230 research outputs found
Tidal stream generators, current state and potential opportunities for condition monitoring
Tidal power industry has made significant progress towards commercialization over the past decade. Significant investments from sector leaders, strong technical progress and positive media coverage have established the credibility of this specific renewable energy source. However, its progress is being retarded by operation and maintenance problems, which results in very low operational availability times, as low as 25 %. This paper presents a literature review of the current state of tidal device operators as well as some commercial tidal turbine condition monitoring solutions. Furthermore, an overview is given of the global tidal activity status (tidal energy market size and geography), the key industry activity and the regulations-standards related with tidal energy industry. Therefore, the main goal of this paper is to provide a bird’s view of the current status of the tidal power industry to serve as a roadmap for the academia regarding the real needs of the tidal power industry
Quantifying Greek rhyme
In this paper we report on Greek Rhyme (GrR), the first freely accessible pilot database on rhyme in Greek poetry. The database contains several poems and is constantly expanding. For the purposes of this project, specially designed algorithms have been constructed for automatic rhyme detection and classification according to numerous parameters, including rich and imperfect rhymes, among others. GrR facilitates the study of patterns of rhyme within the work of a single poet and enables comparison with the rhyme schemata found in other poets. It is thus an invaluable tool for both linguists and philologists with interest in poetic meter
Aircraft Skin Inspections: Towards a New Model for Dent Evaluation
Aircraft maintenance, repair and overhaul (MRO) industry is gradually
switching to 3D scanning for dent inspection. High-accuracy devices allow quick
and repeatable measurements, which translate into efficient reporting and more
objective damage evaluations. However, the potential of 3D scanners is far from
being exploited. This is due to the traditional way in which the structural
repair manual (SRM) deals with dents, that is, considering length, width and
depth as the only relevant measures. Being equivalent to describing a dent
similarly to a "box", the current approach discards any information about the
actual shape. This causes high degrees of ambiguity, with very different shapes
(and corresponding fatigue life) being classified as the same, and nullifies
the effort of acquiring such great amount of information from high-accuracy 3D
scanners. In this paper a -parameter model is proposed to describe the
actual dent shape, thus enabling the exploitation of the high fidelity data
produced by 3D scanners. The compact set of values can then be compared against
historical data and structural evaluations based on the same model
Thermographic non-destructive evaluation for natural fiber-reinforced composite laminates
Natural fibers, including mineral and plant fibers, are increasingly used for polymer composite materials due to their low environmental impact. In this paper, thermographic non-destructive inspection techniques were used to evaluate and characterize basalt, jute/hemp and bagasse fibers composite panels. Different defects were analyzed in terms of impact damage, delaminations and resin abnormalities. Of particular interest, homogeneous particleboards of sugarcane bagasse, a new plant fiber material, were studied. Pulsed phase thermography and principal component thermography were used as the post-processing methods. In addition, ultrasonic C-scan and continuous wave terahertz imaging were also carried out on the mineral fiber laminates for comparative purposes. Finally, an analytical comparison of different methods was give
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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
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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
Prognostic and health management of critical aircraft systems and components: an overview
This article belongs to the Special Issue Feature Papers in Fault Diagnosis & Sensors 2023Prognostic and health management (PHM) plays a vital role in ensuring the safety and reliability of aircraft systems. The process entails the proactive surveillance and evaluation of the state and functional effectiveness of crucial subsystems. The principal aim of PHM is to predict the remaining useful life (RUL) of subsystems and proactively mitigate future breakdowns in order to minimize consequences. The achievement of this objective is helped by employing predictive modeling techniques and doing real-time data analysis. The incorporation of prognostic methodologies is of utmost importance in the execution of condition-based maintenance (CBM), a strategic approach that emphasizes the prioritization of repairing components that have experienced quantifiable damage. Multiple methodologies are employed to support the advancement of prognostics for aviation systems, encompassing physics-based modeling, data-driven techniques, and hybrid prognosis. These methodologies enable the prediction and mitigation of failures by identifying relevant health indicators. Despite the promising outcomes in the aviation sector pertaining to the implementation of PHM, there exists a deficiency in the research concerning the efficient integration of hybrid PHM applications. The primary aim of this paper is to provide a thorough analysis of the current state of research advancements in prognostics for aircraft systems, with a specific focus on prominent algorithms and their practical applications and challenges. The paper concludes by providing a detailed analysis of prospective directions for future research within the field.European Union funding: 95568
Thermography data fusion and non-negative matrix factorization for the evaluation of cultural heritage objects and buildings
The application of the thermal and infrared technology in different areas of research is considerably increasing. These applications involve nondestructive testing, medical analysis (computer aid diagnosis/detection—CAD), and arts and archeology, among many others. In the arts and archeology field, infrared technology provides significant contributions in terms of finding defects of possible impaired regions. This has been done through a wide range of different thermographic experiments and infrared methods. The proposed approach here focuses on application of some known factor analysis methods such as standard nonnegative matrix factorization (NMF) optimized by gradient-descent-based multiplicative rules (SNMF1) and standard NMF optimized by nonnegative least squares active-set algorithm (SNMF2) and eigen-decomposition approaches such as principal component analysis (PCA) in thermography, and candid covariance-free incremental principal component analysis in thermography to obtain the thermal features. On the one hand, these methods are usually applied as preprocessing before clustering for the purpose of segmentation of possible defects. On the other hand, a wavelet-based data fusion combines the data of each method with PCA to increase the accuracy of the algorithm. The quantitative assessment of these approaches indicates considerable segmentation along with the reasonable computational complexity. It shows the promising performance and demonstrated a confirmation for the outlined properties. In particular, a polychromatic wooden statue, a fresco, a painting on canvas, and a building were analyzed using the above-mentioned methods, and the accuracy of defect (or targeted) region segmentation up to 71.98%, 57.10%, 49.27%, and 68.53% was obtained, respectively
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