The Experts below are selected from a list of 288 Experts worldwide ranked by ideXlab platform
Rodrigo Amezcua-correa - One of the best experts on this subject based on the ideXlab platform.
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Author Correction: High-Performance Vector bending and orientation distinguishing curvature sensor based on asymmetric coupled multi-core fibre.
Scientific reports, 2021Co-Authors: Oskar Arrizabalaga, Qi Sun, Martynas Beresna, Timothy Lee, Joseba Zubia, Javier Velasco Pascual, Idurre Sáez De Ocáriz, Axel Schülzgen, Jose Enrique Antonio-lopez, Rodrigo Amezcua-correaAbstract:An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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High-Performance Vector bending and orientation distinguishing curvature sensor based on asymmetric coupled multi-core fibre.
Scientific reports, 2020Co-Authors: Oskar Arrizabalaga, Qi Sun, Martynas Beresna, Timothy Lee, Joseba Zubia, Javier Velasco Pascual, Idurre Sáez De Ocáriz, Axel Schülzgen, Jose Enrique Antonio-lopez, Rodrigo Amezcua-correaAbstract:Fibre optic technology is rapidly evolving, driven mainly by telecommunication and sensing applications. Excellent reliability of the manufacturing processes and low cost have drawn ever increasing attention to fibre-based sensors, e.g. for studying mechanical response/limitations of aerospace composite structures. Here, a Vector bending and orientation distinguishing curvature sensor, based on asymmetric coupled multi-core fibre, is proposed and experimentally demonstrated. By optimising the mode coupling effect of a seven core multi-core fibre, we have achieved a sensitivity of - 1.4 nm/° as a Vector bending sensor and - 17.5 nm/m-1 as a curvature sensor. These are the highest sensitivities reported so far, to the best of our knowledge. In addition, our sensor offers several advantages such as repeatability of fabrication, wide operating range and small size and weight which benefit its sensing applications.
Oskar Arrizabalaga - One of the best experts on this subject based on the ideXlab platform.
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Author Correction: High-Performance Vector bending and orientation distinguishing curvature sensor based on asymmetric coupled multi-core fibre.
Scientific reports, 2021Co-Authors: Oskar Arrizabalaga, Qi Sun, Martynas Beresna, Timothy Lee, Joseba Zubia, Javier Velasco Pascual, Idurre Sáez De Ocáriz, Axel Schülzgen, Jose Enrique Antonio-lopez, Rodrigo Amezcua-correaAbstract:An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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High-Performance Vector bending and orientation distinguishing curvature sensor based on asymmetric coupled multi-core fibre.
Scientific reports, 2020Co-Authors: Oskar Arrizabalaga, Qi Sun, Martynas Beresna, Timothy Lee, Joseba Zubia, Javier Velasco Pascual, Idurre Sáez De Ocáriz, Axel Schülzgen, Jose Enrique Antonio-lopez, Rodrigo Amezcua-correaAbstract:Fibre optic technology is rapidly evolving, driven mainly by telecommunication and sensing applications. Excellent reliability of the manufacturing processes and low cost have drawn ever increasing attention to fibre-based sensors, e.g. for studying mechanical response/limitations of aerospace composite structures. Here, a Vector bending and orientation distinguishing curvature sensor, based on asymmetric coupled multi-core fibre, is proposed and experimentally demonstrated. By optimising the mode coupling effect of a seven core multi-core fibre, we have achieved a sensitivity of - 1.4 nm/° as a Vector bending sensor and - 17.5 nm/m-1 as a curvature sensor. These are the highest sensitivities reported so far, to the best of our knowledge. In addition, our sensor offers several advantages such as repeatability of fabrication, wide operating range and small size and weight which benefit its sensing applications.
Antonio J. Marques Cardoso - One of the best experts on this subject based on the ideXlab platform.
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High-Performance Vector control without AC phase current sensors for induction motor drives: Simulation and real-time implementation
ISA transactions, 2020Co-Authors: Younes Azzoug, Mohamed Sahraoui, Remus Pusca, Tarek Ameid, Raphael Romary, Antonio J. Marques CardosoAbstract:Abstract The main purpose of this paper is to develop a high-level Performance, and low-cost current sensorless control strategy for Induction Motor (IM) drives. Therefore, a new phase-current regeneration method, for current sensorless Vector control in induction motor drives is introduced. The idea is based on the reconfiguration of the Luenberger adaptive observer for currents estimation, using the information provided by the dc-link voltage sensor. The basis of the proposed control and the theoretical study of the modified adaptive observer are presented. Several simulation and experimental tests were performed on an induction motor of 1.1 kW working under different operating conditions. The obtained results prove and testify the relevance, workability, and practicability of the suggested currents sensorless Vector control strategy.
Peter F. Swaszek - One of the best experts on this subject based on the ideXlab platform.
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Unrestricted multistage Vector quantizers
IEEE Transactions on Information Theory, 1992Co-Authors: Peter F. SwaszekAbstract:A low-complexity, high-Performance Vector quantization technique for medium-to-high-bit-rate encoding based on multistage (residual) VQ is introduced. The design, a variable-rate version of multistage VQ, is the Vector extension of the piecewise uniform scalar quantizers of P.F. Swaszek and J.B. Thomas (1984), and is related to the piecewise uniform VQs of F. Kuhlmann and J.A. Buckview (1988). Examples for the independent Gaussian and Laplacian sources are included. >
Javier Velasco Pascual - One of the best experts on this subject based on the ideXlab platform.
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Author Correction: High-Performance Vector bending and orientation distinguishing curvature sensor based on asymmetric coupled multi-core fibre.
Scientific reports, 2021Co-Authors: Oskar Arrizabalaga, Qi Sun, Martynas Beresna, Timothy Lee, Joseba Zubia, Javier Velasco Pascual, Idurre Sáez De Ocáriz, Axel Schülzgen, Jose Enrique Antonio-lopez, Rodrigo Amezcua-correaAbstract:An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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High-Performance Vector bending and orientation distinguishing curvature sensor based on asymmetric coupled multi-core fibre.
Scientific reports, 2020Co-Authors: Oskar Arrizabalaga, Qi Sun, Martynas Beresna, Timothy Lee, Joseba Zubia, Javier Velasco Pascual, Idurre Sáez De Ocáriz, Axel Schülzgen, Jose Enrique Antonio-lopez, Rodrigo Amezcua-correaAbstract:Fibre optic technology is rapidly evolving, driven mainly by telecommunication and sensing applications. Excellent reliability of the manufacturing processes and low cost have drawn ever increasing attention to fibre-based sensors, e.g. for studying mechanical response/limitations of aerospace composite structures. Here, a Vector bending and orientation distinguishing curvature sensor, based on asymmetric coupled multi-core fibre, is proposed and experimentally demonstrated. By optimising the mode coupling effect of a seven core multi-core fibre, we have achieved a sensitivity of - 1.4 nm/° as a Vector bending sensor and - 17.5 nm/m-1 as a curvature sensor. These are the highest sensitivities reported so far, to the best of our knowledge. In addition, our sensor offers several advantages such as repeatability of fabrication, wide operating range and small size and weight which benefit its sensing applications.