V
Vincent Choqueuse
Researcher at Centre national de la recherche scientifique
Publications - 62
Citations - 1655
Vincent Choqueuse is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Fault detection and isolation & Fault (power engineering). The author has an hindex of 22, co-authored 56 publications receiving 1424 citations. Previous affiliations of Vincent Choqueuse include École nationale d'ingénieurs de Brest.
Papers
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Diagnosis of Three-Phase Electrical Machines Using Multidimensional Demodulation Techniques
TL;DR: By exploiting the configuration of three-phase machines, it is demonstrated that the demodulation can be efficiently performed with low-complexity multidimensional transforms such as the Concordia transform (CT) or the principal component analysis (PCA).
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An Efficient Hilbert–Huang Transform-Based Bearing Faults Detection in Induction Machines
TL;DR: In this article, the authors proposed a bearing fault detection method based on stator currents analysis using the Hilbert-Huang transform (HHT) and empirical mode decomposition (EMD).
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Induction machine faults detection using stator current parametric spectral estimation
TL;DR: In this article, a parametric spectral estimator based on the maximum likelihood estimator (MLE) was proposed for fault detection in electrical machines, which is evaluated using simulation signals, issued from a coupled electromagnetic circuits approach-based simulation tool.
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Blind Recognition of Linear Space–Time Block Codes: A Likelihood-Based Approach
TL;DR: This paper deals with the blind recognition of the space-time block coding (STBC) scheme used in multiple-input-multiple-output (MIMO) communication systems and proposes three maximum-likelihood (ML)-based approaches for STBC classification: the optimal classifier, the second-order statistic (SOS) classifiers, and the code parameter (CP) classifier.
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Current Frequency Spectral Subtraction and Its Contribution to Induction Machines’ Bearings Condition Monitoring
TL;DR: In this article, a stator current spectral subtraction method was proposed to monitor induction machine bearings by means of short-time Fourier transform or discrete wavelet transform, which is performed using short-term Fourier Transform (STFT) or Discrete Wavelet Transform (DWT).