...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Mechanical systems and signal processing >An energy-based sparse representation of ultrasonic guided-waves for online damage detection of pipelines under varying environmental and operational conditions
【24h】

An energy-based sparse representation of ultrasonic guided-waves for online damage detection of pipelines under varying environmental and operational conditions

机译：超声导波的基于能量的稀疏表示，用于在变化的环境和操作条件下对管道进行在线损伤检测

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This work addresses the main challenges in real-world application of guided-waves for damage detection of pipelines, namely their complex nature and sensitivity to environmental and operational conditions (EOCs). Different propagation characteristics of the wave modes, their distinctive sensitivities to different types and ranges of EOCs, and to different damage scenarios, make the interpretation of diffuse-field guided-wave signals a challenging task. This paper proposes an unsupervised feature-extraction method for online damage detection of pipelines under varying EOCs. The objective is to simplify diffuse-field guided-wave signals to a sparse subset of the arrivals that contains the majority of the energy carried by the signal. We show that such a subset is less affected by EOCs compared to the complete time-traces of the signals. Moreover, it is shown that the effects of damage on the energy of this subset suppress those of EOCs. A set of signals from the undamaged state of a pipe are used as reference records. The reference dataset is used to extract the aforementioned sparse representation. During the monitoring stage, the sparse subset representing the undamaged pipe, will not accurately reconstruct the energy of a signal from a damaged pipe. In other words, such a sparse representation of guided-waves is sensitive to occurrence of damage. Therefore, the energy estimation errors are used as damage-sensitive features for damage detection purposes. A diverse set of experimental analyses are conducted to verify the hypotheses of the proposed feature-extraction approach, and to validate the detection performance of the damage-sensitive features. The empirical validation of the proposed method includes (1) detecting a structural abnormality in an aluminum pipe, under varying temperature at different ranges, (2) detecting multiple small damages of different types, at different locations, in a steel pipe, under varying temperature, (3) detecting a structural abnormality in an operating hot-water piping system, under multiple varying EOCs, such as temperature, water flow rate, and inner pressure; and (4) detecting a structural abnormality as the ratio of the damaged pipe's signals in the reference dataset increases.
机译：这项工作解决了在实际应用中将导波用于管道损伤检测的主要挑战，即其复杂的性质以及对环境和操作条件（EOC）的敏感性。波模式的不同传播特性，其对不同类型和范围的EOC以及对不同破坏情况的独特敏感性，使得对扩散场导波信号的解释成为一项艰巨的任务。提出了一种在变化的EOCs下在线监测管道损伤的无监督特征提取方法。目的是将扩散场导波信号简化为到达的稀疏子集，其中包含信号所携带的大部分能量。我们表明，与信号的完整时间轨迹相比，此类子集受EOC的影响较小。此外，研究表明，损害对该子集能量的影响会抑制EOC的能量。来自管道未损坏状态的一组信号用作参考记录。参考数据集用于提取上述稀疏表示。在监视阶段，代表未损坏管道的稀疏子集将无法准确地重建来自受损管道的信号能量。换句话说，导波的这种稀疏表示对损坏的发生很敏感。因此，能量估计误差被用作损伤敏感特征以用于损伤检测目的。进行了各种各样的实验分析，以验证提出的特征提取方法的假设，并验证损伤敏感特征的检测性能。所提方法的经验验证包括：（1）在不同温度下，在不同范围内检测铝管中的结构异常；（2）在不同温度下，在钢管中的不同位置，检测不同类型的多个小损伤，（3）在多个变化的EOC（例如温度，水流量和内部压力）下检测热水管道系统中的结构异常； （4）随着参考数据集中破损管道信号比例的增加，检测结构异常。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号