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Structural health monitoring using sparse distributed networks of guided wave sensors

机译:使用引导波传感器稀疏分布式网络的结构健康监测

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The motivation for using guided acoustic waves as the sensing mechanism for large area structural health monitoring (SHM) is explained and the logic for using baseline signal subtraction as the fundamental signal processing tool is presented. In the first part of this paper, a simple experimental example is presented to illustrate how a guided wave SHM using baseline subtraction could be used to detect and locate simulated damage in a 1 m by 1.5 m by 3 mm thick aluminum plate. The experiment shows for an SHM system to be useful it must have a coherent noise floor around 40 dB lower in amplitude that the amplitude of a signal reflected from the edge of the structure. The experiment demonstrates that the sensitivity is severely limited by the stability of the baseline subtraction procedure which deteriorates rapidly over time. In the second part of the paper, the factors affecting the stability of the reference signal subtraction approach are investigated. Experimental and modeling studies on a simple test structure are presented that show that a change in temperature of a few degrees leads to coherent artifacts after baseline subtraction that are of a similar magnitude to the signals arising from defects. A possible strategy for overcoming this barrier to reliable baseline signal subtraction is then considered and shown to provide an improvement in sensitivity of around 10 dB.
机译:向使用引导声波作为大面积结构健康监测(SHM)的传感机制的动机,并且呈现了作为基本信号处理工具的基线信号减法的逻辑。在本文的第一部分中,提出了一个简单的实验例,以说明使用基线减法的引导波Shm如何使用3mm厚的铝板1米的1米中的模拟损坏。实验表明SHM系统是有用的,它必须具有相干噪声底板,其幅度幅度为40dB,幅度从结构的边缘反射的信号的幅度。该实验表明,灵敏度受到基线减法过程的稳定性的严重限制,随着时间的推移迅速降低。在本文的第二部分中,研究了影响参考信号减法方法稳定性的因素。提出了一种简单测试结构的实验和建模研究,表明,几度的温度变化导致基线减法后的相干伪像对由缺陷引起的信号具有类似的幅度。然后考虑并显示用于克服该可靠基线信号减法的可能策略,并显示出大约10dB的灵敏度的改善。

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