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Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction

机译:基于稀疏反演图像重建的肘部损伤识别技术

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摘要

Continuous monitoring for defects in oil and gas pipelines is important for leakage prevention. This paper proposes a new kind of pipe elbow damage identification technique, which consists of three processes. First, piezoelectric sensors evenly arranged along the circumference of the pipeline in the turn generated ultrasonic guided wave signals in the elbow. Then, the wavefront flight time at each grid node in the known sound field were computed using the fast-marching algorithm. Finally, an elbow wall thickness map reconstruction technique based on the sparse inversion method was proposed to identify elbow defects. Compared with the traditional elbow defect identification technology, this technology can not only detect the existence of the defect but also accurately locate the defect position.
机译:连续监测油气管道中的缺陷对于防止泄漏非常重要。提出了一种新的管道弯头损伤识别技术,它包括三个过程。首先,压电传感器沿管道的圆周均匀地布置,进而在弯头中产生超声导波信号。然后,使用快速前进算法计算已知声场中每个网格节点处的波前飞行时间。最后,提出了一种基于稀疏反演的弯管壁厚图重建技术,以识别弯管缺陷。与传统的肘部缺陷识别技术相比,该技术不仅可以检测出缺陷的存在,而且可以准确地定位缺陷的位置。

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