Inspection of aircraft wing panels using unmanned aerial vehicles

In large civil aircraft manufacturing, a time-consuming post-production process is the non-destructive inspection of wing panels. This work aims to address this challenge and improve the defects’ detection by performing automated aerial inspection using a small off-the-shelf multirotor. The UAV is equipped with a wide field-of-view camera and an ultraviolet torch for implementing non-invasive imaging inspection. In particular, the UAV is programmed to perform the complete mission and stream video, in real-time, to the ground control station where the defects’ detection algorithm is executed. The proposed platform was mathematically modelled in MATLAB/SIMULINK in order to assess the behaviour of the system using a path following method during the aircraft wing inspection. In addition, two defect detection algorithms were implemented and tested on a dataset containing images obtained during inspection at Airbus facilities. The results show that for the current dataset the proposed methods can identify all the images containing defects

Inspection of aircraft wing panels using unmanned aerial vehicles

In large civil aircraft manufacturing a time-consuming post-production process is the non-destructive inspection of wing panels. This work aims to address this challenge and improve the defects' detection by performing automated aerial inspection using a small off-the-shelf multirotor. The UAV is equipped with a wide field-of-view camera and an ultraviolet torch for implementing non-invasive imaging inspection. In particular, the UAV is programmed to perform the complete mission and stream video, in real-time, to the ground control station where the defects' detection algorithm is executed. The proposed platform was mathematically modelled in MATLAB/SIMULINK in order to assess the behaviour of the system using a path following method during the aircraft wing inspection. The UAV was tested in the lab where a six-meter-long wing panel was one-side inspected. Initial results indicate that this inspection method could reduce significantly the inspection time, cost, and workload, whilst potentially increasing the probability of detection

Autonomous systems thermographic NDT of composite structures

Transient thermography is a method used successfully in the evaluation of composite materials and aerospace structures. It has the capacity to deliver both qualitative and quantitative results about hidden defects or features in a composite structure. Aircraft must undergo routine maintenance – inspection to check for any critical damage and thus to ensure its safety. This work aims to address the challenge of NDT automated inspection and improve the defects’ detection by suggesting an autonomous thermographic imaging approach using a UAV (Unmanned Aerial Vehicle) active thermographic system. The concept of active thermography is discussed and presented in the inspection of aircraft CFRP panels along with the mission planning for aerial inspection using the UAV for real time inspection. Results indicate that the suggested approach could significantly reduce the inspection time, cost, and workload, whilst potentially increase the probability of detection of defects on aircraft composites

Autonomous systems imaging of aerospace structures

Aircraft manufacturers are constantly improving their aircraft ensuring they are more cost-efficient to do this the weight of the aircraft needs to be reduced, which results in less fuel required to power the aircraft. This has led to an increased use of composite materials within an aircraft. Carbon fibre reinforced polymer (CFRP) composite is used in industries where high strength and rigidity are required in relation to weight. e.g. in aviation – transport. The fibre-reinforced matrix systems are extremely strong (i.e. have excellent mechanical properties and high resistance to corrosion). However, because of the nature of the CFRP, it does not dint or bend, as aluminium would do when damaged, it makes it difficult to locate structural damage, especially subsurface. Non Destructive Testing (NDT) is a wide group of analysis techniques used to evaluate the properties of a material, component or system without causing damage to the operator or material. Active Thermography is one of the NDT risk-free methods used successfully in the evaluation of composite materials. This approach has the ability to provide both qualitative and quantitative information about hidden defects or features in a composite structure. Aircraft has to undergo routine maintenance – inspection to check for any critical damage and thus to ensure its safety. This work aims to address the challenge of NDT automated inspection and improve the defects’ detection by performing automated aerial inspection using a Unmanned Aerial Vehicle (UAV) thermographic imaging system. The concept of active thermography is discussed and presented in the inspection of aircraft’s CFRP panels along with the mission planning for aerial inspection using the UAV for real time inspection. Results indicate that this inspection approach could significantly reduce the inspection time, cost, and workload, whilst potentially increasing the probability of detection

