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Condition Assessment of Foundation Piles and Utility Poles Based on Guided Wave Propagation Using a Network of Tactile Transducers and Support Vector Machines

机译:基于触觉换能器和支持向量机网络的导波传播的基桩和公用立柱状态评估

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摘要

This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced), and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM) classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%.
机译:本文提出了一种使用触觉传感器和加速度计网络的新型无损测试和健康监测系统,用于基础桩和电线杆的状态评估和损伤分类。在传统的桩身完整性测试中,通常使用具有宽带频率激励的冲击锤,而提出的测试系统则利用基于触觉换能器网络的创新激励系统来感应受控的窄带频率应力波。因此,避免了(或至少减少了)多种应力波类型和模式的同时激励,并且可以生成目标波形。新的测试系统可以在无法到达顶部的基础桩和电线杆中进行测试和监视,从而使新的测试系统适用于例如带头部受阻的桩结构和带火线的杆的状态评估。为了进行系统验证,新系统在9种木材和混凝土杆上进行了实验测试,这些杆遭受了几种类型的损坏。触觉换能器被频率为1 kHz的连续正弦波信号激励。支持向量机与先进的信号处理算法一起使用,以区分记录的应力波信号与具有不同类型损坏的杆结构。结果表明,使用快速傅立叶变换信号并结合主成分分析作为具有不同核函数的支持向量机(SVM)分类器的输入特征向量,可以实现损伤分类,准确度为92.5%±7.5%。

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