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Ricerca della configurazione ottimale dei sensori per sistemi di monitoraggio permanente con incertezza nei dati
Full text linkLe tecniche più avanzate per l’identificazione dinamica e del danno strutturale prevedono l’uso di un sistema di acquisizione per il controllo del comportamento strutturale durante l’intera vita della struttura. Queste sono basate sullo sviluppo di efficienti tecniche numeriche e sullo sviluppo di strumentazioni sempre più sofisticate ed affidabili che permettono alte prestazioni e costi relativamente contenuti. La qualità delle informazioni ottenute però dipende significativamente dal numero di sensori e dalla loro posizione sulla struttura; pertanto risulta di fondamentale importanza la ricerca di una configurazione ottimale per un ridotto numero di sensori, compatibile con i vincoli economici e spaziali, al fine di ottenere il maggior numero di informazioni dai dati misurati e per garantire allo stesso tempo una stima affidabile dei parametri di interesse.
La tesi vuole investigare il problema della ricerca della posizione ottimale dei sensori nell’ambito del monitoraggio strutturale e definire il ruolo degli errori di modello e delle incertezze nei parametri di input sul set-up ottimale.
Nella prima parte del lavoro sono state analizzate differenze ed analogie tra diversi metodi presenti in letteratura quali il Kinetic Energy, l’ Effective Independence, il Driving Point Residue e l’Information Entropy per la determinazione della posizione ottimale dei sensori attraverso esempi numerici, facendo ricorso a casi benchmark come una trave ed un telaio spaziale, oltre che ad una passerella pedonale. I risultati ottenuti dipendono considerevolmente dalla matrice di covarianza dell'errore stimato (legata alle forme modali) e dalla correlazione del segnale (legata alla distanza tra i sensori); pertanto, si sono confrontate definizioni della correlazione del segnale già presenti in letteratura e si è proposta una nuova funzione obiettivo che dipende sia dalla distanza tra i sensori che dalla matrice di forma modale. Per confrontare numericamente la qualità dei risultati ottenuti, sono stati utilizzati diversi criteri, indipendenti uno dall'altro: il determinante della matrice di Fisher, il Modal Assurance Criterion ed il numero di condizionamento.
Il posizionamento dei sensori è uno studio a priori che utilizza dati analitici ottenuti da modelli predittivi del comportamento strutturale quali modelli agli elementi finiti. Nel problema di posizionamento dei sensori, quindi, la soluzione ottimale è affetta da errori ed incertezze, principalmente causati dai limiti del modello numerico nel rappresentare il reale comportamento della struttura (errori di modello) e dall'errore di misura. Questi errori possono modificare la soluzione e quindi limitare l'efficienza del sistema di monitoraggio.
Nella seconda parte del lavoro si è quindi analizzato il ruolo delle incertezze parametriche e di modello nella ricerca della configurazione ottimale dei sensori valutando l'affidabilità e la robustezza della funzione di correlazione proposta precedentemente e confrontandola con le altre metodologie. Sono riportati a titolo esplicativo diversi casi benchmark e un'applicazione su una struttura reale. Si è considerata una passerella pedonale in acciaio a Correggio (RE), di 168m, composta da 5 campate in semplice appoggio di sezione scatolare.
Viene mostrato che la funzione di correlazione proposta è in grado di considerare facilmente una correlazione tra le informazioni dei sensori anche per strutture spaziali; inoltre, i risultati sui casi studio effettuati mostrano che la proposta è in grado di cogliere in modo più accurato anche i modi superiori eventualmente identificabili oltre a quelli definiti in input; può inoltre limitare la variabilità dei risultati nel caso di incertezze nei parametri del modello.Modern technologies for structural safety, system identification and damage detection require controlling systems which monitor the structural behaviour during the whole operating life. These systems are based on the development of efficient numerical techniques for structural identification and on the adoption of increasingly reliable sensors that conjugate limited costs with performance suitable for monitoring purposes. However, the quality of the obtained information significantly depends on the sensor number and position. Several sensor positions can be selected, although economic constraints and spatial restrictions tend to limit the experimental set-up. Thus, it is necessary to optimize the position of a limited number of sensors, in order to obtain the maximum amount of information from the measured data and to assure a reliable evaluation of the parameters of interest.
This work investigates optimal sensor placement problem for structural health monitoring (SHM) and modal testing; the role of model errors and parametric uncertainties in the input data is also considered.
First, a comparison among several sensor placement procedures is presented. Results obtained with reference to numerical examples and case studies such as a simply supported beam, a spatial frame and a real footbridge are reported. Kinetic Energy, Effective Independence, Driving Point Residue and Information Entropy methods are applied. Since results of optimization and placement process considerably depend on both the covariance matrix of prediction error (mode shape dependent) and on the definition of signal correlation (sensor distance dependent), different proposal of the definition of covariance matrix are compared. Then a new proposal depending from both the distance and modal vectors is presented, and results are critically commented.
