1,720,957 research outputs found
Toward Autonomous LLM-Based AI Agents for Predictive Maintenance: State of the Art, Challenges, and Future Perspectives
Full text linkRecent advances in Large Language Models (LLMs) enable agentic systems that combine perception, reasoning, and action across the enitre Predictive Maintenance (PdM) lifecycle, including machine fault diagnosis. However, the literature on LLM-driven agents for PdM remains fragmented and lacks a unified view on contemporary frameworks such as Model Context Procotol. This paper reviews discriminative, generative, and LLM-based approaches for PdM and consolidates fragmented evidence on LLM-driven AI agents. Namely, it introduces agentic AI concepts for PdM and develops an analysis of potential applications, challenges, and risks in light of agency theory, while mapping drivers and barriers to adoption based on recent evidence from industry analysis. Findings indicate near-term value for information and decision-support agents, while higher autonomy needs stronger governance, benchmarks, and safety evidence
Theory of critical distances: A discussion on concepts and applications
Full text linkTheory of Critical Distances (TCD) collects several methods adopted in failure prediction of components provided with stress concentration features. The idea of evaluating stress effect in a zone rather than in a single point was proposed decades ago but, only thanks to relatively recent works, TCD concepts showed to be a successful extension of Linear Elastic Fracture Mechanics (LEFM), able to assess strength and fatigue life. The increasing computational power has made Finite Element Method (FEM) widespread, hence stress fields can be easily extracted and used as input data for fatigue post-processing and durability analyses. In this scenario, TCD reveals as a powerful tool which, thanks to the introduction of a single material parameter (critical distance, (Formula presented.)), integrates classical fracture models by considering the presence of microscale phenomena acting in fracture process. In this sense, TCD behaves as a link between continuum mechanics and LEFM. Modalities and reasons for this connection to occur are interesting points of further investigations. Literature on TCD and its theoretical-experimental background is quite extended, nevertheless few industrial applications are available in literature to the best of authors’ knowledge. In this paper, an overview of concepts and applications related to TCD are reported highlighting the relevance of theoretical arguments in actual applications
Deep transfer learning for machine diagnosis: From sound and music recognition to bearing fault detection
Full text linkToday’s deep learning strategies require ever‐increasing computational efforts and demand for very large amounts of labelled data. Providing such expensive resources for machine diagnosis is highly challenging. Transfer learning recently emerged as a valuable approach to address these issues. Thus, the knowledge learned by deep architectures in different scenarios can be reused for the purpose of machine diagnosis, minimizing data collecting efforts. Existing research provides evidence that networks pre‐trained for image recognition can classify machine vibrations in the time‐frequency domain by means of transfer learning. So far, however, there has been little discussion about the potentials included in networks pre‐trained for sound recognition, which are inherently suited for time‐frequency tasks. This work argues that deep architectures trained for music recognition and sound detection can perform machine diagnosis. The YAMNet convolutional network was designed to serve extremely efficient mobile applications for sound detection, and it was originally trained on millions of data extracted from YouTube clips. That framework is employed to detect bearing faults for the CWRU dataset. It is shown that transferring knowledge from sound and music recognition to bearing fault detection is successful. The maximum accuracy is achieved using a few hundred data for fine‐tuning the fault diagnosis model
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
Health indicators construction for damage level assessment in bearing diagnostics: A proposal of an energetic approach based on envelope analysis
Full text linkPredictive maintenance strategies are established in the industrial context on account of their benefits in terms of costs abatement and machine failures reduction. Among the available techniques, vibration-based condition monitoring (VBCM) has notably been applied in many bearing fault detection problems. The health indicators construction is a central issue for VBCM, since these features provide the necessary information to assess the current machine condition. However, the relation between vibration data and its sources intimately related to bearing damage is not effortlessly definable from a diagnostic perspective. This study discloses a diagnostic investigation performed both on the vibration signal and on the contact pressure signal that is supposed to be one of main forcing terms in the dynamic equilibrium of the damaged bearing. Envelope analysis and spectral kurtosis (SK) are applied to extract and compare diagnostic features from both signals, referring to the Case Western Reserve University (CWRU) case-study. Namely, health indicators are constructed by means of physical considerations based on the effect of faults on the signal power contents. These indicators show to be promising not only for damage detection but, also, for damage severity assessment. Moreover, they provide an invaluable reading key of the link occurring between the contact pressure path and the vibration response
Design of an Innovative Test Rig for Industrial Bearing Monitoring with Self-Balancing Layout
Full text linkThe remote prognosis and diagnosis of bearings can prevent industrial system failures, but the availability of realistic experimental data, being as close as possible to those detected in industrial applications, is essential to validate the monitoring algorithms. In this paper, an innovative bearing test rig architecture is presented, based on the novel concept of “self-contained box”. The monitoring activity is applicable to a set of four middle-sized bearings simultaneously, while undergoing the independent application of radial and axial loads in order to simulate the behavior of the real industrial machinery. The impact of actions on the platform and supports is mitigated by the so-called “self-contained box” layout, leading to self-balancing of actions within the rotor system. Moreover, the high modularity of this innovative layout allows installing various sized bearings, just changing mechanical adapters. This leads to a reduction of cost as well as of system down-time required to change bearings. The test rig is equipped with suitable instrumentation to develop effective procedures and tools for in-and out-monitoring of the system. An initial characterization of the healthy system is presented
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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