Huang et al., 2018 - Google Patents
Short-time kurtogram for bearing fault feature extraction under time-varying speed conditionsHuang et al., 2018
View PDF- Document ID
- 3445671361353938214
- Author
- Huang H
- Baddour N
- Liang M
- Publication year
- Publication venue
- International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
External Links
Snippet
The kurtogram is a spectral analysis tool used to detect non-stationarities in a signal. It can be effectively used to determine the optimal filter for bearing fault feature extraction from a blurred vibration signal, since the transients of the bearing fault-induced signal can be …
- 238000000605 extraction 0 title abstract description 15
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
- G01R31/12—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
- G01R31/1227—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 of components, parts or materials
- G01R31/1263—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 of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
-
- 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
- G01R31/34—Testing dynamo-electric machines
- G01R31/343—Testing dynamo-electric machines in operation
-
- 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
- G01M13/02—Testing of gearing or of transmission mechanisms
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Hemmati et al. | Roller bearing acoustic signature extraction by wavelet packet transform, applications in fault detection and size estimation | |
Moshrefzadeh et al. | The Autogram: An effective approach for selecting the optimal demodulation band in rolling element bearings diagnosis | |
Cong et al. | Short-time matrix series based singular value decomposition for rolling bearing fault diagnosis | |
Lei et al. | Application of an improved kurtogram method for fault diagnosis of rolling element bearings | |
He et al. | Tunable Q-factor wavelet transform denoising with neighboring coefficients and its application to rotating machinery fault diagnosis | |
Guo et al. | Faulty bearing signal recovery from large noise using a hybrid method based on spectral kurtosis and ensemble empirical mode decomposition | |
Yang et al. | Fault diagnosis of rolling element bearings using basis pursuit | |
Djebala et al. | Rolling bearing fault detection using a hybrid method based on empirical mode decomposition and optimized wavelet multi-resolution analysis | |
Pang et al. | Enhanced singular spectrum decomposition and its application to rolling bearing fault diagnosis | |
Guo et al. | An enhanced modulation signal bispectrum analysis for bearing fault detection based on non-Gaussian noise suppression | |
Patel et al. | Induction motor bearing fault identification using vibration measurement | |
Zhang et al. | Improved local cepstrum and its applications for gearbox and rolling bearing fault detection | |
Huang et al. | Short-time kurtogram for bearing fault feature extraction under time-varying speed conditions | |
CN107941511B (en) | A kind of implementation method of the frequency based on signal Time-frequency Decomposition-kurtosis figure | |
Makowski et al. | Parametric time-frequency map and its processing for local damage detection in rotating machinery | |
Gong et al. | Fault detection for rolling element bearing based on repeated single-scale morphology and simplified sensitive factor algorithm | |
Deng et al. | Fast Cmspogram: An effective new tool for periodic pulse detection | |
CN115436058B (en) | Bearing fault feature extraction method, device, equipment and storage medium | |
Zhang et al. | A joint kurtosis-based adaptive bandstop filtering and iterative autocorrelation approach to bearing fault detection | |
Hemmati et al. | Rolling element bearing condition monitoring using acoustic emission technique | |
Kanneg et al. | A wavelet spectrum technique for machinery fault diagnosis | |
Bertot et al. | Refining Envelope Analysis Methods usingWavelet De-Noising to Identify Bearing Faults | |
Zhang et al. | Fault diagnosis of rolling element bearing using ACYCBD based cross correlation spectrum | |
Yang | The detection of bearing incipient fault with maximal overlap discrete wavelet packet transform and sparse code shrinkage denoising | |
Daga et al. | Fast computation of the autogram for the detection of transient faults |