Company
Catalog Number
Comments
A Detector Coil-based PEC Sensing System.
The representative results in this work were generated using the PEC system developed by University of Technology Sydney (UTS), Australia and published in works 6,8. This system may be accessible to readers via collaborating with UTS.
A suitable conductive ferromagnetic material of varying thickness.
The representative results in this work were generated by acquiring PEC measurements on grey cast iron test pieces extracted from a pipe test-bed located in Sydney Australia, whose location and vintage details are available in references 9-11. The pipe test-bed as well as the extracted calibration samples may be accessible to readers via collaborating with UTS.
A computation platform for PEC signal processing
MathWorks, Natick, MA, USA.
A computation platform in which the PEC signal processing algorithm can be coded and executed is required. In this publication, PEC signal processing was done using a software executable named "PEC_Signal_Processor", produced using MATLAB R2017b, Publisher: MathWorks, Natick, MA, USA.
An application that can produce a table containing raw PEC signals (e.g., Microsoft Office Excel).
Microsoft Corporation, One Microsoft Way, Redmond, Washington, USA.
Microsoft Office Excel (Office 16) was used for the work of this publication.
Valls Miro, J., Hunt, D., Ulapane, N., Behrens, M. Towards Automatic Robotic NDT Dense Mapping for Pipeline Integrity Inspection.
Field and Service Robotics
. , Springer. Cham. 319-333 (2018).
Ulapane, N., Thiyagarajan, K., Hunt,
D., Valls Miro, J. Quantifying the Relative Thickness of Conductive Ferromagnetic Materials Using Detector Coil-Based Pulsed Eddy Current Sensors. J. Vis. Exp. (155), e59618, doi:10.3791/59618 (2020).
…
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Ulapane, N., Thiyagarajan, K., Hunt, D., Valls Miro, J. Quantifying the Relative Thickness of Conductive Ferromagnetic Materials Using Detector Coil-Based Pulsed Eddy Current Sensors.
J. Vis. Exp.
(155), e59618, doi:10.3791/59618 (2020).
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[]2，
当一个信号被获取，放置一个PEC传感器在磁渗透性的导电铁磁性层
*，
电导率
=，
和厚度
d。
虽然此衰减率信号特征对传感器尺寸、
传感器形状和提升
6、7、8
等参数
具有相当大的抗扰度，这使得衰减率非常适合具有挑战性的 NDE 方案，如原位管道状况评估
9、10、11），
但必须校准此功能（即，估计被检查材料的
α，=±]），
以便实现厚度（即）。
，d
） 量化。为了使传统的衰变率方法基于厚度定量
6，8，
这种校准必须通过提取校准样品
6，8
或涉及涡流为基础的
材料属性表征方法
12，13。
或者，通过以相对厚度的形式表示厚度，可以避免校准的复杂性。假设进行 NDE 练习并从信号中提取
α
值，则从质量上代表测试件中最大厚度点的
α
值将被视为参考值（即
α
ref
中最大厚度的百分比，将相对厚度作为输出，这仍然是有用的定性信息作为 NDE 输出，也具有不必为
*
，
进行
校准的简单性。此处介绍的协议描述了为此应遵循的步骤。
的条件
的形式找到线性区域。根据
图1
中的信号，
恰好是一个令人满意的、切实可行的线性区域。
与确定线性区域内的实验信号数据拟合，并估计
α
的值。
似乎是一个充分和切实可行的线性区域。
形式中表示相对厚度百分比，其中
索引对应于第
1 个
度量。
"和最后一列"时产生的相应相对厚度值"，最后一列列出了使用第一列中列出的实际厚度值计算的相应实际相对厚度值。图 4 显示了实际相对厚度值相对于从 PEC 信号计算的相对厚度值（即使用
α
值计算）的图
解。
该数据集上观察到的估计值与实际值之间的相关性超过 99%，表明相对厚度定量方法的有效性。
