Application of compressed sensing in the guided wave structural health monitoring of switch rails
Application of compressed sensing in the guided wave structural health monitoring of switch rails
复制标题
压缩感知在尖轨导波结构健康监测中的应用
DOI：
10.1088/1361-6501/ac2316
复制
发表时间：
2021
影响因子：
2.4
通讯作者：
Chen Xiangxian
中科院分区：
文献类型：
--
作者：
Tang Zhifeng;Liu Weixu;Yan Rui;Zhang Pengfei;Lv Fuzai;Chen Xiangxian
道岔钢轨是高铁系统的薄弱但必不可少的组成部分。在高铁状态检修中，超声导波在线监测技术被广泛应用于实时判断运行状态，但其产生的数据量往往很大。太多的数据带来了巨大的挑战，如在道岔结构健康监测中存在太多不必要的能量、存储和网络带宽成本，这使得实现高耐用性和低功耗的嵌入式传感器网络具有挑战性。此外，从长期来看，结构损伤发生的次数相对较少，这表明这些测量天生就是稀疏的。结构损伤的稀疏性使其对压缩传感技术具有吸引力。本研究提出了一种新颖的数据压缩和重建方法，以应对挑战，减少传感器网络传输的数据量，同时保持其准确性。首先，根据UGW信号的传播特点，构造轻量级数据字典对UGW信号进行稀疏分解。其次，针对UGW信号的亚奈奎斯特采样和压缩，设计了一种基于稀疏随机矩阵的有效采样方法。第三，提出了一种新的块自适应匹配跟踪算法，用于从压缩数据中重建UGW信号。最后，通过数值信号、有限元仿真和道岔轨下的实际监测实验，验证了该方法的有效性和准确性。研究了不同压缩比和块大小对导波信号重构性能的影响。结果表明，该方法能够以比奈奎斯特采样定理低得多的要求对UGW信号进行采样，并且优于其他新的算法。
Switch rails are weak but essential components of high-speed rail (HSR) systems. In the condition-based maintenance of HSR, ultrasonic guided wave (UGW) on-line monitoring technology is widely used in judging real-time operating conditions; however, it always generates large amounts of data. Too much data bring significant challenges, such as too many unnecessary costs of energy, storage, and network bandwidth in the structural health monitoring of switch rails, making it challenging to realize embedded sensor networks with high durability and low power consumption. Furthermore, the structural damage occurs relatively less over the long-term, indicating that these measurements are inherently sparse. The sparseness of structural damage makes them attractive for the compressed sensing technique. This study proposes a novel data compression and reconstruction method to meet the challenges and reduce the amount of data transmitted by sensor networks and maintain their accuracies simultaneously. First, a lightweight data dictionary is constructed to perform a sparse decomposition of UGW signals according to the characteristics of UGW propagation. Second, an effective sampling method based on a sparse random matrix is designed for sub-Nyquist sampling and compressing UGW signals. Third, a novel block adaptive matching pursuing algorithm is proposed to reconstruct UGW signals from compressed data. Finally, numerical signals, finite element simulation, and several actual monitoring experiments on the foot of a switch rail are conducted to verify the effectiveness and accuracy of the proposed method. The influence of different compression ratios and block sizes on the reconstruction performance of guided wave signals is investigated. The results indicate that the proposed method can sample UGW signals with much lower requirements than the Nyquist sampling theorem and is superior to other novel algorithms.
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DOI：
10.1017/cbo9780511794308
发表时间：
2012
期刊：
--
影响因子：
--
作者：
Gitta Kutyniok
通讯作者：
Gitta Kutyniok
DOI：
10.1117/12.2048276
发表时间：
2014-03
期刊：
--
影响因子：
--
作者：
Z. Duan;Jie Kang
通讯作者：
Z. Duan;Jie Kang
DOI：
10.1016/j.dsp.2015.04.001
发表时间：
2015-07
期刊：
Digit. Signal Process.
影响因子：
--
作者：
A. Perelli;L. Marchi;L. Flamigni;A. Marzani;G. Masetti
通讯作者：
A. Perelli;L. Marchi;L. Flamigni;A. Marzani;G. Masetti
DOI：
--
发表时间：
2018
期刊：
--
影响因子：
--
作者：
Si-Xin Chen;Yi-Qing Ni
通讯作者：
Si-Xin Chen;Yi-Qing Ni
影响因子：
4.7
作者：
Rizzo, Piervincenzo;Sorrivi, Elisa;Viola, Erasmo
通讯作者：
Viola, Erasmo