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David Camarena-Martinez

Researcher at Universidad de Guanajuato

Publications -  36
Citations -  624

David Camarena-Martinez is an academic researcher from Universidad de Guanajuato. The author has contributed to research in topics: Induction motor & Fault (power engineering). The author has an hindex of 12, co-authored 36 publications receiving 436 citations. Previous affiliations of David Camarena-Martinez include Autonomous University of Queretaro.

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New methodology for modal parameters identification of smart civil structures using ambient vibrations and synchrosqueezed wavelet transform

TL;DR: Numerical and experimental results show accurate identification of the natural frequencies and damping ratios even when the signal is embedded in high-level noise demonstrating that the proposed methodology provides a powerful approach to estimate the modal parameters of a civil structure using ambient vibration excitations.
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Novel Downsampling Empirical Mode Decomposition Approach for Power Quality Analysis

TL;DR: The aim of the proposed iterative downsampling stage fused to the empirical mode decomposition (EMD) method is to extract the fundamental component as the first intrinsic mode function (IMF) to simplify the remaining decomposition.
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Empirical mode decomposition and neural networks on FPGA for fault diagnosis in induction motors.

TL;DR: A novel digital structure to implement the empirical mode decomposition (EMD) for processing nonstationary and nonlinear signals using the full spline-cubic function is presented and the detection and classification results show the effectiveness of the proposed fused techniques.
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Synchrosqueezing transform-based methodology for broken rotor bars detection in induction motors

TL;DR: In this article, a methodology based on Synchrosqueezing transform for detection of broken rotor bars during the startup transient is presented, and a threshold-based stage using the Pearson product-moment correlation coefficient is presented.
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Demodulation Technique for Broken Rotor Bar Detection in Inverter-Fed Induction Motor Under Non-Stationary Conditions

TL;DR: A novel method is proposed to create a new fault pattern that can concentrate the fault harmonic in a specific frequency bandwidth and avoid the spectral leakage by reducing the supply frequency amplitude.