Aircraft Composite Materials Research Articles

FTnet: An integrated network for fusing multi-modal NDE data of lightning damage in aircraft composite materials

Lightning strikes pose a significant challenge for aircraft and wind turbine blades with Carbon Fiber Reinforced Polymer (CFRP) structures, requiring reliable damage detection techniques. Non-destructive evaluation (NDE) methods, including X-ray and Ultrasonic Testing, are effective in identifying material damage in aircraft. However, X-ray requires access to both sides of the structure, and UT requires a coupling medium between the transducer and the structure, as well as a relatively smooth surface, making both methods less feasible for routine aircraft maintenance. Other NDE techniques, such as eddy current testing and infrared thermography, can detect damage on the side struck by lightning but lack the precision needed for a comprehensive assessment. To address these challenges, this paper introduces a two-stage Fusion-Translation network (FTnet), which integrates NDE 4.0 innovations, including data fusion and advanced imaging algorithms, to optimize the NDE process. By integrating infrared and eddy current data, FTnet characterizes lightning-induced damage with enhanced depth and contour detail, demonstrating superior performance over existing methods in both qualitative and quantitative evaluations. The implementation of FTnet marks an advancement in NDE 4.0, potentially enhancing aircraft safety and streamline maintenance protocols by providing a more reliable and comprehensive assessment of lightning strike damage.

Evaluation of the mechanical properties of aircraft composite materials after indentation

Evaluation of the mechanical properties of aircraft composite materials after indentation

Infrared defect recognition technology for composite materials

This study mainly involves the methods and experiments of using infrared thermal wave imaging detection technology to detect internal defects in aircraft composite materials. The results were discussed and analyzed. In this paper, the feasibility of the experiment was verified by simulation. In simulation, the minimum accuracy of detectable defects is 4 mm radius under the mesh division accuracy with a correlation coefficient of 5. On this basis, an accurate detection method and prototype nondestructive testing system for defects of aircraft composite materials based on infrared imaging detection technology were designed, which can realize the identification and positioning of defects in aircraft composite material structures, including type, size and accurate depth of defects. Finally, the data collected by the infrared detection system was recognized through YOLO neural network. The test result shows the confidence level for water point defect is more than 0.9, while the confidence level for crack defect is about 0.5. This research result will expand the use case of infrared nondestructive testing technology around the world, and the transformation of the results will help to solve the maintenance problems of aircraft in general aviation.

Data Twin-Driven Cyber-Physical Factory for Smart Manufacturing.

Because of the complex production processes and technology-intensive operations that take place in the aerospace and defense industry, introducing Industry 4.0 into the manufacturing processes of aircraft composite materials is inevitable. Digital Twin and Cyber-Physical Systems in Industry 4.0 are key techniques to develop digital manufacturing. Since it is very difficult to create high-fidelity virtual models, the development of digital manufacturing for aircraft manufacturers is challenging. In this study, we provide a view from a data simulation perspective and adopt machine learning approaches to simplify the high-fidelity virtual models in Digital Twin. The novel concept is called Data Twin, and the deployable service to support the simulation is known as the Data Twin Service (DTS). Relying on the DTS, we also propose a microservice software architecture, Cyber-Physical Factory (CPF), to simulate the shop floor environment. Additionally, there are two war rooms in the CPF that can be used to establish a collaborative platform: one is the Physical War Room, used to integrate real data, and the other is the Cyber War Room for handling simulation data and the results of the CPF.

Economic and Environmental Aspects of Aircraft Recycling

Aircraft recycling can be considered as an important step on the path to sustainable aviation, as valuable resources used in aircraft construction can be returned for use in a circular economy by these activities. Our results have shown that the market for aircraft recycling is emerging with great future relevance due to the increasing number of aircraft retirements expected in the future. The costs of recycling per aircraft vary by aircraft class and number of engines. The costs range from USD 109,000 for a twin-engine regional jet to USD 268,000 for a four-engine widebody jet. The costs for a twin-engine narrowbody jet lie in between at USD 138,000. In this paper, we investigated the economic efficiency of aircraft recycling expressed as the ratio of average dismantling and recycling costs per aircraft and engine in USD compared with the achieved environmental benefit in average tons recycled material or re-used parts. This ratio revealed that aircraft recycling leads to notable environmental benefits as a large share (60%) of the total structural weight is being re-used at given costs. The average economic efficiency is estimated at 1,666 USD/ton for a widebody aircraft, 3,531 USD/ton for a narrowbody jet and 6,693 USD per ton for a regional jet. In future, aircraft recycling will be facing a number of major challenges as the number of retired aircraft will increase and the share of composite material to be recycled will rise significantly in the medium and long term - for which material no satisfying technological recycling solution exists today. In addition, the environmental pressure from politics and society is expected to be increasing in future. Against this background, we recommend to effectively enforce ambitious recycling standards for retired aircraft on a global level. Furthermore, as recycling technologies for aircraft composite materials are not mature currently, significant R&D investments are needed for these technologies.

