Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Papaelias, Mayorkinos

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University of Birmingham

in Cooperation with on an Cooperation-Score of 37%

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Publications (5/5 displayed)

  • 2020Damage monitoring of surface treated steel under severe rolling contact loading conditions1citations
  • 2020Perspectives on railway axle bearing condition monitoring42citations
  • 2020Utilisation of ensemble empirical mode decomposition in conjunction with cyclostationary technique for wind turbine gearbox fault detection13citations
  • 2018Quantitative monitoring of brittle fatigue crack growth in railway steel using acoustic emission23citations
  • 2016Inspection and Structural Health Monitoring techniques for Concentrated Solar Power plants98citations

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  • Dong, Hanshan
  • Junior, Valter Luiz Jantara
  • Stewart, Edward
  • Entezami, Mani
  • Amini, Arash
  • Weston, Paul
  • Roberts, Clive
  • Roshanmanesh, Sanaz
  • Hayati, Farzad
  • Vallely, Patrick
  • Liu, Zipeng
  • Soua, Slim
  • Han, Zhiyuan
  • Shi, Shengrun
  • Muñoz, Carlos Quiterio Gómez
  • Constantinou, Louis
  • Selcuk, Cem
  • Marquez, Fausto Pedro Garcia
  • Gan, Tat Hean
  • Mohimi, Abbas
  • Cheng, Liang
  • Kappatos, Vassilis
  • Kogia, Maria
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article

Utilisation of ensemble empirical mode decomposition in conjunction with cyclostationary technique for wind turbine gearbox fault detection

  • Papaelias, Mayorkinos
  • Roshanmanesh, Sanaz
  • Hayati, Farzad
Abstract

In this paper the application of cyclostationary signal processing in conjunction with Ensemble Empirical Mode Decomposition (EEMD) technique, on the fault diagnostics of wind turbine gearboxes is investigated and has been highlighted. It is shown that the EEMD technique together with cyclostationary analysis can be used to detect the damage in complex and non-linear systems such as wind turbine gearbox, where the vibration signals are modulated with carrier frequencies and are superimposed. In these situations when multiple faults alongside noisy environment are present together, the faults are not easily detectable by conventional signal processing techniques such as FFT and RMS.

Topics
  • impedance spectroscopy
  • decomposition