Compressed Sensing in Material Diagnostics via Ultrasound Imaging (CoSMaDU)

通过超声成像进行材料诊断的压缩传感 (CoSMaDU)

• 批准号: 421389590
• 负责人: Professor Dr.-Ing. Giovanni del Galdo
• 金额: --
• 依托单位: Fachgebiet Drahtlose Verteilsysteme / Digitaler Rundfunk (DVT)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/421389590?language=en
• 关键词: Compressed; Sensing; Material; Diagnostics; via

Non-destructive testing (NDT) is a core tool to ensure the absence of critical flaws in fabrication and enable maintenance of large infrastructure such as railroad tracks. With growing demands in both areas, the importance of fast and reliable NDT techniques has increased aiming at examining a component throughout its entire life.Ultrasound is, due to its simple and safe applicability, one of the most established NDT techniques. However, so far ultrasound testing is performed mostly on a qualitative basis (i.e., is a specimen is flawed or not). The quantitative assessment of defects is in fact limited, since the exact interpretation of ultrasound data is difficult. Due to the complex nature of ultrasonic wave propagation, the acquired data can be highly ambiguous which necessitates a large amount of a priori knowledge on the component or structure under test and the measurement setup to allow for a reliable interpretation.To facilitate this, appropriate post-processing becomes indispensable. Notwithstanding, the post-processing methods currently used in commercial ultrasound NDT products are quite rudimentary or are used only together with the inspection of the raw data in a complementary fashion for lack of reliability. The main reason advanced signal processing techniques have not been applied is the lack of appropriate forward models that account for the complexity of the ultrasonic wave propagation and yet are still suitable for signal processing applications. The proposed project aims at improving the state-of-the-art by pursuing two goals: The first objective is to investigate forward models for ultrasonic wave propagation with the goal to find the best compromise between the realistic modeling of physical propagation effects such as dispersion, acoustic shadowing and speckle noise on the one hand and the suitability for signal processing methods in terms of the model complexity on the other hand. Our investigations will consider the measurement setup and the post-processing stage jointly. Based on this, the second objective of this project is to design measurement architectures that capture relevant (for post-processing) information efficiently. To achieve this, the state-of-the-art in sub-Nyquist-Sampling techniques such as Compressed Sensing or Finite Rate of Innovation Sampling will be applied to ultrasonic NDT. In particular, our proposal aims at closing the gap between novel theoretical results (that usually rely on idealized algebraic formulations) and the physics of ultrasonic wave propagation to make these results applicable to real setups.

无损检测（NDT）是确保制造过程中不存在关键缺陷并维护铁路轨道等大型基础设施的核心工具。随着这两个领域的需求不断增长，快速可靠的无损检测技术的重要性也在不断增加，旨在在整个寿命周期内对部件进行检查。超声波由于其简单和安全的适用性，是最成熟的无损检测技术之一。然而，到目前为止，超声测试主要是在定性的基础上执行的（即，是标本有缺陷还是没有）。缺陷的定量评估实际上是有限的，因为超声数据的准确解释是困难的。由于超声波传播的复杂性，所采集的数据可能非常模糊，因此需要对被测部件或结构以及测量设置进行大量的先验知识，以便进行可靠的解释。为了促进这一点，适当的后处理变得不可或缺。尽管如此，目前在商业超声无损检测产品中使用的后处理方法是相当初级的，或者由于缺乏可靠性而仅以互补的方式与原始数据的检查一起使用。高级信号处理技术尚未应用的主要原因是缺乏适当的前向模型，该模型考虑了超声波传播的复杂性，但仍然适合于信号处理应用。拟议的项目旨在通过追求两个目标来改善最先进的技术：第一个目标是研究超声波传播的前向模型，目标是找到物理传播效应（如色散，声学阴影和斑点噪声）的现实建模与信号处理方法在模型复杂性方面的适用性之间的最佳折衷。我们的调查将同时考虑测量设置和后处理阶段。在此基础上，本项目的第二个目标是设计有效捕获相关（后处理）信息的测量架构。为了实现这一点，最先进的亚奈奎斯特采样技术，如压缩传感或有限创新率采样将应用于超声无损检测。特别是，我们的建议旨在关闭新的理论结果（通常依赖于理想化的代数公式）和超声波传播的物理之间的差距，使这些结果适用于真实的设置。