1,720,967 research outputs found
Control oriented modelling of an integrated attitude and vibration suppression architecture for large space structures
Full text linkThis thesis is divided into two parts. The main focus of the research, namely active vibration control for large flexible spacecraft, is exposed in Part I and, in parallel, the topic of machine learning techniques for modern space applications is described in Part II. In particular, this thesis aims at proposing an end-to-end general architecture for an integrated attitude-vibration control system, starting from the design of structural models to the synthesis of the control laws. To this purpose, large space structures based on realistic missions are investigated as study cases, in accordance with the tendency of increasing the size of the scientific instruments to improve their sensitivity, being the drawback an increase of its overall flexibility. An active control method is therefore investigated to guarantee satisfactory pointing and maximum deformation by avoiding classical stiffening methods. Therefore, the instrument is designed to be supported by an active deployable frame hosting an optimal minimum set of collocated smart actuators and sensors. Different spatial configurations for the placement of the distributed network of active devices are investigated, both at closed-loop and open-loop levels. Concerning closed-loop techniques, a method to optimally place the poles of the system via a Direct Velocity Feedback (DVF) controller is proposed to identify simultaneously the location and number of active devices for vibration control with an in-cascade optimization technique. Then, two general and computationally efficient open-loop placement techniques, namely Gramian and Modal Strain Energy (MSE)-based methods, are adopted as opposed to heuristic algorithms, which imply high computational costs and are generally not suitable for high-dimensional systems, to propose a placement architecture for generically shaped tridimensional space structures. Then, an integrated robust control architecture for the spacecraft is presented as composed of both an attitude control scheme and a vibration control system. To conclude the study, attitude manoeuvres are performed to excite main flexible modes and prove the efficacy of both attitude and vibration control architectures. Moreover, Part II is dedicated to address the problem of improving autonomy and self-awareness of modern spacecraft, by using machine-learning based techniques to carry out Failure Identification for large space structures and improving the pointing performance of spacecraft (both flexible satellite with sloshing models and small rigid platforms) when performing repetitive Earth Observation manoeuvres
An Experimental-Data-Driven Deep Learning Strategy for Structural Health Monitoring of a Plate in Acoustic Fields
No full textDetecting damages and degradation of aerospace components is crucial to guarantee mission safety and reliability, and to reduce costs and maintenance time. A structural health monitoring architecture, based on a Deep Learning approach, is introduced to analyze the vibration response acquired by accelerometers and investigate the system sensitivity to the loosening of bolts on a double-end constrained plate. Different boundary conditions are realized and a vibration signals database is created by subjecting the plate to several acoustic fields. The system is then trained and tested on the collected experimental data. Results suggest that the proposed approach is promising to detect potential modifications in the plate clamping conditions
Learning-based control scheme to deploy modular space structures
No full textMany space activities could benefit by learning from the available on-orbit data collected during the mission. An effective improvement in control system performance and autonomy can be obtained implementing learning-based strategies, opportunely modified to adapt themselves to specific mission requirements. Growing interest is currently being addressed to in-space assembly and deploy operations worldwide. Due to the repetitive nature of space structures geometry and assembling procedure, these missions could benefit from the data collected during previous phases. In this sense, the Iterative Learning Control (ILC) appears to be a promising tool for the purpose. The proposed paper explores the possibility of its application to space deployable systems. In particular, this study focusses on the application of ILC to those foldable systems that have a repetitive modular structure, in order to track the same deployment trajectory for each module. In this scenario, the ILC can cope with the uncertainties in the model using the deploying information originated by the previous extended modules. Thus, the control system can be considered as an online supporting signal co-operating with a traditional feedback controller to achieve better deploying performance. The system is able to learn from the past experience, reducing the tracking error of the modules belonging to the successive iteration
A Study on Structural Health Monitoring of a Large Space Antenna via Distributed Sensors and Deep Learning
Full text linkMost modern Earth and Universe observation spacecraft are now equipped with large lightweight and flexible structures, such as antennas, telescopes, and extendable elements. The trend of hosting more complex and bigger appendages, essential for high-precision scientific applications, made orbiting satellites more susceptible to performance loss or degradation due to structural damages. In this scenario, Structural Health Monitoring strategies can be used to evaluate the health status of satellite substructures. However, in particular when analysing large appendages, traditional approaches may not be sufficient to identify local damages, as they will generally induce less observable changes in the system dynamics yet cause a relevant loss of payload data and information. This paper proposes a deep neural network to detect failures and investigate sensor sensitivity to damage classification for an orbiting satellite hosting a distributed network of accelerometers on a large mesh reflector antenna. The sensors-acquired time series are generated by using a fully coupled 3D simulator of the in-orbit attitude behaviour of a flexible satellite, whose appendages are modelled by using finite element techniques. The machine learning architecture is then trained and tested by using the sensors’ responses gathered in a composite scenario, including not only the complete failure of a structural element (structural break) but also an intermediate level of structural damage. The proposed deep learning framework and sensors configuration proved to accurately detect failures in the most critical area or the structure while opening new investigation possibilities regarding geometrical properties and sensor distribution
Thermal and mechanical design and test campaign results of a single-piece structure for the URSA MAIOR nanosatellite
No full textThe Sapienza Space Systems and Space Surveillance Laboratory (S5Lab) of La Sapienza University of Rome is involved in the development and manufacturing of the nano-satellite URSA MAIOR (University of Rome la SApienza Micro Attitude In ORbit testing), a 3U CubeSat selected in the framework of QB50 mission, an FP7 project led by the Von Karman Institute of Fluid Dynamics with the aim to demonstrate the possibility of launching a network of 50 CubeSats intended for measuring and analyzing the lower thermosphere. The nano-satellite, scheduled for launch from July 2016 on, carries a multi Needle Langmuir Probe (mNLP) science unit, used to determine the electron temperature and density and the electric potential of plasma, an Attitude Determination and Control System (ADCS) realized by Surrey Space Centre and two experiments: a polymeric drag sail for nano-satellites deorbiting and an innovative cold-gas MEMS (Micro Electro Mechanical System) micro-thruster for attitude control of nano-satellites, developed at the Sapienza Aerospace Research Centre (CRAS). Both the on-board computers and the structure have been designed, manufactured and tested at the local facilities. The structure subsystem is realized from a 100mm × 100mm square aluminium profile to enhance the thermal conductivity and the mechanical properties. The profile le is properly machined to reduce the overall weight while preserving the thermal conductivity features and the structural stiffness. This paper outlines and compares the results from thermal and mechanical analysis and test campaigns. In particular, a PSD (Power Spectral Density) frequency analysis, used to evaluate the stress suffered by the satellite during the launch, is performed. Furthermore, a (1g) sine sweep 5-400Hz test allows evaluating the natural frequency of the structure and a random vibration test allows comparing real results to FEM analysis
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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