Priddy et al., 1993 - Google Patents
Neural networks and fault diagnosis in rotating machineryPriddy et al., 1993
- Document ID
- 17516012887852443854
- Author
- Priddy K
- Lothers M
- Saeks R
- Publication year
- Publication venue
- Proceedings of IEEE Systems Man and Cybernetics Conference-SMC
External Links
Snippet
Neural networks and fault diagnosis in rotating machinery Page 1 Neural Networks and Fault
Diagnosis in Rotating Machinery Kevin L. Priddy, Michael D. Lothers, and Richard E. Saeks
Accurate Automation Corporation 7001 Shallowford Road Chattanooga, TN 37421 …
- 230000001537 neural 0 title abstract description 16
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR
- G01M15/00—Testing of engines
- G01M15/04—Testing of internal-combustion engines, e.g. diagnostic testing of piston engines
- G01M15/12—Testing of internal-combustion engines, e.g. diagnostic testing of piston engines by monitoring vibrations
-
- 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
-
- 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
- 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
- G01R31/28—Testing of electronic circuits, e.g. by signal tracer
-
- 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
- G01M17/00—Testing of vehicles
- G01M17/007—Testing of vehicles of wheeled or endless-tracked vehicles
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Betta et al. | A DSP-based FFT-analyzer for the fault diagnosis of rotating machine based on vibration analysis | |
Goumas et al. | Classification of washing machines vibration signals using discrete wavelet analysis for feature extraction | |
US4352293A (en) | Method of diagnosing vibration of rotary machine | |
CN111521400B (en) | A bearing early fault diagnosis method based on EDM and spectral kurtosis | |
US4435770A (en) | Vibration diagnosing method and apparatus for a rotary machine | |
CA2204195C (en) | An adaptive, on line, statistical method and apparatus for motor bearing fault detection by passive motor current monitoring | |
GB2277151A (en) | Machine monitoring using neural network | |
JPH09113416A (en) | Rolling bearing damage diagnosis method | |
Harris | A Kohonen SOM based, machine health monitoring system which enables diagnosis of faults not seen in the training set | |
De Almeida et al. | New technique for evaluation of global vibration levels in rolling bearings | |
Wegerich et al. | Nonparametric modeling of vibration signal features for equipment health monitoring | |
Betta et al. | A DSP-based FFT-analyzer for the fault diagnosis of rotating machine based on vibration analysis | |
Priddy et al. | Neural networks and fault diagnosis in rotating machinery | |
Maasoum et al. | An autoencoder-based algorithm for fault detection of rotating machines, suitable for online learning and standalone applications | |
CN113790890B (en) | Bearing fault classification method and device based on wavelet packet decomposition weight fuzzy entropy and ELM | |
CN118243382A (en) | Characteristic index for bearing fault diagnosis and degradation tracking | |
Lahdelma et al. | Generalised lp norms in vibration analysis of process equipments | |
Thanagasundram et al. | Autoregressive based diagnostics scheme for detection of bearing faults | |
Lahdelma et al. | Intelligent condition monitoring for lime kilns | |
Kaewkongka et al. | Continuous wavelet transform and neural network for condition monitoring of rotodynamic machinery | |
Xue et al. | Structural fault diagnosis of rotating machinery based on distinctive frequency components and support vector machines | |
Alekseev et al. | Data measurement system of compressor units defect diagnosis by vibration value | |
CN111042802A (en) | Fault diagnosis method, device and system for oil pumping unit | |
Juuso et al. | Advanced condition monitoring for lime kilns | |
KR960000803B1 (en) | The method for checking a rotary machine |