Machine Learning and Infrared Thermography for Fiber Orientation Assessment on Randomly-Oriented Strands Parts

Fernandes, Henrique; Zhang, Hai; Figueiredo, Alisson; Malheiros, Fernando Costa; Ignacio, Luís Henrique da Silva; Сфарра, Стефано; Ibarra-Castanedo, Clemente; Guimarães, Gilmar; Maldague, Xavier

doi:10.3390/s18010288

Cited by 26 publications

(12 citation statements)

References 34 publications

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“…Roemer et al [ 93 ] compared LST with UST (see Section 3 ) to detect fatigue cracks on an aluminium sample ( Figure 10 ). Khodayar et al [ 94 ] used robotized Line Scan Thermography to inspect large composite materials, whilst Zhang et al [ 95 ] used pulsed micro-laser line thermography to detect submillimeter porosity in CFRP composites. Fernandes et al [ 96 ] employed a flying laser spot to heat a line region on a CFRP sample and assess the fiber orientation over that region.…”

Section: Optically Stimulated Thermographymentioning

confidence: 99%

Recent Advances in Active Infrared Thermography for Non-Destructive Testing of Aerospace Components

Ciampa

Mahmoodi

Pinto

et al. 2018

Sensors

347

185

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Active infrared thermography is a fast and accurate non-destructive evaluation technique that is of particular relevance to the aerospace industry for the inspection of aircraft and helicopters’ primary and secondary structures, aero-engine parts, spacecraft components and its subsystems. This review provides an exhaustive summary of most recent active thermographic methods used for aerospace applications according to their physical principle and thermal excitation sources. Besides traditional optically stimulated thermography, which uses external optical radiation such as flashes, heaters and laser systems, novel hybrid thermographic techniques are also investigated. These include ultrasonic stimulated thermography, which uses ultrasonic waves and the local damage resonance effect to enhance the reliability and sensitivity to micro-cracks, eddy current stimulated thermography, which uses cost-effective eddy current excitation to generate induction heating, and microwave thermography, which uses electromagnetic radiation at the microwave frequency bands to provide rapid detection of cracks and delamination. All these techniques are here analysed and numerous examples are provided for different damage scenarios and aerospace components in order to identify the strength and limitations of each thermographic technique. Moreover, alternative strategies to current external thermal excitation sources, here named as material-based thermography methods, are examined in this paper. These novel thermographic techniques rely on thermoresistive internal heating and offer a fast, low power, accurate and reliable assessment of damage in aerospace composites.

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Section: Optically Stimulated Thermographymentioning

confidence: 99%

Recent Advances in Active Infrared Thermography for Non-Destructive Testing of Aerospace Components

Ciampa

Mahmoodi

Pinto

et al. 2018

Sensors

347

185

View full text Add to dashboard Cite

show abstract

“…Sub-surface artificial defects in composite sandwich panels (commonly used materials in aircraft applications) could be identified using Laser-Line Thermography (LLT) [43][44]. Feasibility of Laser-Spot Thermography (LST), Laser-Line Thermography (LLT) and Ultrasonic Stimulated Thermography (UST) for inspections of composite materials, employed in aircraft industry, such as metallic turbine blades, aluminium samples, CFRP composites etc., to name few, was also assessed in several investigations [45][46][47][48][49].…”

Section: Applications Of Thermography For Aircraft Compositesmentioning

confidence: 99%

“…It was concluded that the detection accuracy of the proposed NN for the simulated data and the experimental data was 97% and 90% respectively. The artificial neural network algorithm was also combined with what so called Pulsed Thermal Ellipsometry (PTE) to investigate the fiber orientation on laminates reinforced with randomly-oriented strands [87]. Different CFRP samples were experimented using two thermography heating approaches.…”

Section: Applications Of Thermography For Aircraft Compositesmentioning

confidence: 99%

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

Alhammad¹,

Fragonara²,

Avdelidis³

2020

Preprint

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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.

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“…These data must be processed to extract knowledge about the inner structures of composite components. With this regard, machine learning can play a key role in defect and damage assessment [ 16 , 17 , 18 , 19 , 20 ]. Deep learning is a machine learning approach that is based on neural networks.…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning Method for the Impact Damage Segmentation of Curve-Shaped CFRP Specimens Inspected by Infrared Thermography

Wei

Fernandes

Herrmann

et al. 2021

Sensors

Self Cite

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Advanced materials such as continuous carbon fiber-reinforced thermoplastic (CFRP) laminates are commonly used in many industries, mainly because of their strength, stiffness to weight ratio, toughness, weldability, and repairability. Structural components working in harsh environments such as satellites are permanently exposed to some sort of damage during their lifetimes. To detect and characterize these damages, non-destructive testing and evaluation techniques are essential tools, especially for composite materials. In this study, artificial intelligence was applied in combination with infrared thermography to detected and segment impact damage on curved laminates that were previously submitted to a severe thermal stress cycles and subsequent ballistic impacts. Segmentation was performed on both mid-wave and long-wave infrared sequences obtained simultaneously during pulsed thermography experiments by means of a deep neural network. A deep neural network was trained for each wavelength. Both networks generated satisfactory results. The model trained with mid-wave images achieved an F1-score of 92.74% and the model trained with long-wave images achieved an F1-score of 87.39%.

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Machine Learning and Infrared Thermography for Fiber Orientation Assessment on Randomly-Oriented Strands Parts

Cited by 26 publications

References 34 publications

Recent Advances in Active Infrared Thermography for Non-Destructive Testing of Aerospace Components

Recent Advances in Active Infrared Thermography for Non-Destructive Testing of Aerospace Components

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

A Deep Learning Method for the Impact Damage Segmentation of Curve-Shaped CFRP Specimens Inspected by Infrared Thermography

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