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Non-destructive damage detection for steel pipe scaffolds using MFL-based 3D defect visualization
Journal of Civil Structural Health Monitoring ( IF 4.4 ) Pub Date : 2023-11-23 , DOI: 10.1007/s13349-023-00726-0
Fitsum Emagnenehe Yigzew , Hansun Kim , Sebum Mun , Seunghee Park

Magnetic flux leakage (MFL) is a commonly used non-destructive technique for diagnosing defects in steel structures. In this study, we investigate a magnetic flux leakage (MFL)-based 3D visualization approach for identifying metal loss defects and evaluating their severity, which is a major concern in various industry fields where the structural integrity of specimens is crucial. We focus specifically on small-dimensional steel pipelines and steel pipe scaffolds as target specimens, which require a consistent inspection system to maintain their healthy performance for their intended purposes. When a magnetic field encounters a small air gap created by a defect, it spreads out because the air cannot support as much magnetic field per unit volume as a magnet can. We detect and measure the MFL signal that leaks due to the metal loss using a sensor head prototype containing hall sensors, which is used to scan the steel pipeline. The measured MFL signals are used to investigate abnormalities in the targeted pipeline specimen. Once the MFL signal is collected and measured, a series of digital signal processing steps are performed to enhance the resolution and extent of the defect level. This study proposes a 3D visualization of the defect profile based on the time domain MFL data, which provides insights into how the defect occurs on the target specimen and the general location of the defect. This visualization approach offers an effective means of evaluating the severity of metal loss defects in steel structures and can help ensure the long-term structural integrity of these specimens.



中文翻译:

使用基于 MFL 的 3D 缺陷可视化对钢管脚手架进行无损损伤检测

漏磁 (MFL) 是诊断钢结构缺陷的常用非破坏性技术。在这项研究中,我们研究了一种基于漏磁 (MFL) 的 3D 可视化方法,用于识别金属损失缺陷并评估其严重程度,这是各个行业领域的主要关注点,其中样本的结构完整性至关重要。我们特别关注小尺寸钢管道和钢管脚手架作为目标样本,它们需要一致的检测系统以保持其健康性能以达到预期目的。当磁场遇到由缺陷产生的小气隙时,它会扩散,因为空气不能像磁铁一样支持每单位体积那么多的磁场。我们使用包含霍尔传感器的传感器头原型来检测和测量由于金属损失而泄漏的 MFL 信号,该传感器头原型用于扫描钢制管道。测量的 MFL 信号用于调查目标管道样本中的异常情况。一旦收集并测量了 MFL 信号,就会执行一系列数字信号处理步骤,以提高缺陷级别的分辨率和范围。本研究提出了基于时域 MFL 数据的缺陷轮廓的 3D 可视化,可深入了解缺陷如何在目标样本上发生以及缺陷的一般位置。这种可视化方法提供了一种评估钢结构中金属损失缺陷严重程度的有效方法,并有助于确保这些样本的长期结构完整性。

更新日期:2023-11-24
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