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首页> 外文期刊>Journal of intelligent material systems and structures >Validation and evaluation of damage identification using probability-based diagnostic imaging on a stiffened composite panel
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Validation and evaluation of damage identification using probability-based diagnostic imaging on a stiffened composite panel

机译：在加固的复合板上使用基于概率的诊断成像对损伤识别进行验证和评估

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摘要

Probability-based diagnostic imaging, as one of the damage identification methods using ultrasonic guided waves, has been attracting increasing attention by researchers in the community of structural health monitoring. However, the probability-based diagnostic imaging algorithm's influencing parameters, including the selection of certain damage index and frequency, the network of sensing paths, and the size of the effective elliptical distribution area, are empirically determined. This experience dependency limits the application of the method to identify damages in real-world practices. Therefore, it is important to clarify the influences of the above-mentioned various factors on the damage identification. However, the complexity of these factors makes it almost impossible to interpret the influencing mechanisms directly. Thus, a fusion image approach of multiple frequencies is employed to eliminate the influence of different frequencies, while a histogram-based method is proposed to evaluate the reliability of the fusion result. Meanwhile, a unit weight distribution function, considering both the network of sensing paths and the size of the effective elliptical distribution area, is presented in the analysis. Then, the influencing mechanisms are studied and discussed in detail, and a methodology is proposed to optimize the network and the scaling parameter which controls the affected zone.
机译：基于概率的诊断成像作为使用超声波导波的损伤识别方法之一，在结构健康监测领域引起了研究人员的越来越多的关注。但是，凭经验确定了基于概率的诊断成像算法的影响参数，包括某些损伤指数和频率的选择，传感路径的网络以及有效椭圆分布区域的大小。这种经验依赖性限制了该方法在实际操作中识别损害的方法的应用。因此，重要的是弄清上述各种因素对损伤识别的影响。但是，这些因素的复杂性使得几乎不可能直接解释影响机制。因此，采用多频率的融合图像方法来消除不同频率的影响，同时提出了一种基于直方图的方法来评估融合结果的可靠性。同时，分析中提出了既考虑传感路径网络又考虑有效椭圆分布区域大小的单位重量分布函数。然后，详细研究和讨论了影响机制，并提出了一种方法来优化控制受影响区域的网络和缩放参数。

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