考虑无基线数据的区间分析小波损伤检测的不确定性

IF 3 Q2 ENGINEERING, CIVIL
Muyideen Abdulkareem, N. Bakhary, A. Ganiyu, O. Nathaniel, Taha M. Jassam, R. Al-Mansob
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引用次数: 2

摘要

研究人员已经证明了基于振动的损伤检测(VBDD)方法的有效性,以提供可靠的结果。然而,测量和建模数据中存在的不确定性阻碍了VBDD结果的准确性。综合概率方法的研究取得了良好的结果。尽管取得了这些成功,概率方法仍然面临着获得不确定性的无偏概率分布的问题。此外,概率方法涉及漫长而复杂的计算。在处理这些问题时,提出了不需要对不确定性分布进行假设的非概率方法。它只涉及估计不确定参数的上界和下界。然而,非概率方法的成功因其对现有结构通常无法获得的基线(未损坏)数据的依赖而缩短。在本研究中,提出了一种在不使用基线健康数据的情况下考虑损伤识别不确定性的非概率区间分析小波(NIAW)方法。通过使用板结构并应用板结构的对称特性来证明所提出的方法。沿着对称线对板模形状的小波系数进行划分,以获得小波系数WL和WR,并估计WL和WR。利用WL和WR的边界估计PoDE和小波系数增量因子(WCIF)以获得损伤识别。PoDE和WCIF的乘积提供了DMI的值,DMI表示损坏严重程度。使用钢板的数值模型演示了这种方法。结果表明,当应用噪声污染的振型数据时,该方法能够准确识别损伤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consideration of uncertainty in damage detection using interval analysis wavelet without baseline data
ABSTRACT The effectiveness of vibration-based damage detection (VBDD) method has been demonstrated by researchers to provide reliable results. However, the existence of uncertainties in measurement and modelling data hinders the accuracy of results obtained from VBDD. Researches have yielded favourable results by integrating probabilistic method. Despite these successes, the probabilistic method faces the problem of obtaining an unbiased probabilistic distribution of uncertainties. Furthermore, the probabilistic method involves long and complex computations. In dealing with these problems, the nonprobabilistic method that requires no assumptions of the uncertainties distribution was proposed. It involves estimating only the upper and lower bounds of the uncertain parameter. However, the success of the nonprobabilistic method is shortened by its reliance on baseline (undamaged) data that is often not available for existing structures. In this study, a nonprobabilistic interval analysis wavelet (NIAW) method to consider uncertainties in damage identification without using baseline healthy data is proposed. The proposed method is demonstrated by using a plate structure and applying the symmetrical properties of the plate structure. The wavelet coefficient of the plate mode shape is divided along the line of symmetry to obtain wavelet coefficients WL and WR , and the bounds (upper and lower) of WL and WR are estimated. The PoDE and wavelet coefficient increment factor (WCIF) are estimated to obtain damage identity by using the bounds of WL and WR . The product of PoDE and WCIF provides the value of DMI which indicates the level of damage severity. This method is demonstrated using numerical models of a steel plate. The results show that the proposed method accurately identifies damage when noise-contaminated mode shape data is applied.
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来源期刊
CiteScore
3.90
自引率
9.50%
发文量
24
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