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Pattern recognition by wavelet transforms using macro fibre composites transducers

delete2014-10-01
delete37
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OA
AI
R
Raúl Ruiz de la Hermosa González-Carrato *
F
Fausto Pedro Garcı́a Márquez
V
Vichaar Dimlaye
D
Diego Ruiz-Hernández
DOI:10.1016/j.ymssp.2014.04.002delete
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摘要

摘要

En 中文
This paper presents a novel pattern recognition approach for a non-destructive test based on macro fibre composite transducers applied in pipes. A fault detection and diagnosis (FDD) method is employed to extract relevant information from ultrasound signals by wavelet decomposition technique. The wavelet transform is a powerful tool that reveals particular characteristics as trends or breakdown points. The FDD developed for the case study provides information about the temperatures on the surfaces of the pipe, leading to monitor faults associated with cracks, leaks or corrosion. This issue may not be noticeable when temperatures are not subject to sudden changes, but it can cause structural problems in the medium and long-term. Furthermore, the case study is completed by a statistical method based on the coefficient of determination. The main purpose will be to predict future behaviours in order to set alarm levels as a part of a structural health monitoring system. (C) 2014 Elsevier Ltd. All rights reserved.
Keyword:
Wavelet transform
Macro fibre composite transducers
Pattern recognition
Maintenance management

期刊

Mechanical Systems and Signal Processing 封面图
Mechanical Systems and Signal Processing
IF:
8.9
论文数:
1.3W
被引数:
6.6W

机构

CUNEF Universidad 封面图
CUNEF Universidad
学者数:
186
论文数: 221
被引数: 133
U
Universidad de Castilla-La Mancha
学者数:
9.9K
论文数: 9.1K
被引数: 7
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