Immovilli et al., 2009 - Google Patents
Detection of generalized-roughness bearing fault by spectral-kurtosis energy of vibration or current signalsImmovilli et al., 2009
View PDF- Document ID
- 14978041389242464417
- Author
- Immovilli F
- Cocconcelli M
- Bellini A
- Rubini R
- Publication year
- Publication venue
- IEEE Transactions on Industrial Electronics
External Links
Snippet
Generalized roughness is the most common damage occurring to rolling bearings. It produces a frequency spreading of the characteristic fault frequencies, thus making it difficult to detect with spectral or envelope analysis. A statistical analysis of typical bearing faults is …
- 238000001514 detection method 0 title description 11
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/34—Testing dynamo-electric machines
- G01R31/343—Testing dynamo-electric machines in operation
-
- 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
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
- G01M13/04—Testing of bearings
- G01M13/045—Testing of bearings by acoustic or vibration analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/34—Testing dynamo-electric machines
- G01R31/346—Testing of armature or field windings
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H1/00—Measuring characteristics of vibrations in solids by using direct conduction to the detector
- G01H1/003—Measuring characteristics of vibrations in solids by using direct conduction to the detector of rotating machines
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/02—Testing of electric apparatus, lines or components, for short-circuits, discontinuities, leakage of current, or incorrect line connection
- G01R31/024—Arrangements for indicating continuity or short-circuits in electric apparatus or lines, leakage or ground faults
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Immovilli et al. | Detection of generalized-roughness bearing fault by spectral-kurtosis energy of vibration or current signals | |
| Bellini et al. | Diagnosis of bearing faults of induction machines by vibration or current signals: A critical comparison | |
| US8994359B2 (en) | Fault detection based on current signature analysis for a generator | |
| Önel et al. | Induction motor bearing failure detection and diagnosis: Park and concordia transform approaches comparative study | |
| Siddiqui et al. | Health monitoring and fault diagnosis in induction motor-a review | |
| Pandarakone et al. | Distinct fault analysis of induction motor bearing using frequency spectrum determination and support vector machine | |
| Amirat et al. | EEMD-based notch filter for induction machine bearing faults detection | |
| Choqueuse et al. | Current frequency spectral subtraction and its contribution to induction machines’ bearings condition monitoring | |
| Elbouchikhi et al. | Motor current signal analysis based on a matched subspace detector | |
| Gong et al. | Bearing fault diagnosis for direct-drive wind turbines via current-demodulated signals | |
| Benbouzid | A review of induction motors signature analysis as a medium for faults detection | |
| Elbouchikhi et al. | Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation | |
| Vitek et al. | Detection of eccentricity and bearings fault using stray flux monitoring | |
| Rosero et al. | Fault Detection in dynamic conditions by means of Discrete Wavelet Decomposition for PMSM running under Bearing Damage | |
| Önel et al. | Detection of bearing defects in three-phase induction motors using Park’s transform and radial basis function neural networks | |
| Trajin et al. | Comparison between vibration and stator current analysis for the detection of bearing faults in asynchronous drives | |
| Haddad et al. | Outer race bearing fault detection in induction machines using stator current signals | |
| Amirat et al. | Performance analysis of an EEMD-based Hilbert Huang transform as a bearing failure detector in wind turbines | |
| Ciszewski | Induction motor bearings diagnostic indicators based on MCSA and normalized triple covariance | |
| Irfan et al. | An intelligent fault diagnosis of induction motors in an arbitrary noisy environment | |
| Nasiri et al. | Ball-bearing fault detection of squirrel-cage induction motors based on single-phase stator current using wavelet packet decomposition and statistical features | |
| PK et al. | Healthy monitoring and fault detection outer race bearing in induction motor using stator current | |
| Iorgulescu et al. | Vibration and current monitoring for fault’s diagnosis of induction motors | |
| Othman et al. | Vibration and acoustic emission signal monitoring for detection of induction motor bearing fault | |
| Bellini et al. | Diagnosis of mechanical faults by spectral kurtosis energy |