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Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition

Ultrasonic NDE has been a well known approach to investigate material’s microstructures, mechanical properties and structure integrity in industry. The internal structure of a material and position of anomalies can be recognised by the reactions of different materials to ultrasound. However, the in...

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Main Authors: Ng, Sok Choo, Ismail, Napsiah, Ali, Aidy, Sahari, Barkawi, Mohd Yusof, Juraina
Format: Article
Language:English
Published: Asian Network for Scientific Information 2013
Online Access:http://psasir.upm.edu.my/id/eprint/28797/1/Ultrasonic%20NDE%20for%20internal%20defect%20detection%20in%20multi.pdf
http://psasir.upm.edu.my/id/eprint/28797/
http://scialert.net/abstract/?doi=jas.2013.87.94
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spelling my.upm.eprints.287972015-12-08T03:23:58Z http://psasir.upm.edu.my/id/eprint/28797/ Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition Ng, Sok Choo Ismail, Napsiah Ali, Aidy Sahari, Barkawi Mohd Yusof, Juraina Ultrasonic NDE has been a well known approach to investigate material’s microstructures, mechanical properties and structure integrity in industry. The internal structure of a material and position of anomalies can be recognised by the reactions of different materials to ultrasound. However, the interpretation of ultrasound signals is difficult in composite material inspection task due to the fact that the ultrasonic pulse is reflected not only by the defect occurred within the material but the microstructures and multiple lay ups of the material. This phenomenon causes the backscattering noise to hinder the real defect’s signal during the inspection. Backscattering noise exists in multiple frequencies. The objective of this study was to develop a new noise reduction method to enhance the defect detectability in coarse-grained structure material such as composites materials. This method increases Signal-to-noise Ratio (SNR) by means of decomposing the original signal into multiresolution representations. To prevent the loss of information, the signal is processed in both temporal and frequency domain. The proposed method has been tested on simulated signal and Glass Fiber Reinforced Plastics (GFRP) laminates. Both simulation and experimental results showed that this method can significantly reduce grain noise while preserving the resolution of the original signal of the defect. Asian Network for Scientific Information 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/28797/1/Ultrasonic%20NDE%20for%20internal%20defect%20detection%20in%20multi.pdf Ng, Sok Choo and Ismail, Napsiah and Ali, Aidy and Sahari, Barkawi and Mohd Yusof, Juraina (2013) Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition. Journal of Applied Sciences, 13 (1). pp. 87-94. ISSN 1812-5654 http://scialert.net/abstract/?doi=jas.2013.87.94 10.3923/jas.2013.87.94
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Ultrasonic NDE has been a well known approach to investigate material’s microstructures, mechanical properties and structure integrity in industry. The internal structure of a material and position of anomalies can be recognised by the reactions of different materials to ultrasound. However, the interpretation of ultrasound signals is difficult in composite material inspection task due to the fact that the ultrasonic pulse is reflected not only by the defect occurred within the material but the microstructures and multiple lay ups of the material. This phenomenon causes the backscattering noise to hinder the real defect’s signal during the inspection. Backscattering noise exists in multiple frequencies. The objective of this study was to develop a new noise reduction method to enhance the defect detectability in coarse-grained structure material such as composites materials. This method increases Signal-to-noise Ratio (SNR) by means of decomposing the original signal into multiresolution representations. To prevent the loss of information, the signal is processed in both temporal and frequency domain. The proposed method has been tested on simulated signal and Glass Fiber Reinforced Plastics (GFRP) laminates. Both simulation and experimental results showed that this method can significantly reduce grain noise while preserving the resolution of the original signal of the defect.
format Article
author Ng, Sok Choo
Ismail, Napsiah
Ali, Aidy
Sahari, Barkawi
Mohd Yusof, Juraina
spellingShingle Ng, Sok Choo
Ismail, Napsiah
Ali, Aidy
Sahari, Barkawi
Mohd Yusof, Juraina
Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition
author_facet Ng, Sok Choo
Ismail, Napsiah
Ali, Aidy
Sahari, Barkawi
Mohd Yusof, Juraina
author_sort Ng, Sok Choo
title Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition
title_short Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition
title_full Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition
title_fullStr Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition
title_full_unstemmed Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition
title_sort ultrasonic nde for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition
publisher Asian Network for Scientific Information
publishDate 2013
url http://psasir.upm.edu.my/id/eprint/28797/1/Ultrasonic%20NDE%20for%20internal%20defect%20detection%20in%20multi.pdf
http://psasir.upm.edu.my/id/eprint/28797/
http://scialert.net/abstract/?doi=jas.2013.87.94
_version_ 1643829571312680960
score 13.211869

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