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Structural Health Monitoring in composites based on probabilistic reconstruction techniques

机译:基于概率重建技术的复合材料结构健康监测

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Structural Health Monitoring (SHM) based on guided waves (GWs) is responsive to damage occurrences allowing the assessment of composites integrity. However, online monitoring is quite complex due to a wide range of parameters affecting wave propagation and consequently diagnostic outputs. A useful implementation of a GW-based condition monitoring requires an accurate analysis of reconstruction algorithm and collected data as well. In view of a more effective detection of impact induced damages in composites using a sparse array of sensors, several methods are explored in this paper as a first step towards a comprehensive capability assessment of a system permanently installed on aircraft structures. Various probabilistic reconstruction methods and signal transformation techniques are developed and used to detect hidden flaws with a multiple analysis. From a wide number of simulation carried out it appears that, although a single procedure for the estimation of the structural health is a fast solution for flaw detection, a multiple analysis based on different reconstruction techniques and/or several damage parameters could provide more detailed information about the location and the severity of possible failures if the parameters affecting diagnostics are completely addressed.
机译:基于导波结构健康监测(SHM)(GW的)响应损伤发生允许的复合材料的完整性进行评估。然而,在线监测是相当复杂的,由于广泛的影响波的传播,因此诊断输出参数。基于GW-状态监测的有用实施需要重建算法和收集的数据以及准确分析。鉴于使用传感器的稀疏数组的复合材料更有效地检测冲击引起的损害的,几种方法在本文中探索作为朝向上飞机结构永久性地安装的系统的综合能力评估的第一步。各种概率重建方法和信号转化技术被开发并用于检测与多分析隐藏缺陷。从广泛的数目进行仿真的看来,尽管对于结构健康的估计单个过程为探伤,基于不同的重建技术和/或多个损坏的参数的多种分析可以提供更详细的信息的快速的解决方案有关的位置和可能故障的严重程度,如果影响诊断参数完全解决。

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