scholarly journals Diagnosis of Composite Materials in Aircraft Applications–Brief Survey of Recent Literature

Author(s):  
Muflih Alhammad ◽  
Luca Zanotti Fragonara ◽  
Nicolas P Avdelidis

Diagnosis and prognosis of failures for aircrafts’ integrity are some of the most important regular functionalities in complex and safety-critical aircraft structures. Further, development of failure diagnostic tools such as Non-Destructive Testing (NDT) techniques, in particular, for aircraft composite materials, has been seen as a subject of intensive research over the last decades. The need for diagnostic and prognostic tools for composite materials in aircraft applications rises and draws increasing attention. Yet, there is still an ongoing need for developing new failure diagnostic tools to respond to the rapid industrial development and complex machine design. Such tools will ease the early detection and isolation of developing defects and the prediction of damages propagation; thus allowing for early implementation of preventive maintenance and serve as a countermeasure to the potential of catastrophic failure. In this paper, following a short introductory summary and definitions, this paper provides a brief literature review of recent research on failure diagnosis of composite materials with an emphasis on the use of NDT techniques in aerospace industry. In addition to this, within a some of significant NDT application extents, prognosis of composites is also briefly discussed.

2020 ◽  
Vol 12 (4) ◽  
pp. 168781402091376 ◽  
Author(s):  
Bing Wang ◽  
Shuncong Zhong ◽  
Tung-Lik Lee ◽  
Kevin S Fancey ◽  
Jiawei Mi

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.


2019 ◽  
Vol 9 (14) ◽  
pp. 2810 ◽  
Author(s):  
Azadeh Noori Hoshyar ◽  
Maria Rashidi ◽  
Ranjith Liyanapathirana ◽  
Bijan Samali

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.


2016 ◽  
Author(s):  
Egor V. Yakovlev ◽  
Kirill I. Zaytsev ◽  
Nikita V. Chernomyrdin ◽  
Arsenii A. Gavdush ◽  
Arsen K. Zotov ◽  
...  

2002 ◽  
Author(s):  
◽  
Kevin M. Dugmore

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


1994 ◽  
Vol 82 (11) ◽  
pp. 56-58
Author(s):  
Claude Bathias ◽  
Christophe Le Niniven ◽  
Dongliu Wu

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