1,720,967 research outputs found
Data-Driven Fault Diagnosis in a Complex Hydraulic System based on Early Classification
No full textIn this paper, an early time-series classification (ETSC) algorithm is applied to support fault diagnosis in a complex hydraulic system (HS) with several interconnected components. The proposed technique aims at early classifying the state of the system while keeping the loss of classification inaccuracy at the minimum level. In contrast to baseline models that detect the eventual faults at the end of each working cycle, the ETSC model can diagnose any fault type of the HS components before observing the entire working cycle. Indeed, the early classification model successfully achieves a trade-off between the accuracy and the earliness criterion. Experimental results on a realistic HS dataset from the related literature show that the ETSC method can effectively identify different fault types with a higher accuracy and earlier compared to baseline methodologies
A Semi-Supervised Learning Approach for Fault Detection and Diagnosis in Complex Mechanical Systems
No full textThe integration of artificial intelligence in mechanical fault detection and diagnosis (FDD) helps to increase reliability, reduce costs, and improve the overall performance of mechanical systems in Industry 4.0 applications. Most interesting industrial applications nowadays come from dynamic environments where data are generated continuously over time and where the labeled data are scarce and expensive. Therefore, semi-supervised learning (SSL) can be particularly useful in FDD because faults may be rare or difficult to identify, and may not be fully represented in the labeled data. By using a combination of labeled and unlabeled data, SSL can help to identify these rare or difficult-to-detect faults, leading to more effective FDD. In this paper, graph-based SSL relying on label propagation is combined with conventional classification algorithms to detect potential failures in complex mechanical systems. Experimental results on realistic pneumatic and hydraulic systems from the related literature show that the proposed method can effectively enlarge the labeled datasets and interestingly identify different types of non-nominal conditions with higher accuracy compared to baseline methodologies
An adaptive constrained clustering approach for real-time fault detection of industrial systems
No full text
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
An Adaptive Model Predictive Control Approach for Position Tracking and Force Control of a Hydraulic Actuator
No full textThis paper presents an Adaptive Model Predictive Control (AMPC) approach for the position tracking and force control of a hydraulic actuator (HA). Due to its nonlinear dynamics, the iterative linearization paradigm is employed to approximate the HA system by a linear time-varying model. Such a representation is used as the internal plant model of the predictive controller to effectively make predictions on the system state. The effectiveness of the proposed AMPC architecture is shown through numerical experiments addressing the control of a real HA on different scenarios. Finally, a comparative analysis on several values of sampling time, prediction and control horizon is carried out in order to investigate the effect of the parameters tuning on the performance of the closed-loop control system
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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