Antonino-Daviu, 2020 - Google Patents
Electrical monitoring under transient conditions: A new paradigm in electric motors predictive maintenanceAntonino-Daviu, 2020
View HTML- Document ID
- 8868119587560432469
- Author
- Antonino-Daviu J
- Publication year
- Publication venue
- Applied Sciences
External Links
Snippet
Featured Application Electric motors condition monitoring. Abstract Electric motors condition monitoring is a field of paramount importance for industry. In recent decades, there has been a continuous effort to investigate new techniques and methods that are able to determine the …
- 230000001052 transient 0 title abstract description 62
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electro-chemical, or magnetic means
- G01N27/72—Investigating or analysing materials by the use of electric, electro-chemical, or magnetic means by investigating magnetic variables
- G01N27/82—Investigating or analysing materials by the use of electric, electro-chemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws
- G01N27/90—Investigating or analysing materials by the use of electric, electro-chemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws using eddy currents
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Antonino-Daviu | Electrical monitoring under transient conditions: A new paradigm in electric motors predictive maintenance | |
Garcia-Calva et al. | Early detection of faults in induction motors—A review | |
Krichen et al. | Motor current signature analysis-based permanent magnet synchronous motor demagnetization characterization and detection | |
Martinez-Herrera et al. | Multiple fault detection in induction motors through homogeneity and kurtosis computation | |
Artigao et al. | Current signature and vibration analyses to diagnose an in-service wind turbine drive train | |
Zamudio-Ramírez et al. | Smart-sensor for the automatic detection of electromechanical faults in induction motors based on the transient stray flux analysis | |
Adouni et al. | Thermal analysis of low-power three-phase induction motors operating under voltage unbalance and inter-turn short circuit faults | |
Cusidó et al. | Signal injection as a fault detection technique | |
Halder et al. | Broken rotor bar fault diagnosis techniques based on motor current signature analysis for induction motor—A review | |
Chang et al. | Induction motors condition monitoring system with fault diagnosis using a hybrid approach | |
Maraaba et al. | Recognition of stator winding inter-turn fault in interior-mount LSPMSM using acoustic signals | |
Wang et al. | Fault identification of broken rotor bars in induction motors using an improved cyclic modulation spectral analysis | |
Garcia-Calva et al. | Early detection of broken rotor bars in inverter-fed induction motors using speed analysis of startup transients | |
Nakamura et al. | A diagnosis method of bearing and stator fault in motor using rotating sound based on deep learning | |
Iglesias-Martínez et al. | Rotor fault detection in induction motors based on time-frequency analysis using the bispectrum and the autocovariance of stray flux signals | |
Liu et al. | A review of modeling and diagnostic techniques for eccentricity fault in electric machines | |
Barmpatza et al. | Study of a combined demagnetization and eccentricity fault in an AFPM synchronous generator | |
Zamudio-Ramirez et al. | Smart-sensors to estimate insulation health in induction motors via analysis of stray flux | |
Freire et al. | Fault detection and condition monitoring of PMSGs in offshore wind turbines | |
Biot-Monterde et al. | Stray flux analysis for the detection and severity categorization of rotor failures in induction machines driven by soft-starters | |
Navarro-Navarro et al. | Current and stray flux combined analysis for the automatic detection of rotor faults in soft-started induction motors | |
Dias et al. | Fuzzy-based statistical feature extraction for detecting broken rotor bars in line-fed and inverter-fed induction motors | |
Areias et al. | Evaluation of current signature in bearing defects by envelope analysis of the vibration in induction motors | |
Tian et al. | Stray flux sensor core impact on the condition monitoring of electrical machines | |
Skora et al. | Selected rolling bearing fault diagnostic methods in wheel embedded permanent magnet brushless direct current motors |