JOSE ALFONSO ANTONINO-DAVIU

Associate Professor

Universitat Politècnica de València

Spain

Research Interests

Explore related searches

Professors in Spain Professors in Electrical Engineering Electrical Engineering professors in Spain

Contact this professor

ORCID

Google Scholar

About

Dr. Jose Alfonso Antonino-Daviu is an Associate Professor at Universitat Politècnica de València, Spain. His research focuses on advanced diagnostic methods and condition monitoring in electrical machines, as highlighted in his recent articles. Key areas of interest include intelligent fault diagnosis, vibration monitoring, and predictive maintenance techniques for industrial applications.

JOSE ALFONSO ANTONINO-DAVIU

Research Interests

Explore related searches

Contact this professor

About

Articles (30)

Real-Time Digital Twins for Intelligent Fault Diagnosis and Condition-Based Monitoring of Electrical Machines

FEA-Assisted Test Bench to Enhance the Comprehension of Vibration Monitoring in Electrical Machines—A Practical Experiential Learning Case Study

A Novel Harmonic Isolation Method for the Reliable Detection of Rotor Breakages in Induction Motors

Automatic Detection of Corrosion in Ball Bearings of Soft-Started Induction Motors Using the Persistence Spectrum of the Stray-Flux Signals

Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance Motors

Comparative Analysis of the Effect of Rotor Faults in the Performance of Low-Speed High-Torque Machines

A Novel Framework for Industrial Steam Turbine Generator Start-Up Predictive Monitoring Considering Data Limitations

Accurate Criteria for Broken Bar Detection in Induction Motors Based on the Wavelet (Packet) Transform

Detection of Contamination and Failure in the Outer Race on Ceramic, Metallic, and Hybrid Bearings through AI Using Magnetic Flux and Current

Methodology for the Detection of Contamination and Gradual Outer Race Faults in Bearings by Fusion of Statistical Vibration–Current Features and SVM Classifier

FPGA-Microprocessor Based Sensor for Faults Detection in Induction Motors Using Time-Frequency and Machine Learning Methods

Current and Stray Flux Combined Analysis for Sparking Detection in DC Motors/Generators Using Shannon Entropy

A Review of Broadband Frequency Techniques for Insulation Monitoring and Diagnosis in Rotating Electrical Machines

A Virtual Reality Environment Based on Infrared Thermography for the Detection of Multiple Faults in Kinematic Chains

Comprehensive Diagnosis of Localized Rolling Bearing Faults during Rotating Machine Start-Up via Vibration Envelope Analysis

Influence of Rotor Position in the Broadband Impedance Response for SFRA Rotating Machine Diagnosis

Higher-Order Spectral Analysis and Artificial Intelligence for Diagnosing Faults in Electrical Machines: An Overview

Localized Bearing Fault Analysis for Different Induction Machine Start-Up Modes via Vibration Time–Frequency Envelope Spectrum

Start-Up and Steady-State Regimes Automatic Separation in Induction Motors by Means of Short-Time Statistics

Condition Monitoring of Rotating Diodes in Synchronous Machines Through the Exciter Stray Flux Analysis

Automatic Classification of Field Winding Faults in Synchronous Motors Based on Bicoherence Image Segmentation and Higher Order Statistics of Stray Flux Signals

Novel Approaches to Electrical Machine Fault Diagnosis

Condition Evaluation of Steam Turbine Generator Using Minute-Interval Integrated Vibration Signals

FPGA-Flux Proprietary System for Online Detection of Outer Race Faults in Bearings

Methodology for Tool Wear Detection in CNC Machines Based on Fusion Flux Current of Motor and Image Workpieces

Power Disturbance Monitoring through Techniques for Novelty Detection on Wind Power and Photovoltaic Generation

Application of Transient Analysis Techniques to Fault Diagnosis in Low- and Medium-Power Synchronous Machines

A Study on the Effectiveness of Partial Discharge Models for Various Electrical Machines’ Insulation Materials

Gear Wear Detection Based on Statistic Features and Heuristic Scheme by Using Data Fusion of Current and Vibration Signals

Automatic Methodology for Multiple Fault Detection in Induction Motor Under Periodic Low-Frequency Fluctuating Load Based on Stray Flux Signals

Collaborators (16)

J. Alberto Conejero

José Manuel Guerrero

Athanasios Karlis

Alfredo Peris

Larisa Dunai

Carlos Antonio Platero Gaona

Sven Urschel

Toomas Vaimann

Andres Bustillo

Miguel Delgado Prieto

Félix Martínez-Giménez

Konstantinos N. Gyftakis

Sang Bin Lee

Anton Rassõlkin

Ioannis Arvanitakis

Hubert Razik

How do I reach out?

Meet Kite AI