A measure of the quality of the sensor configurations is necessary in order to numerically compare the obtained results. Independent assessment criteria are then selected to evaluate the suitability of sensor position, such as the determinant of Fisher Information Matrix, a criterion based on the Modal Assurance Criterion, and the so called Condition Number.
As a matter of fact, sensor placement is a priori problem where only analytical data are available, obtained through a Finite Element Model. In a general sensor placement procedure, the optimal positioning estimate is sensitive to errors and uncertainties, mainly due to limitations of the adopted numerical model to represent the behaviour of the real structure (model errors) and the presence of uncertainties in measures whether experimental data are used (measurement errors). Both these uncertainties can alter the optimal locations of sensors and limit the monitoring systems efficiency. Therefore, the role of parametric and model uncertainties in sensor placements is investigated. The reliability and the robustness of the proposed correlation function in the case of model error is tested forcing an alteration (distortion) in a constraint condition, and comparing set-up obtained from different methods. Benchmark examples and an application to a real footbridge are reported. This steel footbridge in Correggio (RE) is 168 m long and it is composed of 5 simple-supported spans. The structure has a box cross-section 3.00 x 2.85 m composed of truss girders.
Results show that the proposed correlation function easily takes into account the spatial correlation in 3D structures; moreover, it allows to identify also higher modes (not given to find the optimal set-up) and it could reduce the variability of results in the case of model uncertainties
Influence of model errors in optimal sensor placement
Full text linkThe paper investigates the role of model errors and parametric uncertainties in optimal or near optimal sensor placements for structural health monitoring (SHM) and modal testing. The near optimal set of measurement locations is obtained by the Information Entropy theory; the results of placement process considerably depend on the so-called covariance matrix of prediction error as well as on the definition of the correlation function. A constant and an exponential correlation function depending on the distance between sensors are firstly assumed; then a proposal depending on both distance and modal vectors is presented. With reference to a simple case-study, the effect of model uncertainties on results is described and the reliability and the robustness of the proposed correlation function in the case of model errors are tested with reference to 2D and 3D benchmark case studies. A measure of the quality of the obtained sensor configuration is considered through the use of independent assessment criteria. In conclusion, the results obtained by applying the proposed procedure on a real 5-spans steel footbridge are described. The proposed method also allows to better estimate higher modes when the number of sensors is greater than the number of modes of interest. In addition, the results show a smaller variation in the sensor position when uncertainties occur
Influence of measurement and model errors in optimal sensor placement for SHM purposes
No full textIn this work, the influence of measurement and model errors in optimal sensor placement is investigated. The sensor placement procedure is based on the Information Entropy theory and the solution of the optimization problem is obtained maximizing the determinant of the so called Fisher Information Matrix (FIM). Results of placement process considerably depend on the so called covariance matrix of prediction error as well as on the definition of the correlation function. The paper thus investigates the role of the covariance matrix and the correlation function in optimal sensor placement. Different proposals on their definition are compared. A constant and an exponential correlation function depending on the distance between sensors are firstly assumed; then a new proposal depending from both the distance and modal vectors is presented. The method is finally applied to a benchmark case study and the effect of model and measurement error on results is described
Dynamic monitoring of the Pasternak footbridge using MEMS-based sensing system
No full textThe aim of this paper is to investigate the dynamic behaviour of a steel curved cable-stayed footbridge using an advanced MEMS-based Structural Health Monitoring system. Experimental campaigns were carried out in July and December to characterize the dynamic behaviour of the footbridge subjected to ambient vibrations and human-induced loading actions and to evaluate the effects of temperature shifts on structural modal properties. The monitoring system is composed of a controller and storage unit and several intelligent bus-connected sensing units that can record both the accelerations along two orthogonal axes and the temperature. The main features of this system are the transmission of data in digital form and its high signal-to-noise ratio in the low and medium-low frequency range. The structural dynamic properties are identified through the classic Enhanced Frequency Domain Decomposition (EFDD) method that is based on the diagonalization of the spectral density matrix. A preliminary FE model of the footbridge is built and the numerical results are compared with the experimental ones
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
Mechanical reprocessing of polyurethane and phenolic foams to increase the sustainability of thermal insulation materials
Full text linkIn this work polyurethane (PU) and phenolic foam (PF) panels were mechanically grinded and incorporated within an expanded polyurethane matrix utilized for thermal insulation, in order to reduce the use of virgin material and to promote a circular re-utilization of recycled materials. As observed by scanning electron microscopy, the formulations containing both recyclates showed a rather homogeneous cell structure, however their presence led to a strong reduction of the closed porosity. This reflected in a slight increase in the thermal conductivity, reaching maximum values of 0.030 W/m∙K in foams with 7.5%wt of PF particles. The introduction of the recyclates slightly improved the thermal stability of the PU foams and led to a general decrease in flexural and compression properties. Cone calorimetry tests demonstrated that the inclusion of PF particles reduced the peak heat release rate up to 28 % compared to neat PU foam, enhancing the fire safety of the insulating panels
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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