的,这是由于诸如有限的可用数据量的实际情况。在这种情况下,不确定因素被视为间隔不确定性。在这方面,该研究在间隔不确定性下提出了基于振动的损伤识别。为了获得可靠的结果,该研究不假设任何随机分布,例如,均匀分布,内部间隔。由于未假定检测到的损坏是相对于间隔功能的单调功能,因此传统的模糊间隔算法不适用。相反,我们首先进行详尽的搜索,以便看到间隔不确定性对所识别的损坏的影响;即,将间隔的间隔不确定性离散化并在所有可能的组合下执行损坏识别,以便在确定的损害中看到间隔不确定性的影响。然后,我们基于M-H算法开发独特的算法,以设施计算效率。

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