Non destructive testing and smart composite materials

1994 ◽  
Vol 82 (11) ◽  
pp. 29-33
Author(s):  
Takehito Fukuda
Keyword(s):  
Composite Materials ◽  
Non Destructive Testing ◽  
Smart Composite ◽  
Destructive Testing ◽  
Smart Composite Materials ◽  
Non Destructive

scholarly journals Non-destructive testing and evaluation of composite materials/structures: A state-of-the-art review

2020 ◽  
Vol 12 (4) ◽  
pp. 168781402091376 ◽  
Author(s):  
Bing Wang ◽  
Shuncong Zhong ◽  
Tung-Lik Lee ◽  
Kevin S Fancey ◽  
Jiawei Mi
Keyword(s):  
Composite Materials ◽  
Composite Structures ◽  
Neutron Imaging ◽  
Image Correlation ◽  
Historical Background ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Testing Technique ◽  
Testing Techniques ◽  
Non Destructive

Composite materials/structures are advancing in product efficiency, cost-effectiveness and the development of superior specific properties. There are increasing demands in their applications to load-carrying structures in aerospace, wind turbines, transportation, medical equipment and so on. Thus, robust and reliable non-destructive testing of composites is essential to reduce safety concerns and maintenance costs. There have been various non-destructive testing methods built upon different principles for quality assurance during the whole lifecycle of a composite product. This article reviews the most established non-destructive testing techniques for detection and evaluation of defects/damage evolution in composites. These include acoustic emission, ultrasonic testing, infrared thermography, terahertz testing, shearography, digital image correlation, as well as X-ray and neutron imaging. For each non-destructive testing technique, we cover a brief historical background, principles, standard practices, equipment and facilities used for composite research. We also compare and discuss their benefits and limitations and further summarise their capabilities and applications to composite structures. Each non-destructive testing technique has its own potential and rarely achieves a full-scale diagnosis of structural integrity. Future development of non-destructive testing techniques for composites will be directed towards intelligent and automated inspection systems with high accuracy and efficient data processing capabilities.

scholarly journals Algorithm Development for the Non-Destructive Testing of Structural Damage

2019 ◽  
Vol 9 (14) ◽  
pp. 2810 ◽  
Author(s):  
Azadeh Noori Hoshyar ◽  
Maria Rashidi ◽  
Ranjith Liyanapathirana ◽  
Bijan Samali
Keyword(s):  
Composite Materials ◽  
Structural Damage ◽  
Steel Plates ◽  
Sensor Data ◽  
Support Vector ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Validity Assessment ◽  
Metal Plates ◽  
Non Destructive

Monitoring of structures to identify types of damages that occur under loading is essential in practical applications of civil infrastructure. In this paper, we detect and visualize damage based on several non-destructive testing (NDT) methods. A machine learning (ML) approach based on the Support Vector Machine (SVM) method is developed to prevent misdirection of the event interpretation of what is happening in the material. The objective is to identify cracks in the early stages, to reduce the risk of failure in structures. Theoretical and experimental analyses are derived by computing the performance indicators on the smart aggregate (SA)-based sensor data for concrete and reinforced-concrete (RC) beams. Validity assessment of the proposed indices was addressed through a comparative analysis with traditional SVM. The developed ML algorithms are shown to recognize cracks with a higher accuracy than the traditional SVM. Additionally, we propose different algorithms for microwave- or millimeter-wave imaging of steel plates, composite materials, and metal plates, to identify and visualize cracks. The proposed algorithm for steel plates is based on the gradient magnitude in four directions of an image, and is followed by the edge detection technique. Three algorithms were proposed for each of composite materials and metal plates, and are based on 2D fast Fourier transform (FFT) and hybrid fuzzy c-mean techniques, respectively. The proposed algorithms were able to recognize and visualize the cracking incurred in the structure more efficiently than the traditional techniques. The reported results are expected to be beneficial for NDT-based applications, particularly in civil engineering.

Non-destructive testing of composite materials using terahertz time-domain spectroscopy

2016 ◽  
Author(s):  
Egor V. Yakovlev ◽  
Kirill I. Zaytsev ◽  
Nikita V. Chernomyrdin ◽  
Arsenii A. Gavdush ◽  
Arsen K. Zotov ◽  
...  
Keyword(s):  
Composite Materials ◽  
Time Domain ◽  
Non Destructive Testing ◽  
Terahertz Time Domain Spectroscopy ◽  
Destructive Testing ◽  
Time Domain Spectroscopy ◽  
Non Destructive

scholarly journals Acousto-ultrasonics for defect assessment of composite materials

2002 ◽  
Author(s):  
◽  
Kevin M. Dugmore
Keyword(s):  
Composite Materials ◽  
Composite Structures ◽  
Testing Device ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Defect Assessment ◽  
Short Time ◽  
Non Destructive

The experiments and their results contained herein will form the basis for the development of a portable non-destructive testing device for composite structures. This device is to be capable of detecting any of a variety of defects and assessing their severity within a short time

scholarly journals Identification of structural defects in composite materials by the thermal imaging non-destructive testing method

2019 ◽  
Vol 298 ◽  
pp. 00119
Author(s):  
Andrey Kokurov ◽  
Igor Odintsev ◽  
Boris Chichigin ◽  
Dmitry Subbotin
Keyword(s):  
Composite Materials ◽  
Polymer Composites ◽  
Thermal Imaging ◽  
Structural Defects ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Testing Method ◽  
Non Destructive ◽  
Layered Polymer Composites

The article discusses the practical aspects of applying the thermal imaging non-destructive testing method of layered polymer composites. The specific purpose of the work is to demonstrate the possibilities of detecting in material and geometric identification of initial defects such as debonding.

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