Impact damage detection in carbon fibre composites using HTS SQUIDs and neural networks

Graham, Duncan; Maas, P.; Donaldson, G.B.; Carr, C.

doi:10.1016/j.ndteint.2004.03.001

Cited by 19 publications

(19 citation statements)

References 16 publications

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“…Damage detection in CFRP laminates using eddy current methods has been extensively studied (2), (4), (6), (7), (11), (18), (28), (41)(42)(43)(44), (52), (56)(57)(58), (69)(70) . Inhomogeneity and strong anisotropy in CFRP, however, interfere with application of conventional eddy current methods.…”

Section: Eddy Current Methodsmentioning

confidence: 99%

“…Slots up to 17.5mm in depth were in 20mm thick CFRP using this method. D. Graham et al (69) propose a HTS SQUID-based automated detection system using a neural network to speed the detection process of impact damaged CFRP and to increase the probability of detection in data affected by environmental noise. An image of the damaged area was produced using this method.…”

Section: Eddy Current Methodsmentioning

confidence: 99%

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Strain and Damage Monitoring of CFRP Laminates by Means of Electrical Resistance Measurement

Todoroki

Ueda

Hirano

2007

JMMP

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This review discusses the use of electrical resistance and potential change in various methods for monitoring Carbon Fiber Reinforced Plastic (CFRP) composites. CFRP composites have electrical conductivity as they contain carbon fibers. When fibers and fiber networks break within the structure its electrical resistance changes; the electrical resistance of carbon fiber changes with the applied strain just as physical resistance varies in a conventional strain gage. Using these changes in electrical resistance damage to CFRP composites can be monitored and applied strain measured without implementation of additional sensors. This makes CFRP a self-sensing material. The electrical resistance change method has been applied for decades to detect carbon fiber breakages. As regards the measurement of applied strain, there is divergence of opinion amongst researchers about the piezoresistance of CFRP. This discrepancy is discussed in detail in this review. For monitoring damage such as delamination cracks, the electrical resistance change method can accurately estimate the location and dimension of the damage. This review also discusses electrical potential change and eddy current methods for monitoring CFRP composites.

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Section: Eddy Current Methodsmentioning

confidence: 99%

Section: Eddy Current Methodsmentioning

confidence: 99%

Strain and Damage Monitoring of CFRP Laminates by Means of Electrical Resistance Measurement

Todoroki

Ueda

Hirano

2007

JMMP

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“…So far, neural networks have been applied to various topics from fatigue prediction to wear simulation, and to monitoring of the manufacturing process and analysis of composite curing [18]. This technique was also applied to pattern classification in nondestructive detection by SQUIDs in the case of flaws in metals [19,20] and only recently in the case of impact damage in composite materials [21]. The structure used in [21] is a multilayered feed-forward network constructed with three layers of neurons: input, output and hidden layers (Fig.…”

Section: Neural Network System Applied To Cfrpmentioning

confidence: 99%

“…The network function is largely determined by the non-linear connections between neurons. Each synaptic link between neurons is characterized by a weight where all the information of the neural network, acquired during the learning process, is stored (from [21]).…”

Section: Neural Network System Applied To Cfrpmentioning

confidence: 99%

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Nondestructive detection of damage in carbon fibre composites by SQUID magnetometry

Ruosi

2005

phys. stat. sol. (c)

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Monitoring of structural integrity is an essential issue in enhancing the affordability as well the safety of modern aircraft and spacecraft structures. Increasingly, metallic parts of aircrafts are being replaced by carbon fibre composite components due to their high strength and stiffness combined with low density. This paper reviews of the use of superconducting quantum interference devices (SQUIDs) in the detection of different types of damage in carbon fibre panels. The results presented here on impact damage on carbon fibre reinforced polymer and cracks induced by tensile loads on carbon fibre reinforced carbon matrix show that this method is sensitive not only to the presence but also the severity of damage. Indeed, it enables one to distinguish between the different failure mechanisms as the damage process evolves. SQUIDs response to artificial delaminations, flaws and deep-lying defects are also presented. The application of a neural network system for the detection of impact damage in a noisy environment is discussed. Experimental results demonstrate that nondestructive evaluation using SQUID magnetometers is a suitable technique to investigate composites to improve their mechanical properties

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SQUIDsin Nondestructive Evaluation

Krause

Tanaka

2015

Digital Encyclopedia of Applied Physics

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Impact damage detection in carbon fibre composites using HTS SQUIDs and neural networks

Cited by 19 publications

References 16 publications

Strain and Damage Monitoring of CFRP Laminates by Means of Electrical Resistance Measurement

Strain and Damage Monitoring of CFRP Laminates by Means of Electrical Resistance Measurement

Nondestructive detection of damage in carbon fibre composites by SQUID magnetometry

SQUIDsin Nondestructive Evaluation

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