scholarly journals Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1824 ◽  
Author(s):  
Vasileios Tzitzilonis ◽  
Konstantinos Malandrakis ◽  
Luca Zanotti Fragonara ◽  
Jose Angel Gonzalez Domingo ◽  
Nicolas P. Avdelidis ◽  
...  
Keyword(s):  
Path Following ◽  
Detection Algorithm ◽  
Wide Field ◽  
Aircraft Wing ◽  
Detection Algorithms ◽  
Non Invasive ◽  
Aircraft Manufacturing ◽  
Wide Field Of View ◽  
Civil Aircraft ◽  
Non Destructive

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.

Unmanned air vehicles for targeting tasks

2018 ◽  
Vol 233 (5) ◽  
pp. 1926-1934
Author(s):  
Chimpalthradi R Ashokkumar
Keyword(s):  
Unmanned Vehicles ◽  
Obstacle Detection ◽  
The Body ◽  
Wide Field ◽  
Detection Algorithms ◽  
Flight Operations ◽  
Air Vehicle ◽  
Wide Field Of View ◽  
Aerial Vehicle ◽  
Fixed Order

Unmanned aerial vehicle in surveillance and reconnaissance operations are well known with its flight operations confining to the lateral and longitudinal plane where the altitude is maintained constant. The objective in these operations is to have a wide field of view when camera is mounted underneath the aircraft. However, in obstacle detection algorithms as well as in weapon-target assignments by an unmanned combat air vehicle, the sensors such as cameras and radars are mounted along the X direction of the body fixed frame. The unmanned vehicles with such sensor locations are expected to offer obstacle-camera and weapon-target line-of-sight engagements. These operations by the unmanned vehicles are referred as targeting tasks. In this paper, a procedure to use unmanned vehicles as targeting systems in pitch plane is presented with respect to a fixed order controller at the inner loop. The remote pilot's inputs at the outer loop is disengaged and to mimic these inputs, various flight path angles are scheduled thus depicting autonomous characteristics. Illustrations to depict targeting tasks are provided.

STM studies of crystal growth

1991 ◽  
Vol 49 ◽  
pp. 374-375
Author(s):  
M. G. Lagally
Keyword(s):  
Crystal Growth ◽  
Molecular Beam ◽  
Chemical Vapor ◽  
Sputter Deposition ◽  
Field Of View ◽  
Scanning Tunneling ◽  
Wide Field ◽  
Tunneling Microscopy ◽  
Wide Field Of View ◽  
The One

It has been recognized since the earliest days of crystal growth that kinetic processes of all Kinds control the nature of the growth. As the technology of crystal growth has become ever more refined, with the advent of such atomistic processes as molecular beam epitaxy, chemical vapor deposition, sputter deposition, and plasma enhanced techniques for the creation of “crystals” as little as one or a few atomic layers thick, multilayer structures, and novel materials combinations, the need to understand the mechanisms controlling the growth process is becoming more critical. Unfortunately, available techniques have not lent themselves well to obtaining a truly microscopic picture of such processes. Because of its atomic resolution on the one hand, and the achievable wide field of view on the other (of the order of micrometers) scanning tunneling microscopy (STM) gives us this opportunity. In this talk, we briefly review the types of growth kinetics measurements that can be made using STM. The use of STM for studies of kinetics is one of the more recent applications of what is itself still a very young field.

Design and verification of high-precision multi-star simulator with a wide field of view

2020 ◽  
Vol 13 (6) ◽  
pp. 1-9
Author(s):  
XU Hong-gang ◽  
◽  
HAN Bing ◽  
LI Man-li ◽  
MA Hong-tao ◽  
...  
Keyword(s):  
High Precision ◽  
Field Of View ◽  
Wide Field ◽  
Wide Field Of View

scholarly journals Non-Invasive Testing of Physical Systems Using Topological Sensitivity

2021 ◽  
Vol 11 (3) ◽  
pp. 1341
Author(s):  
María Higuera ◽  
José M. Perales ◽  
María-Luisa Rapún ◽  
José M. Vega
Keyword(s):  
Lamb Waves ◽  
General Purpose ◽  
Mathematical Tool ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Topological Sensitivity ◽  
Physical Systems ◽  
Non Invasive ◽  
Active Infrared Thermography ◽  
Non Destructive

