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Your search keyword '"Coppotelli, Giuliano"' showing total 137 results
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137 results on '"Coppotelli, Giuliano"'

1. A Data-driven Approach for Rapid Detection of Aeroelastic Modes from Flutter Flight Test Based on Limited Sensor Measurements

Author

Das, Arpan, Marzocca, Pier, Coppotelli, Giuliano, Levinski, Oleg, and Taylor, Paul

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning, Mathematics - Dynamical Systems, Mathematics - Numerical Analysis
Abstract

Flutter flight test involves the evaluation of the airframes aeroelastic stability by applying artificial excitation on the aircraft lifting surfaces. The subsequent responses are captured and analyzed to extract the frequencies and damping characteristics of the system. However, noise contamination, turbulence, non-optimal excitation of modes, and sensor malfunction in one or more sensors make it time-consuming and corrupt the extraction process. In order to expedite the process of identifying and analyzing aeroelastic modes, this study implements a time-delay embedded Dynamic Mode Decomposition technique. This approach is complemented by Robust Principal Component Analysis methodology, and a sparsity promoting criterion which enables the automatic and optimal selection of sparse modes. The anonymized flutter flight test data, provided by the fifth author of this research paper, is utilized in this implementation. The methodology assumes no knowledge of the input excitation, only deals with the responses captured by accelerometer channels, and rapidly identifies the aeroelastic modes. By incorporating a compressed sensing algorithm, the methodology gains the ability to identify aeroelastic modes, even when the number of available sensors is limited. This augmentation greatly enhances the methodology's robustness and effectiveness, making it an excellent choice for real-time implementation during flutter test campaigns., Comment: 31 pages, 12 figures, submitted in 'Mechanical Systems and Signal processing' journal

Published
2024
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2. Stochastic Modal Appropriation Method: Time Domain Extension for MDOF Systems

Author

Coppotelli, Giuliano, Abdelghani, Maher, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Rainieri, Carlo, editor, Gentile, Carmelo, editor, and Aenlle López, Manuel, editor

Published
2024
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3. DBSCAN-Based Approach for the Automatic Estimate of the Modal Parameters

Author

Sbarra, R., Coppotelli, Giuliano, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Rainieri, Carlo, editor, Gentile, Carmelo, editor, and Aenlle López, Manuel, editor

Published
2024
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4. Monitoring Damage Progression in Wind Turbine Blade Under Fatigue Testing Using Acceleration Measurements

Author

Rossi, Pamela, Tavares, André, Di Lorenzo, Emilio, Cornelis, Bram, Luczak, Marcin, Branner, Kim, Gryllias, Konstantinos, Coppotelli, Giuliano, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Rainieri, Carlo, editor, Gentile, Carmelo, editor, and Aenlle López, Manuel, editor

Published
2024
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7. Real-time system identification for fixed-wing UAV

Author

International Symposium on Space Flight Dynamics (27th : 2019 : Melbourne, Vic.), Di Giandomenico, Federico, Das, Arpan, Altaf, Alaman, Marino, Matthew, Marzocca, Pier, and Coppotelli, Giuliano

Published
2019

16. On the Accuracy of the Modal Parameter Estimates INOMA

Author

Ventura, Carlos E., Motamedi, Mehrtash, Mendler, Alexander, Aenlle-Lopez, Manuel, Paulsen, Thomas Thougaard, Coppotelli, Giuliano, Ferreira Santos, Ilmar, Ventura, Carlos E., Motamedi, Mehrtash, Mendler, Alexander, Aenlle-Lopez, Manuel, Paulsen, Thomas Thougaard, Coppotelli, Giuliano, and Ferreira Santos, Ilmar

Abstract

Modal identification procedures are used to evaluate the vibration properties of structures and can be divided into two branches, that is Input-Output and Output-Only analyses. Several methods are developed to assess the accuracy of the modal parameter estimates in the Input-Output framework, whereas deeper investigation is still needed to assess the confidence boundaries of Output-Only methods. Such accuracy of the estimates is generally given by comparing them with the expected set of modal parameters provided by a numerical model. In this paper, the accuracy of the modal parameters estimated using Output-Only techniques is investigated aided by the use of both time and frequencybased estimating methods coupled to a sensitivity analysis when varying data acquisition settings. Furthermore, insights into the robustness of the estimating process to the measuring chain is obtained from several independent tests and changes to the boundary conditions. Indeed, the experimental boundary conditions are altered by using materials with different elastic properties and different connection configurations. The uncertainties arising from the estimating process and the experimental setup mounting are evaluated for the natural frequencies, damping ratios, mode shapes through several modal assurance criterion formulations. The tests show that the accuracy of modal parameter estimates can be assessed and increased by weighting the similarity between multiple estimates of the same vibration mode. The accuracy depends on mounting configurations due to changes of structural properties. An evaluation of the overall accuracy of the modal parameter estimates finds that the accuracy is increased when information from multiple OMA algorithms is used.

Published
2022

41. Experimental Evaluation of Wind Turbine Rotor Tower Structural Dynamic Interaction

Author

Arsenault, Tyler J., Janoyan, K., Achuthan, A., Marzocca, Pier, Coppotelli, Giuliano, Achuthan, Ajit, and Grappasonni, Chiara

Subjects
Wind power, structural health monitoring, Turbine blade, business.industry, condition monitoring, turbomachine blades, Condition monitoring, Rotor speed, structural dynamics, wind power, Turbine rotor, Turbine, towers, Lattice tower, law.invention, law, characterization, natural frequencies, wind turbines, Harmonics, Environmental science, business, Marine engineering
Abstract

Load characterization for wind turbines has been a major area of study with growing interest due to the upcoming extremely long and flexible turbine blades and towers. it is perhaps the most important task posed to a structural dynamics engineer in the wind energy generation field. What is currently requested by the engineering community are validated methods to evaluate dynamic responses of a wind turbine tower when coupled to an operating wind turbine rotor subjected to typical operational conditions. Such methods can provide insight into the structural health and behavior of a wind turbine system through varying operating conditions, information of paramount importance when it comes to condition based monitoring assessments. Toward this goal the dynamic characterization of an operating small 5kW wind turbine installed on a free-standing lattice tower was carried out by extracting natural frequencies, Operationally Deflected Shapes (ODS) and rotor speed information from data collected, at few discrete tower locations, during field measurements. The in-situ monitoring is used to identify and understand how integer harmonics of the rotor speed (nP), produce harmonic forcing affecting the wind turbine system natural frequencies. The proposed approach is also used to develop wind turbine dynamic characterization techniques which have the potentials to be employed in condition monitoring (CM) system.

Published
2015

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