APPLICATION OF MELLIN TRANSFORM FEATURES FOR ROBUST ULTRASONIC GUIDED WAVE STRUCTURAL HEALTH MONITORING

被引：14

作者：

Harley, Joel B. ^{[1
]}

Ying, Yujie ^{[2
]}

Moura, Jose M. F. ^{[1
]}

Oppenheim, Irving J. ^{[2
]}

Sobelman, Lucio ^{[2
]}

Garrett, James H. ^{[2
]}

机构：

[1] Carnegie Mellon Univ, Dept Elect & Comp Engn, Pittsburgh, PA 15213 USA

[2] Carnegie Mellon Univ, Dept Civil & Environm Engn, Pittsburgh, PA 15213 USA

来源：

REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOLS 31A AND 31B | 2012年 / 1430卷

关键词：

Structural Health Monitoring; Environmental Effects; Mellin Transform; Detection; Correlation; Machine Learning; TEMPERATURE-DEPENDENCE;

D O I：

10.1063/1.4716399

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

Guided wave based structural health monitoring systems are sensitive to environmental and operational conditions. This leads to false-positive results for most conventional detection methods. In this paper, we investigate the capabilities of the Mellin transform for detecting damage under variable environmental conditions. The Mellin transform is chosen due to its invariance to scaling operations and robustness to wave velocity. From experimental results, we demonstrate that the Mellin transform features can detect a mass on a steel pipe under variable internal pressure with an overall average accuracy of 94.00% while equivalent Fourier transform features detect the mass with only a 67.00% accuracy.

引用

页码：1551 / 1558

页数：8

共 18 条

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