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Rene de Jesus Romero-Troncoso

Researcher at Autonomous University of Queretaro

Publications -  224
Citations -  5686

Rene de Jesus Romero-Troncoso is an academic researcher from Autonomous University of Queretaro. The author has contributed to research in topics: Induction motor & Condition monitoring. The author has an hindex of 35, co-authored 220 publications receiving 4441 citations. Previous affiliations of Rene de Jesus Romero-Troncoso include Universidad de Guanajuato.

Papers
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Journal ArticleDOI

Detection and Classification of Single and Combined Power Quality Disturbances Using Neural Networks

Martin Valtierra-Rodriguez, +3 more
- 01 May 2014 - 
TL;DR: A new dual neural-network-based methodology to detect and classify single and combined PQ disturbances is proposed, consisting of an adaptive linear network for harmonic and interharmonic estimation that allows computing the root-mean-square voltage and total harmonic distortion indices.
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The Application of High-Resolution Spectral Analysis for Identifying Multiple Combined Faults in Induction Motors

Arturo Garcia-Perez, +3 more
- 11 Apr 2011 - 
TL;DR: Results show the methodology potentiality as a deterministic detection technique that is suited for detecting multiple features where the fault-related frequencies are very close to those analytically reported in literature.
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Techniques and methodologies for power quality analysis and disturbances classification in power systems: a review

David Granados-Lieberman, +4 more
- 28 Mar 2011 - 
TL;DR: A review of techniques and methodologies developed for power quality analysis and power disturbance classification is presented in this article, in order to show their major characteristics, such as harmonics, sags, swells etc.
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Methodology for fault detection in induction motors via sound and vibration signals

Paulo Antonio Delgado-Arredondo, +5 more
- 15 Jan 2017 - 
TL;DR: In this article, the authors proposed a methodology for detecting faults in induction motors in steady-state operation based on the analysis of acoustic sound and vibration signals, using the Complete Ensemble Empirical Mode Decomposition for decomposing the signal into several intrinsic mode functions.
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Reconfigurable Monitoring System for Time-Frequency Analysis on Industrial Equipment Through STFT and DWT

Eduardo Cabal-Yepez, +4 more
- 01 May 2013 - 
TL;DR: This work presents the design and implementation of a low-cost SoC design that utilizes reconfigurable hardware and a customized embedded processor for time-frequency analysis on industrial equipment through short-time Fourier transform and discrete wavelet transform.