Artificial Neural Network Application for Damages Classification in Fibreglass Pre-impregnated Laminated Composites (FGLC) from Ultrasonic Signal

Mahmod, Muhammad Faisal; Bakar, Elmi Abu; Ramzi, Raiminor; Harimon, Mohd Azhar; Latif, Noradila Abdul; Mustapa, Mohammad Sukri; Ismail, Al Emran

doi:10.1007/978-981-13-6447-1_72

Cited by 1 publication

(2 citation statements)

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“…These are achieved through artificial neural network coding or algorithms to enable automatic detection and recognition of defects/damage. Examples include applying pattern recognition to discriminate failure modes in composites using AE data; 307 damage classification in carbon fibre–reinforced polymer (CFRP) laminates using artificial neural networks in UT; 308 automatic defect detection through IRT in CFRP laminates 309 and honeycomb composite structures; 310 an automated shearography system for cylindrical surface inspection using machining learning; 252 neural network-based hybrid signal processing for THz pulsed imaging. 311 Despite the exciting achievements in NDT techniques, there is still substantial work required to develop fast and affordable systems for both equipment and data processing methods to promote their practical implementation in industry.…”

Section: Discussionmentioning

confidence: 99%

“…The initial development and application of various NDT techniques are driven by demands from aerospace industries, which rapidly expand to other fields. AE, ultrasound, IRT, shearography, DIC and X-ray imaging represent the main techniques within composite Examples include: applying pattern recognition to discriminate failure modes in composites using acoustic emission data [307]; damage classification in CFRP laminates using artificial neural networks in ultrasonic testing [308]; automatic defect detection through infrared thermography in CFRP laminates [309] and honeycomb composite structures [310]; an automated shearography system for cylindrical surface inspection using machining learning [252]; neural network-based hybrid signal processing for terahertz pulsed imaging [311].…”

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confidence: 99%

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

Wang

Zhong

Lee

et al. 2020

Advances in Mechanical Engineering

297

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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, and medical equipment, etc. Thus robust and reliable non-destructive testing (NDT) of composites is essential to reduce safety concerns and maintenance costs. There have been various NDT methods built upon different principles for quality assurance during the whole lifecycle of a composite product. This paper reviews the most established NDT 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 NDT 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 NDT technique has its own potential and rarely achieves a full-scale diagnosis of structural integrity. Future development of NDT techniques for composites will be directed towards intelligent and automated inspection systems with high accuracy and efficient data processing capabilities.

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