DANIEL MORINIGO-SOTELO

Profesor Titular de Universidad (Associate Professor)

Universidad de Valladolid

Spain

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Daniel Morinigo-Sotelo is an Associate Professor at Universidad de Valladolid, Spain. His research focuses on the diagnosis and monitoring of induction motors, particularly in relation to rotor faults and speed estimation techniques. Recent articles authored by him explore advanced methods such as convolutional neural networks and Kalman filtering for enhancing motor fault detection and performance diagnostics.

DANIEL MORINIGO-SOTELO

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Articles (22)

Cohen’s class bilinear distributions and convolutional neural networks applied to broken rotor bar diagnosis

A Novel Subband Method for Instantaneous Speed Estimation of Induction Motors Under Varying Working Conditions

Diagnosis of rotor asymmetries in induction motors: A steady state approach using rotating frame references

Detecting Particle Contamination in Bearings of Inverter-Fed Induction Motors: A Comparative Evaluation of Monitoring Signals

Broken rotor bar fault detection — A virtual current approach combined with a robust linear parameter-varying observer

Broken Rotor Bar Detection in Closed Loop Inverter Fed Induction Motors Through Time-Frequency Techniques

Very Accurate Time-Frequency Representation of Induction Motors Harmonics for Fault Diagnosis Under Load Variations

New Harmonics for Early Detection of Inter-Turn Faults in Induction Motors During Start-Up

Imbalanced Diagnosis Scheme for Incipient Rotor Faults in Inverter-Fed Induction Motors

Rotor speed estimation for half-broken bar detection in induction motors using Kalman filtering

Detection of Broken Bars in Induction Motors Operating with Closed-Loop Speed Control

Demagnetization Monitoring and Identification in PM Generators With Concentrated Windings During Transient Conditions

Advanced Signal Processing Techniques for Demagnetization Detection in PM Generators at Variable Speed

Multi-Rate Vibration Signal Analysis for Bearing Fault Detection in Induction Machines Using Supervised Learning Classifiers

Demagnetization Monitoring and Identification in PM Generators With Concentrated Windings During Transient Conditions

Early Detection of Faults in Induction Motors—A Review

End-Ring Wear in Deep-Well Submersible Motor Pumps

End-Ring Wear in Deep-Well Submersible Motor Pumps

Analysis of the use of the Hanning Window for the measurement of interharmonic distortion caused by close tones in IEC standard framework.

Spectral Kurtosis Based Methodology for the Identification of Stationary Load Signatures in Electrical Signals from a Sustainable Building

Power Quality Monitoring Strategy Based on an Optimized Multi-Domain Feature Selection for the Detection and Classification of Disturbances in Wind Generators

A Review of Total Harmonic Distortion Factors for the Measurement of Harmonic and Interharmonic Pollution in Modern Power Systems

Collaborators (6)

Francisco Vedreño Santos

Oscar Duque-Perez

Angel Luis Zorita Lamadrid

Angel Arranz-Gimon

Vanessa Fernandez-Cavero

Konstantinos N. Gyftakis

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