Intelligent damage recognition of composite materials based on deep learning and ultrasonic testing

Ultrasonic non-destructive testing can effectively detect damage in aircraft composite materials, but traditional manual testing is time-consuming and labor-intensive. To realize the intelligent recognition of aircraft composite material damage, this paper proposes a 1D-YOLO network, in which intelligent fusion recognizes both the ultrasonic C-scan image and ultrasonic A-scan signal of composite material damage. Through training and testing the composite material damage data on aircraft skin, the accuracy of the model is 94.5%, the mean average precision is 80.0%, and the kappa value is 97.5%. The use of dilated convolution and a recursive feature pyramid effectively improves the feature extraction ability of the model. The effectively used Cascade R-CNN (Cascade Region-Convolutional Neural Network) improves the recognition effect of the model, and the effectively used one-dimensional convolutional neural network excludes non-damaged objects. Comparing our network with YOLOv3, YOLOv4, cascade R-CNN, and other networks, the results show that our network can identify the damage of composite materials more accurately.

Intelligent recognition of composite material damage based on deep learning and infrared testing.

Composite materials are commonly used in aircraft, and the integrity of these materials affects both flight and safety performance. Damage detection technology involving infrared nondestructive testing has played an important role in damage detection in aircraft composite materials. Traditional manual detection methods are inefficient, and the use of intelligent detection methods can effectively improve detection efficiency. Due to the diverse types of damage that can occur in composite materials, this damage is difficult to distinguish solely from infrared images. The introduction of infrared signals, which is temporal signals, provides the possibility of judging the type of damage. In this paper, a 1D-YOLOv4 network is established. The network is based on the YOLOv4 network and adds a changing neck and a 1D-CNN for improvement. Testing shows that the algorithm can identify infrared images and infrared signals in composite materials. Its recognition accuracy is 98.3%, with an AP of 91.9%, and a kappa of 0.997. Comparing the network in this paper with networks such as YOLOv3, YOLOv4 and YOLOv4+Neck, the results show that the proposed network is more effective. At the same time, the detection effects of the original data, the fitted data, the first derivative data and the second derivative data are studied, and the detection effect of the first derivative data has the best outcome.

Fast, Accurate, and Reliable Detection of Damage in Aircraft Composites by Advanced Synergistic Infrared Thermography and Phased Array Techniques

This paper presents an advanced methodology for the detection of damage in aircraft composite materials based on the sensor fusion of two image-based non-destructive evaluation techniques. Both of the techniques, phased-array ultrasonics and infra-red thermography, are benchmarked on an aircraft-grade painted composite material skin panel with stringers. The sensors systems for carrying out the inspections have been developed and miniaturized for being integrated on a vortex-robotic platform inspector, in the framework of a larger research initiative, the Horizon-2020 ‘CompInnova’ project.

A review of failure modes and fracture analysis of aircraft composite materials

Composite material-based structures have become increasingly common for aircraft construction. While a large number of researches focused on the understanding of composite materials and structures’ behavior under a variety of scenarios to determine their performance when being exposed to flight loads, it is also critical to consider how these materials fail and fracture, especially in an aircraft accident. In this study, tension, compression, bend, impact, and fatigue fracture analysis of composite laminates and sandwich structures are reviewed, and the failure modes and characteristics of adhesively and mechanically fastened joints are analyzed. Furthermore, aircraft accidents in which composite materials failed are described to highlight the significance of the understanding of composite materials failure modes and fracture analysis on the overall aircraft accident investigation process. Thus, the presented study has a twofold purpose. To provide an all-encompassing review of current research in the area of composite material failure modes and fracture analysis, as well as presenting exemplary cases of aircraft accidents in which the composite material failure modes and fracture analysis body of knowledge has been practically applied. Three overarching themes were observed during the study. First, the complexity of composite material fracture analysis when compared to metallic material fracture analysis. Second, the relationship and dependency between fractographic features of composite materials and the composite structure itself and the failure mode. Lastly, the study and further investigation of composite material failures are found to be critical for aircraft accident investigations. The results from this review can be applied to identify areas of future development concerning composite material failure modes and fracture analysis, especially with applications to material analysis during aircraft accident investigations.

On The Generation of Terahertz Pulses Using Thermoelastic Effect

Time-resolved terahertz spectroscopy can be proposed as a method of non-destructive testing of various parts, for example, aircraft composite materials. The theoretical background and the possibility of exciting pulses of electromagnetic waves in the range of terahertz oscillations using picosecond acoustic pulses excited by laser pulses based on the thermoelastic effect are studied.