A review of available results on non-destructive testing of physical systems, using the concept of topological sensitivity, is presented. This mathematical tool estimates the sensitivity of a set of measurements in some given sensors, distributed along the system, to defects/flaws that produce a degradation of the system. Such degradation manifests itself on the properties of the system. The good performance of this general purpose post-processing method is reviewed and illustrated in some applications involving non-destructive testing. These applications include structural health monitoring, considering both elastodynamic ultrasonic guided Lamb waves and active infrared thermography. Related methods can also be used in other fields, such as diagnosis/prognosis of engineering devices, which is also considered.

scholarly journals Prevalence and Photobiology of Photosynthetic Dinoflagellate Endosymbionts in the Nudibranch Berghia stephanieae

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2200
Author(s):  
Ruben X. G. Silva ◽  
Paulo Cartaxana ◽  
Ricardo Calado
Keyword(s):  
Food Deprivation ◽  
Photosynthetic Efficiency ◽  
Rapid Decrease ◽  
Complete Loss ◽  
Symbiotic Association ◽  
Non Invasive ◽  
Sea Slugs ◽  
Non Destructive ◽  
Over Time

Berghia stephanieae is a stenophagous sea slug that preys upon glass anemones, such as Exaiptasia diaphana. Glass anemones host photosynthetic dinoflagellate endosymbionts that sea slugs ingest when consuming E. diaphana. However, the prevalence of these photosynthetic dinoflagellate endosymbionts in sea slugs appears to be short-lived, particularly if B.stephanieae is deprived of prey that host these microalgae (e.g., during bleaching events impacting glass anemones). In the present study, we investigated this scenario, along with food deprivation, and validated the use of a non-invasive and non-destructive approach employing chlorophyll fluorescence as a proxy to monitor the persistence of the association between sea slugs and endosymbiotic photosynthetic dinoflagellates acquired through the consumption of glass anemones. Berghia stephanieae deprived of a trophic source hosting photosynthetic dinoflagellate endosymbionts (e.g., through food deprivation or by feeding on bleached E. diaphana) showed a rapid decrease in minimum fluorescence (Fo) and photosynthetic efficiency (Fv/Fm) when compared to sea slugs fed with symbiotic anemones. A complete loss of endosymbionts was observed within 8 days, confirming that no true symbiotic association was established. The present work opens a new window of opportunity to rapidly monitor in vivo and over time the prevalence of associations between sea slugs and photosynthetic dinoflagellate endosymbionts, particularly during bleaching events that prevent sea slugs from incorporating new microalgae through trophic interactions.

scholarly journals Design of a Variable-Stiffness Compliant Skin for a Morphing Leading Edge

2021 ◽  
Vol 11 (7) ◽  
pp. 3165
Author(s):  
Zhigang Wang ◽  
Yu Yang
Keyword(s):  
Composite Laminate ◽  
Large Scale ◽  
Design Method ◽  
Leading Edge ◽  
Variable Stiffness ◽  
Manufacturing Constraints ◽  
Aircraft Wing ◽  
Noise Abatement ◽  
Civil Aircraft ◽  
Final Profile

A seamless and smooth morphing leading edge has remarkable potential for noise abatement and drag reduction of civil aircraft. Variable-stiffness compliant skin based on tailored composite laminate is a concept with great potential for morphing leading edge, but the currently proposed methods have difficulty in taking the manufacturing constraints or layup sequence into account during the optimization process. This paper proposes an innovative two-step design method for a variable-stiffness compliant skin of a morphing leading edge, which includes layup optimization and layup adjustment. The combination of these two steps can not only improve the deformation accuracy of the final profile of the compliant skin but also easily and effectively determine the layup sequence of the composite layup. With the design framework, an optimization model is created for a variable-stiffness compliant skin, and an adjustment method for its layups is presented. Finally, the deformed profiles between the directly optimized layups and the adjusted ones are compared to verify its morphing ability and accuracy. The final results demonstrate that the obtained deforming ability and accuracy are suitable for a large-scale aircraft wing.

