Dackermann Ulrike, Yu Yang, Niederleithinger Ernst, Li Jianchun, Wiggenhauser Herbert
Centre for Infrastructure Engineering and Safety, School of Civil and Environmental Engineering, Faculty of Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia.
Centre for Built Infrastructure Research, School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW 2007, Australia.
Sensors (Basel). 2017 Dec 18;17(12):2938. doi: 10.3390/s17122938.
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%.
本文提出了一种新型的无损检测与健康监测系统，该系统使用触觉传感器和加速度计网络对基桩和电线杆的状况进行评估及损伤分类。在传统的桩身完整性检测中，通常使用具有宽带频率激励的冲击锤，而本文所提出的检测系统利用基于触觉传感器网络的创新激励系统来诱发可控的窄带频率应力波。由此，避免了（或至少减少了）多种应力波类型和模式的同时激励，并且能够生成目标波形。这种新型检测系统能够对顶部无法接近的基桩和电线杆进行检测与监测，例如适用于对头部受阻的桩结构以及带电电线的电线杆进行状况评估。为了验证系统，在九根遭受了几种类型损伤的木材和混凝土电线杆上对新系统进行了实验测试。触觉传感器由频率为1kHz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用于区分来自具有不同类型损伤的电线杆结构的记录应力波信号。结果表明，使用快速傅里叶变换信号，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，能够实现准确率为92.5%±7.5%的损伤分类。