Electromagnetic Characterization of Aircraft Composite Materials and its Effects on the Antenna Performance

This paper presents an electromagnetic characterization of aircraft composite materials, as well as numerical and experimental analyses of its effects on the antenna performance. Two uncalibrated S-parameters characterization methods have been applied for retrieving the complex electrical permittivity in the L- and C-band, namely: Air-region method and Sample-shifted method. Dielectric constants of 4.6 and 1.84 and loss tangent of 2.0x10 -2 and 6.1x10 -2 have been obtained for fiberglass and honeycomb composite materials, respectively. A 3.0-meters prototype of an Embraer light jet aircraft dorsal fin was fabricated and used in the experiments in a semi-anechoic chamber in order to evaluate the impact of installing aeronautical VHF and L-band antennas on a fuselage made of composite materials.

Non-destructive inspection of aircraft composite materials using triple IR imaging

Abstract: The wide use of composite materials in a number of industrial sectors has necessitated the development of new nondestructive inspection techniques for both manufacturing quality assurance and in-service damage testing. This paper discusses the development of a new holistic inspection system for aircraft composite materials that is composed of three thermographic cameras (operating at different wavelengths such as Near-infrared, Mid-Wave and Long-Wave) placed on the head of a robotic arm. Different setups were investigated in order to achieve optimal settings for a variety of influencing parameters including camera distance from the surface under investigation, excitation source type and power. Experiments were also conducted to define the effectiveness of each thermographic camera towards a variety of defect types. Advanced image processing algorithms were further developed and deployed to enhance the inspection capabilities of the three cameras and improve the interpretation of the collected thermal images. Future work on validating fusion and machine learning tools, their integration as well as on-site inspections has been planned.

주성분 분석과 이차 판별 분석 기법을 이용한 항공기 복합재료에서의 자동 결함 검출 및 분류

주성분 분석과 이차 판별 분석 기법을 이용한 항공기 복합재료에서의 자동 결함 검출 및 분류

New Technology Research of Nondestructive Testing for Aero Aircraft Composite Materials

Composite materials have many advantages such as big specific strength, high specific stiffness, good disrepair safety characteristic, large area molding conveniently and easy to forming complex shape. It becomes important structural materials of aero aircraft equipment necessarily and is used widely in aviation industry. Composite materials components of aero aircraft with complex and delicate structure chronically work in harsh environment. Early testing of its key component’s minute defects has been an urgent and necessary task. In this paper, its damage model and characteristic are analyzed and studied. Considering the limitation of composite materials structure’s detection methods at present, a number of existing problems are presented and development directions are pointed out. Laser ultrasound detection technique, continuous distribution sensing technique and optical fiber sensing technique are studied. The method of damage detection of aero aircraft’s composite materials components is put forward based on the organic combination of the three techniques. The results show that the system can be used to detect multi-ultrasound signals of large composite materials structure. Its structure is simple. It has small bulk and low cost. It is characterized by easy realization.

3C14 Damage detection in aircraft composite materials using a built-in broadband ultrasonic propagation system

3C14 Damage detection in aircraft composite materials using a built-in broadband ultrasonic propagation system

Defect detection in aircraft composites by using a neural approach in the analysis of thermographic images

Safety in aeronautics could be improved if continuous checks were guaranteed during the in-service inspection of aircraft. However, until now, the maintenance costs of so doing have proved prohibitive. For this reason there is a great interest for the development of low cost non-destructive inspection techniques that can be applied during normal routine tests. The analysis of the internal defects (not detectable by a visual inspection) of the aircraft composite materials is a difficult task unless invasive techniques are applied. In this paper, we have addressed the problem of inspecting composite materials by using automatic analysis of thermographic techniques. The analysis of the time/space variations in a sequence of thermographic images allows the identification of internal defects in composite materials that otherwise could not be detected. A neural network was trained to extract the information that characterises a range of internal defects in different types of composite materials. After the training phase the same neural network was applied to all the points of a sequence of thermographic images. The experimental results demonstrate the ability of the method to recognize regions containing defects but also to identify the contour regions that cannot be associated either with a defective or with a sound region.

Fire resistance certification of aircraft composite materials

The Federal Aviation Administration (FAA) requires fire resistance certification of aircraft composite materials used in civil aircraft exterior structure and engine compartments. This paper presents an FAA approved process for accomplishing certification testing at minimum cost and time using an oxygen-acetylene heating tip. The test stand and process minimized human factors and quantified backside flame visibility for comparing aluminum and composite materials. The process focus was on demonstratingfire resistant characteristics, but could also be applied to thefireproof test process. Backside flame visibility was defined as the visual observance of light from the oxygen-acetylene flame. This definition was uniformly applied to both the aluminum test panels and the composite test panels. This presentation of the fire resistant certification process for aircraft composite materials will enable others to efficiently set up and perform both fire resistant and fireproof certification testing.

航空機用エンジンと複合材料

航空機用エンジンと複合材料