Application of NDT thermographic imaging of aerospace structures

This work aims to address the effectiveness and challenges of Non-Destructive Testing (NDT) inspection and improve the detection of defects without causing damage to the material or operator. It focuses on two types of NDT methods; pulsed thermography and vibrothermography. The paper also explores the possibility of performing automated aerial inspection using an unmanned aerial vehicle (UAV) provided with a thermographic imaging system. The concept of active thermography is discussed for inspecting aircraft CFRP panels along with the proposal for performing aerial inspection using the UAV for real time inspection. Static NDT results and the further UAV research indicate that the UAV inspection approach could significantly reduce the inspection time, cost, and workload, whilst potentially increasing the probability of detection

Autonomous Systems Imaging of Aerospace Structures

Manufacturers are constantly looking for more cost-efficient means to produce aircraft components. An effective way to do this is to reduce the weight, which results in less fuel required to power the aircraft. This has led to an increased use of composite materials. Carbon fibre reinforced polymer (CFRP) composite is used in industries where high strength and rigidity are required in relation to weight. e.g. in aviation – transport. The fibre-reinforced matrix systems are extremely strong (i.e. have excellent mechanical properties and high resistance to corrosion). However, because of the nature of the CFRP, it does not dint or bend, as aluminium would do when damaged, it makes it difficult to locate structural damage, especially subsurface. Non-Destructive Testing (NDT) is a wide group of analysis techniques used to evaluate the properties of a material, component or system without causing damage to the operator or material. Active Thermography is one of the NDT risk-free methods used successfully in the evaluation of composite materials. This approach has the ability to provide both qualitative and quantitative information about hidden defects or features in a composite structure. Aircraft must undergo routine maintenance –inspection to asses for any critical damage and thus to ensure its safety. This work aims to address the challenge of NDT automated inspection and improve the defects’ detection by performing automated aerial inspection using an Unmanned Aerial Vehicle (UAV) thermographic imaging system. The concept of active thermography is discussed and presented in the inspection of aircraft’s CFRP panels along with the mission planning for aerial inspection using the UAV for real time inspection. Results indicate that this inspection approach could significantly reduce the inspection time, cost, and workload, whilst potentially increasing the probability of detection

Improving depth resolution of ultrasonic phased array imaging to inspect aerospace composite structures

In this paper, we present challenges and achievements in development and use of a compact ultrasonic Phased Array (PA) module with signal processing and imaging technology for autonomous non-destructive evaluation of composite aerospace structures. We analyse two different sets of ultrasonic scan data, acquired from 5 MHz and 10 MHz PA transducers. Although higher frequency transducers promise higher axial (depth) resolution in PA imaging, we face several signal processing challenges to detect defects in composite specimens at 10 MHz. One of the challenges is the presence of multiple echoes at the boundary of the composite layers called structural noise. Here, we propose a wavelet transform-based algorithm that is able to detect and characterize defects (depth, size, and shape in 3D plots). This algorithm uses a smart thresholding technique based on the extracted statistical mean and standard deviation of the structural noise. Finally, we use the proposed algorithm to detect and characterize defects in a standard calibration specimen and validate the results by comparing to the designed depth information

An experimental study of the feasibility of phase‐based video magnification for damage detection and localisation in operational deflection shapes

Optical measurements from high‐speed, high‐definition video recordings can be used to define the full‐field dynamics of a structure. By comparing the dynamic responses resulting from both damaged and undamaged elements, structural health monitoring can be carried out, similarly as with mounted transducers. Unlike the physical sensors, which provide point‐wise measurements and a limited number of output channels, high‐quality video recording allows very spatially dense information. Moreover, video acquisition is a noncontact technique. This guarantees that any anomaly in the dynamic behaviour can be more easily correlated to damage and not to added mass or stiffness due to the installed sensors. However, in real‐life scenarios, the vibrations due to environmental input are often so small that they are indistinguishable from measurement noise if conventional image‐based techniques are applied. In order to improve the signal‐to‐noise ratio in low‐amplitude measurements, phase‐based motion magnification has been recently proposed. This study intends to show that model‐based structural health monitoring can be performed on modal data and time histories processed with phase‐based motion magnification, whereas unamplified vibrations would be too small for being successfully exploited. All the experiments were performed on a multidamaged box beam with different damage sizes and angles