A dual U-Net algorithm for automating feature extraction from satellite imagery

2021 ◽  
pp. 154851292098354
Author(s):  
Samuel Humphries ◽  
Trevor Parker ◽  
Bryan Jonas ◽  
Bryan Adams ◽  
Nicholas J Clark
Keyword(s):  
Neural Networks ◽  
Object Detection ◽  
Satellite Images ◽  
Detection Algorithm ◽  
Military Operations ◽  
Detection Algorithms ◽  
Us Military ◽  
Standard Product ◽  
Different Types ◽  
Road Intersections

Quick identification of building and roads is critical for execution of tactical US military operations in an urban environment. To this end, a gridded, referenced, satellite images of an objective, often referred to as a gridded reference graphic or GRG, has become a standard product developed during intelligence preparation of the environment. At present, operational units identify key infrastructure by hand through the work of individual intelligence officers. Recent advances in Convolutional Neural Networks, however, allows for this process to be streamlined through the use of object detection algorithms. In this paper, we describe an object detection algorithm designed to quickly identify and label both buildings and road intersections present in an image. Our work leverages both the U-Net architecture as well the SpaceNet data corpus to produce an algorithm that accurately identifies a large breadth of buildings and different types of roads. In addition to predicting buildings and roads, our model numerically labels each building by means of a contour finding algorithm. Most importantly, the dual U-Net model is capable of predicting buildings and roads on a diverse set of test images and using these predictions to produce clean GRGs.

scholarly journals A novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shaheen Syed ◽  
Bente Morseth ◽  
Laila A. Hopstock ◽  
Alexander Horsch
Keyword(s):  
Threshold Value ◽  
Detection Algorithm ◽  
Classification Model ◽  
Type I ◽  
Accelerometer Data ◽  
Deep Convolutional Neural Networks ◽  
Major Drawback ◽  
Wear Time ◽  
Detection Algorithms ◽  
Type Ii Errors

AbstractTo date, non-wear detection algorithms commonly employ a 30, 60, or even 90 mins interval or window in which acceleration values need to be below a threshold value. A major drawback of such intervals is that they need to be long enough to prevent false positives (type I errors), while short enough to prevent false negatives (type II errors), which limits detecting both short and longer episodes of non-wear time. In this paper, we propose a novel non-wear detection algorithm that eliminates the need for an interval. Rather than inspecting acceleration within intervals, we explore acceleration right before and right after an episode of non-wear time. We trained a deep convolutional neural network that was able to infer non-wear time by detecting when the accelerometer was removed and when it was placed back on again. We evaluate our algorithm against several baseline and existing non-wear algorithms, and our algorithm achieves a perfect precision, a recall of 0.9962, and an F1 score of 0.9981, outperforming all evaluated algorithms. Although our algorithm was developed using patterns learned from a hip-worn accelerometer, we propose algorithmic steps that can easily be applied to a wrist-worn accelerometer and a retrained classification model.

scholarly journals Non-Invasive Dengue Diagnostics—The Use of Saliva and Urine for Different Stages of the Illness

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1345
Author(s):  
Mahathir Humaidi ◽  
Wei Ping Tien ◽  
Grace Yap ◽  
Choon Rong Chua ◽  
Lee Ching Ng
Keyword(s):  
Clinical Symptoms ◽  
Detection Algorithm ◽  
Acute Stage ◽  
Serum Samples ◽  
Non Invasive ◽  
Fever Onset ◽  
Dengue Transmission ◽  
Dengue Diagnostics ◽  
Potential Tool

Dengue diagnosis is largely dependent on clinical symptoms and routinely confirmed with laboratory detection of dengue virus in patient serum samples collected via phlebotomy. This presents a challenge to patients not amenable to venipuncture. Non-invasive methods of dengue diagnosis have the potential to enhance the current dengue detection algorithm. In this study, samples from dengue infected patients were collected between January 2012 until September 2012 and September 2013 until December 2013 in two different setups. Panel A samples (blood, urine, and saliva) were collected daily when the 39 patients were hospitalised and during their follow-up visits while Panel B samples (saliva) were collected from 23 patients during the acute stage of dengue. Using DENV PCR on Panel A, from day 2 to day 4 post fever onset, serum showed the best overall positivity followed by saliva and urine (100%/82.1%/67.9%). From day 5 until day 10 post fever onset, serum and urine had similar positivity (67.4%/61.2%), followed by saliva (51.3%). Beyond day 10 post fever onset, DENV was undetectable in sera, but urine and saliva showed 56.8% and 28.6% positivity, respectively. DENV in urine was detectable up until 32 days post fever. Panel B results showed overall sensitivity of 32.4%/36% (RNA/NS1) for DENV detection in saliva. Our results suggest that the urine-based detection method is useful especially for late dengue detection, where DENV is undetected in sera but still detectable in urine. This provides a potential tool for the physician to pick up new cases in an area where there is ongoing dengue transmission and subsequently prompt for intensified vector control activities.

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