47 research outputs found

    Intelligent Health Monitoring of Machine Bearings Based on Feature Extraction

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    This document is the Accepted Manuscript of the following article: Mohammed Chalouli, Nasr-eddine Berrached, and Mouloud Denai, ‘Intelligent Health Monitoring of Machine Bearings Based on Feature Extraction’, Journal of Failure Analysis and Prevention, Vol. 17 (5): 1053-1066, October 2017. Under embargo. Embargo end date: 31 August 2018. The final publication is available at Springer via DOI: https://doi.org/10.1007/s11668-017-0343-y.Finding reliable condition monitoring solutions for large-scale complex systems is currently a major challenge in industrial research. Since fault diagnosis is directly related to the features of a system, there have been many research studies aimed to develop methods for the selection of the relevant features. Moreover, there are no universal features for a particular application domain such as machine diagnosis. For example, in machine bearing fault diagnosis, these features are often selected by an expert or based on previous experience. Thus, for each bearing machine type, the relevant features must be selected. This paper attempts to solve the problem of relevant features identification by building an automatic fault diagnosis process based on relevant feature selection using a data-driven approach. The proposed approach starts with the extraction of the time-domain features from the input signals. Then, a feature reduction algorithm based on cross-correlation filter is applied to reduce the time and cost of the processing. Unsupervised learning mechanism using K-means++ selects the relevant fault features based on the squared Euclidian distance between different health states. Finally, the selected features are used as inputs to a self-organizing map producing our health indicator. The proposed method is tested on roller bearing benchmark datasets.Peer reviewe

    Experimental and Numerical Characterization of PFRP Structural Elements with Stiffened Web-Flange Junctions

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    The research presented herein pertains to the experimental characterization and numerical simulation of the behavior of pultruded Glass Fiber-Reinforced Polymer (GFRP) structural elements, with specific attention devoted to enhancing ultimate capacity of the Web-Flange Junctions (WFJs). An experimental campaign, performed on as-manufactured I-beam specimens is conducted to serve as a baseline for comparing behavior of pultruded GFRP members with the proposed stiffening strategy. The specimens were produced through the addition of external elements, using bonded L-shaped profiles with variable lengths that were installed in the proximity of the WFJ zone of the I-beams. The experimental tests aimed at highlighting the inherent premature failure that potentially occurs at the WFJ as a result of lack of reinforcement continuity between the flanges and the web that are required to withstand localized radial stress concentration at these locations. To this end, the top flanges of the thin-walled GFRP I-beams were clamped while a localized concentrated load was applied on the bottom flange by means of a steel jaw. Two sets of tests were performed, namely Mid-Point (MP) and End-Point (EP), according to the location of the applied load that caused delamination, and eventually separation of the bottom flange from the web. Failure modes observed in the tests, together with experimental load–displacement curves, are used to investigate the influence of external stiffeners length on the ultimate strength and stiffness of the I-beams. In executing the tests, Digital Image Correlation (DIC) techniques were used to track the spatial distribution of the deformation in the elements. Based on the results of the experimental campaign, a numerical investigation was conducted, to characterize the influence of different stiffeners’ arrangements on the mechanical response of the GFRP elements. The computational model was validated by comparing the observed response, both in terms of measured force–displacement curves, and bi-dimensional displacement maps obtained by means of the DIC technique. Numerical results highlighted the importance and influence of an explicit representation of the mechanical response of the bonding agent (i.e., the epoxy resin used to attach the stiffeners to the I-beams) to correctly characterize the deformation behavior of the strengthened WFJs. © 2022 Elsevier Lt

    Effect of phototherapy on eosinophils count in neonatal hyperbilirubinemia (cross-sectional study)

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    Abstract Background Neonatal jaundice is a common disorder in neonates. Phototherapy is associated with various side effects despite being safe. This research aimed to determine the impact of phototherapy (PT) on eosinophil levels in neonates treated for unconjugated hyperbilirubinemia. Methods In this cross-sectional prospective study, icteric neonates admitted to the Neonatal Intensive Care Unit (NICU) of Abo-Elreesh Child Hospital, Cairo University, from July 2020 to June 2021 were assessed. Laboratory data, including serum bilirubin and blood cell differentiation for eosinophils before and after phototherapy, were collected, and demographic data like age, gender, gestational age, and duration of phototherapy were taken. Results Two hundred neonates were included in this study. Hyperbilirubinemia was most frequently related to ABO group incompatibility (44.5%). After phototherapy, total serum bilirubin and neutrophil levels were significantly decreased, and platelet levels were significantly increased. Eosinophil count and percent were significantly increased (p < 0.001) following phototherapy. A statistically significant positive correlation was found between eosinophil count before and after PT (r = 0.583, p < 0.001) and between eosinophil percent before and after PT (r = 0.617, p < 0.001). Conclusion Serum eosinophils were increased after phototherapy in icteric neonates with hyperbilirubinemia
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