1,721,113 research outputs found

    Application of a neural network in gas turbine control sensor fault detection

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    In this paper an application of a procedure using a neural network for the detection and isolation of faults modeled by step functions in input-output control sensors of a single shaft industrial gas turbine is presented. The real process is modeled as a linear dynamic system corrupted by stochastic additive noise. The diagnosis system involves dynamic observers and utilizes the neural network in order to classify observer residuals into fault classes

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

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    “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

    ARX Linear Model Set-Up for Fault Diagnosis of Gas Turbine Sensors

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    The diagnosis of gas turbine sensor faults requires models of the system to calculate estimates of the measured output system variables. The model set-up phase is of great importance since the reliability of the diagnostic tool depends on the model accuracy. In the paper two different methodologies of I/O linear model set-up are analyzed and compared to find the more simple and general one. The first methodology consists in obtaining the I/O linear models by directly linearizing the physical laws (system modeling). The second one uses statistical methods (system identification) to calculate model parameters from time series data measured on the machine. The models used are of the ARX (Auto Regressive with external input) type. The number of models and the measured variables correlated by each of them have been determined in order to obtain unambiguous fault signatures for each sensor. The system identification method proves to be more suitable to the system modeling because of its grea..

    A Method for the Diagnosis of Gas Turbine Sensor Faults in Presence of Measurement Noise

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    This paper presents a method for the detection and isolation of single gas turbine sensor faults, in presence of model inaccuracy and measurement noise. The method uses a fault matrix with a column-canonical structure (i.e., each matrix column having the same number of zeroes, but in different positions), in order to obtain the unambiguous fault isolation. The fault matrix was obtained by using a number of ARX (Auto Regressive eXogenous) MISO (Multi-Input/Single-Output) models equal to the number of measured gas turbine outputs, each model calculating an estimate of one measurable output as a function of other inputs or outputs measured on the machine. Moreover, in order to reduce the threshold of fault detection and, therefore, the minimal detectable faults, digital filters were used, applied to the time series of data measured on the machine and computed by the models. Finally, tests were performed in order to find the minimal sensor faults that can be detected and isolated

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We 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

    Application of a neural network in gas turbine control sensor fault detection

    No full text
    An application of a procedure using a neural network for the detection and isolation of faults modeled by step functions in input-output control sensors of a single shaft industrial gas turbine is presented. The real process is modeled as a linear dynamic system corrupted by stochastic additive noise. The diagnosis system involves dynamic observers and utilizes the neural network in order to classify observer residuals into fault classe

    Dispelling the Myths Behind First-author Citation Counts

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    We 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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