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Signal processing techniques for IoT-based structural health monitoring

机译:用于基于IoT的结构健康监控的信号处理技术

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With the advancement of modern technology, structures like buildings, bridges, etc. are getting structurally complicated, and safety has become an issue. Structural Health Monitoring (SHM) with Internet of Things (IoT) can help improving security and safety. However, efficient signal processing for IoT is a challenge. In this paper, a signal processing based SHM is proposed where a simple Butterworth filter was used to remove noises. Cross-Correlation was used for damage detection. If there was any damage found, using a mathematical model, damage size and location were determined. After analyzing the experimental data, error found in damage localization is 2.9% and error in determining damage size is 3.344%. Since the whole algorithm does not associate with complex mathematical calculations, this system can be used for low-cost distributed system for SHM.
机译:随着现代技术的进步,诸如建筑物,桥梁等的结构在结构上变得复杂,并且安全性已经成为问题。带有物联网(IoT)的结构健康监控(SHM)可以帮助改善安全性。但是,物联网的高效信号处理是一个挑战。在本文中,提出了一种基于信号处理的SHM,其中使用了简单的Butterworth滤波器来去除噪声。互相关用于损坏检测。如果发现任何损坏,则使用数学模型确定损坏的大小和位置。分析实验数据后,在损伤定位中发现的误差为2.9%,在确定损伤尺寸时的误差为3.344%。由于整个算法不涉及复杂的数学计算,因此该系统可用于SHM的低成本分布式系统。

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