1,720,999 research outputs found
A novel degradation state indicator for steam generators of nuclear power plants
Full text linkWe develop a degradation indicator for nuclear power plants steam generators, based on the use of signal measurements collected by sensors during plant operational transients between two successive maintenance interventions. Given the unavailability of information about the real degradation state during operation, an unsupervised approach is adopted. It consists in the extraction of several features from raw signals and in the selection of those features which best describe the degradation state evolution within a multi-objective optimization framework. The two considered objectives are the monotonicity and trendability of the features
Dynamic Surrogate Modeling for Multistep-ahead Prediction of Multivariate Nonlinear Chemical Processes
No full textThis work proposes a methodology for multivariate dynamic modeling and multistep-ahead prediction of nonlinear systems using surrogate models for the application to nonlinear chemical processes. The methodology provides a systematic and robust procedure for the development of data-driven dynamic models capable of predicting the process outputs over long time horizons. It is based on using surrogate models to construct several nonlinear autoregressive exogenous models (NARX) with each one approximating the future behavior of one process output as a function of the current and previous process inputs and outputs. The developed dynamic models are employed in a recursive schema to predict the process future outputs over several time steps (multistep-ahead prediction). The methodology is able to manage two different scenarios: (1) one in which a set of input-output signals collected from the process is only available for training and (2) another in which a mathematical model of the process is available and can be used to generate specific datasets for training. With respect to the latter, the proposed methodology includes a specific procedure for the selection of training data in dynamic modeling based on design of computer experiment (DOCE) techniques. The proposed methodology is applied to case studies from the process industry presented in the literature. The results show very high prediction accuracies over long time horizons. Also, owing to the flexibility, robustness, and computational efficiency of surrogate modeling, the methodology allows dealing with a wide range of situations, which would be difficult to address using first-principles models
An unsupervised method for the reconstruction of maintenance intervention times
No full textThis paper presents a method for identifying when maintenance interventions have been performed on industrial components. The knowledge of the maintenance intervention times is essential in many situations, such as accident analysis, maintenance planning and development of prognostics and health management models. The proposed method is based on the application of a spectral clustering algorithm to raw data signals collected during the component life. A novel measure of similarity, based on Pearson's correlation coefficient, is used to build the similarity graph. The method is shown able to correctly identify the maintenance intervention times of nuclear power plants steam generators and cutting machines used in the packaging industry
Identification of critical components in the complex technical infrastructure of the large hadron collider using relief feature ranking and support vector machines
Full text linkThis work proposes a data‐driven methodology for identifying critical components in Complex Technical Infrastructures (CTIs), for which the functional logic and/or the system structure functions are not known due the CTI’s complexity and evolving nature. The methodology uses large amounts of CTI monitoring data acquired over long periods of time and under different operating conditions. The critical components are identified as those for which the condition monitoring signals permit the optimal classification of the CTI functioning or failed state. The methodology includes two stages: in the first stage, a feature selection filter method based on the Relief technique is used to rank the monitoring signals according to their importance with respect to the CTI functioning or failed state; the second stage identifies the subset of signals among those highlighted by the Relief technique that are most informative with respect to the CTI state. This identification is performed on the basis of evaluating the performance of a Cost‐Sensitive Support Vector Machine (CS‐SVM) classifier trained with several subsets of the candidate signals. The capabilities of the methodology proposed are assessed through its application to different benchmarks of highly imbalanced datasets, showing performances that are competitive to those obtained by other methods presented in the literature. The methodology is finally applied to the monitoring signals of the Large Hadron Collider (LHC) of the European Organization for Nuclear Research (CERN), a CTI for experiments of physics; the criticality of the identified components has been confirmed by CERN experts
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
A methodology for the identification of the critical components of the electrical distribution network of cern’s large hadron collider
Full text linkWe consider the propagation of disturbances in the electrical distribution network of CERN’s (European Organization for Nuclear Research) Large Hadron Collider (LHC), which is a complex system made of a large number of mutually interconnected and interdependent components. The objective of this work is the identification of the components most critical in the determination of the system operating/failed state. Given the complexity of the system, the identification is to be based on the operational data collected from the monitoring systems. The critical components are sought as those whose condition monitoring signals are most correlated to the system operating/failed state. The method of the identification is based on the use of the Relief feature selection technique to rank the monitoring signals according to their importance with respect to the classification of the system operating/failed state. The criticality of the identified signals and the corresponding components has been validated by the system technical responsibles
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