Rene de Jesus Romero-Troncoso-rekin lankidetzan egindako argitalpenak (21)

2020

  1. Time-frequency analysis based on minimum-norm spectral estimation to detect induction motor faults

    Energies, Vol. 13, Núm. 15

2019

  1. Accurate identification and characterisation of transient phenomena using wavelet transform and mathematical morphology

    IET Generation, Transmission and Distribution, Vol. 13, Núm. 18, pp. 4021-4028

  2. Identification of the electrical load by C-means from non-intrusive monitoring of electrical signals in non-residential buildings

    International Journal of Electrical Power and Energy Systems, Vol. 104, pp. 21-28

  3. Reassigned Short Time Fourier Transform and K-means method for diagnosis of broken rotor bar detection in VSD-fed induction motors

    Advances in Electrical and Computer Engineering, Vol. 19, Núm. 2, pp. 61-68

  4. Short-time transient tracking algorithm for a non-residential facility based on characteristic indices

    Electric Power Systems Research, Vol. 171, pp. 185-193

  5. Study of the harmonic and interharmonic content in electrical signals from photovoltaic generation and their relationship with environmental factors

    Journal of Renewable and Sustainable Energy, Vol. 11, Núm. 4

  6. Vibration, Acoustic Noise Generation and Power Quality in Inverter-fed Induction Motors

    Proceedings of the 2019 IEEE 12th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2019

2018

  1. An Experimental Comparative Evaluation of Machine Learning Techniques for Motor Fault Diagnosis under Various Operating Conditions

    IEEE Transactions on Industry Applications

  2. Hybrid algorithmic approach oriented to incipient rotor fault diagnosis on induction motors

    ISA Transactions, Vol. 80, pp. 427-438

  3. Methodology for Flicker Estimation and Its Correlation to Environmental Factors in Photovoltaic Generation

    IEEE Access, Vol. 6, pp. 24035-24047

2017

  1. Analysis of various inverters feeding induction motors with incipient rotor fault using high-resolution spectral analysis

    Electric Power Systems Research, Vol. 152, pp. 18-26

  2. Discriminating the lubrication condition from the rotor bearing fault in induction motors using Margenau-Hill frequency distribution and artificial neural networks

    Industrial Lubrication and Tribology, Vol. 69, Núm. 6, pp. 970-979

  3. Early Fault Detection in Induction Motors Using AdaBoost with Imbalanced Small Data and Optimized Sampling

    IEEE Transactions on Industry Applications, Vol. 53, Núm. 3, pp. 3066-3075

  4. Evaluation of intelligent approaches for motor diagnosis under changing operational conditions

    Proceedings of the 2017 IEEE 11th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2017

  5. Power consumption analysis of electrical installations at healthcare facility

    Energies, Vol. 10, Núm. 1

2016

  1. Advances in Classifier Evaluation: Novel Insights for an Electric Data-Driven Motor Diagnosis

    IEEE Access, Vol. 4, pp. 7028-7038

  2. Detection and diagnosis of lubrication and faults in bearing on induction motors through STFT

    2016 International Conference on Electronics, Communications and Computers, CONIELECOMP 2016

  3. Rotor unbalance and broken rotor bar detection in inverter-fed induction motors at start-up and steady-state regimes by high-resolution spectral analysis

    Electric Power Systems Research, Vol. 133, pp. 142-148

2015

  1. Supervised diagnosis of induction motor faults: A proposed methodology for an improved performance evaluation

    Proceedings - SDEMPED 2015: IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives

2014

  1. Broken rotor bar detection in VSD-fed induction motors at startup by high-resolution spectral analysis

    Proceedings - 2014 International Conference on Electrical Machines, ICEM 2014