Independent Component Analysis for Improved Defect Detection in Guided Wave Monitoring
Independent Component Analysis for Improved Defect Detection in Guided Wave Monitoring
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DOI：
10.1109/jproc.2015.2451218
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发表时间：
2016-08-01
影响因子：
20.6
通讯作者：
Cawley, Peter
中科院分区：
文献类型：
--
作者：
Dobson, Jacob;Cawley, Peter
导波传感器广泛用于许多行业中，并且在石油和天然气行业中特别应用于管道工程的检查。传统上，这种类型的传感器用于一次性检查，但近年来，传感器的永久安装已经成为趋势。这使得同一段管道的读数具有高度可重复性，从而可能改进缺陷检测和分类。本文提出了一种新的方法，利用独立分量分析的重复导波信号分解成组成的独立分量。这将缺陷与由变化的环境条件引起的相干噪声分离，提高了可检测性。本文演示了独立分量分析应用于一系列工业检测场景中的导波信号。对管道回路的测试数据进行了分析，这些管道回路在未损坏和损坏状态下都经历了多次温度循环。除了处理来自实验损坏条件的数据外，模拟损坏信号已被添加到“未损坏”的实验数据中，因此可以研究多种不同的损坏情况。该算法也已被用来处理导波信号的有限元模拟的管道与分布的浅全面腐蚀，其中有一个补丁的严重腐蚀。在所有这些情况下，独立分量分析算法能够提取缺陷信号，排除相干噪声。
Guided wave sensors are widely used in a number of industries and have found particular application in the oil and gas industry for the inspection of pipework. Traditionally this type of sensor was used for one-off inspections, but in recent years there has been a move towards permanent installation of the sensor. This has enabled highly repeatable readings of the same section of pipe, potentially allowing improvements in defect detection and classification. This paper proposes a novel approach using independent component analysis to decompose repeat guided wave signals into constituent independent components. This separates the defect from coherent noise caused by changing environmental conditions, improving detectability. This paper demonstrates independent component analysis applied to guided wave signals from a range of industrial inspection scenarios. The analysis is performed on test data from pipe loops that have been subject to multiple temperature cycles both in undamaged and damaged states. In addition to processing data from experimental damaged conditions, simulated damage signals have been added to "undamaged" experimental data, so enabling multiple different damage scenarios to be investigated. The algorithm has also been used to process guided wave signals from finite element simulations of a pipe with distributed shallow general corrosion, within which there is a patch of severe corrosion. In all these scenarios, the independent component analysis algorithm was able to extract the defect signal, rejecting coherent noise.