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Sparse estimation based monitoring method for damage detection and localization: A case of study

机译：基于稀疏估计的损伤检测与定位监测方法

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摘要

This paper suggests a Structural Health Monitoring (SHM) method for damage detection and localization in pipeline. The baseline signals, used in SHM, could change due to the variation of environmental and operational conditions (EOCs). Hence, the damage detection method could give rise to false alarm. In this study, this issue is addressed by estimating the current signal using only few reference signals with similar or very close EOCs. Such an operation can be performed by calculating a sparse estimation of the current signal. The estimation error is used as an indication of the presence of damage. Actually, a signal from the damaged pipe will be characterized by a high estimation error compared to that of a signal from the undamaged pipe. The damage location is obtained by calculating the estimation error on a sliding window over the signal from the damaged pipe. This method was tested on signals collected on a 6 m pipeline segment placed in a workshop under natural temperature variations. Results have shown that the created damage was successfully detected and localized.
机译：本文提出了一种结构健康监测（SHM）方法，用于管道中的损伤检测和定位。 SHM中使用的基线信号可能会由于环境和操作条件（EOC）的变化而发生变化。因此，损坏检测方法会引起误报。在这项研究中，通过仅使用很少的具有相似或非常接近的EOC的参考信号来估计电流信号来解决此问题。可以通过计算当前信号的稀疏估计来执行这种操作。估计误差用作损坏存在的指示。实际上，与来自未损坏管道的信号相比，来自损坏管道的信号将具有较高的估计误差。通过计算来自损坏管道的信号的滑动窗口上的估计误差，可以获取损坏位置。在自然温度变化的情况下，该方法在放置于车间的6毫米管道段上采集的信号上进行了测试。结果表明，已成功检测到并确定了造成的损坏。

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