Kumar et al., 2024 - Google Patents
Additive fault diagnosis techniques in rotor systems: a state-of-the-art reviewKumar et al., 2024
View PDF- Document ID
- 14072541980993338371
- Author
- Kumar P
- Tiwari R
- Publication year
- Publication venue
- Sādhanā
External Links
Snippet
Faults in rotating systems can cause significant damage to the machinery and can result in downtime and production losses. Hence, the timely detection and diagnosis of faults are very important for the smooth running of machines and the assurance of their safety and …
- 238000000034 method 0 title abstract description 371
Classifications
-
- 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
-
- 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
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
- G05B23/024—Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Niu et al. | A systematic study of ball passing frequencies based on dynamic modeling of rolling ball bearings with localized surface defects | |
Bachschmid et al. | Identification of transverse crack position and depth in rotor systems | |
Cong et al. | Experimental validation of impact energy model for the rub–impact assessment in a rotor system | |
Yang et al. | Study for ball bearing outer race characteristic defect frequency based on nonlinear dynamics analysis | |
Hadroug et al. | Fuzzy diagnostic strategy implementation for gas turbine vibrations faults detection: Towards a characterization of symptom–fault correlations | |
Jadhav et al. | Distributed fault diagnosis of rotor-bearing system using dimensional analysis and experimental methods | |
Kumar et al. | A review: multiplicative faults and model-based condition monitoring strategies for fault diagnosis in rotary machines | |
Lees | Vibration problems in machines: diagnosis and resolution | |
Guan et al. | Vibration analysis of shaft misalignment and diagnosis method of structure faults for rotating machinery | |
Espinoza-Sepulveda et al. | Theoretical validation of earlier developed experimental rotor faults diagnosis model | |
Begg et al. | Dynamics modeling for mechanical fault diagnostics and prognostics | |
Vojtko et al. | Examining the effect of alignment of the rotor of the emissions exhaust fan on its operating parameters | |
Salunkhe et al. | Vibration analysis of deep groove ball bearing using finite element analysis and dimension analysis | |
Begg et al. | Dynamic simulation of mechanical fault transition | |
Nail et al. | Gas turbine vibration monitoring based on real data and neuro-fuzzy system | |
Kumar et al. | Additive fault diagnosis techniques in rotor systems: a state-of-the-art review | |
Kalkat et al. | Rotor dynamics analysis of rotating machine systems using artificial neural networks | |
AbdulBary et al. | Fault Diagnosis in Rotating System Based on Vibration Analysis | |
CAstillA-Gutiérrez et al. | Analysis, evaluation and monitoring of the characteristic frequencies of pneumatic drive unit and its bearing through their corresponding frequency spectra and spectral density | |
Bettig et al. | Predictive maintenance using the rotordynamic model of a hydraulic turbine-generator rotor | |
Luo et al. | Detection and quantification of oil whirl instability in a rotor-journal bearing system using a novel dynamic recurrence index | |
Chasalevris | Vibration analysis of nonlinear-dynamic rotor-bearing systems and defect detection | |
GANDHI | Coast-down time monitoring for defect detection in rotating equipment | |
Djaidir et al. | Detection of vibrations defects in gas transportation plant based on input/output data analysis: Gas turbine investigations | |
Tselios et al. | Identification of Unbalance in a Rotating System Using Artificial Neural Networks |