Nothing Special   »   [go: up one dir, main page]

Nacib et al., 2014 - Google Patents

A comparative study of various methods of gear faults diagnosis

Nacib et al., 2014

View PDF
Document ID
13495295107426271645
Author
Nacib L
Saad S
Sakhara S
Publication year
Publication venue
Journal of failure analysis and prevention

External Links

Snippet

Investigating gear damages using vibration signal is a subject of a high interest, because gears vibration signals are complex and difficult to understand. A failure diagnosis of gearbox based on Fourier analysis of the vibration produced by speed reducers has shown …
Continue reading at www.researchgate.net (PDF) (other versions)

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
    • G01M13/021—Testing of gearing or of transmission mechanisms of gearings
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/46—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by spectral analysis, e.g. Fourier analysis or wavelet 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
    • 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
    • G01M13/028—Acoustic or vibration analysis
    • 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
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00—Indexing codes associated with group G01N29/00
    • G01N2291/26—Scanned objects

Similar Documents

Publication Publication Date Title
Li et al. Application of bandwidth EMD and adaptive multiscale morphology analysis for incipient fault diagnosis of rolling bearings
Van Hecke et al. Low speed bearing fault diagnosis using acoustic emission sensors
Feng et al. Vibration signal models for fault diagnosis of planetary gearboxes
Feng et al. A novel order spectrum-based Vold-Kalman filter bandwidth selection scheme for fault diagnosis of gearbox in offshore wind turbines
Bechhoefer et al. Processing for improved spectral analysis
Li et al. Gear fault detection and diagnosis under speed-up condition based on order cepstrum and radial basis function neural network
Meng et al. General synchroextracting chirplet transform: Application to the rotor rub-impact fault diagnosis
Feng et al. Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis
Sharma A review on vibration-based fault diagnosis techniques for wind turbine gearboxes operating under nonstationary conditions
Klausen et al. Multi-band identification for enhancing bearing fault detection in variable speed conditions
Mączak Local meshing plane analysis as a source of information about the gear quality
Sharma Gear fault detection based on instantaneous frequency estimation using variational mode decomposition and permutation entropy under real speed scenarios
Nacib et al. A comparative study of various methods of gear faults diagnosis
Gu et al. Monitoring and diagnosing the natural deterioration of multi-stage helical gearboxes based on modulation signal bispectrum analysis of vibrations
Yang et al. The effect of time-varying operating condition on the crack induced impulses and its application to gearbox tooth crack diagnosis
Ravikumar et al. Fault diagnosis of internal combustion engine gearbox using vibration signals based on signal processing techniques
Qu et al. Gearbox Fault Diagnostics using AE Sensors with Low Sampling Rate.
Babouri et al. Application of the cyclostationarity analysis in the detection of mechanical defects: comparative study
Rebiai et al. Faults diagnosis of rolling-element bearings based on fourier decomposition method and Teager energy operator
Chi et al. Spectral DCS-based feature extraction method for rolling element bearing pseudo-fault in rotor-bearing system
Djemili et al. A wind turbine bearing fault detection method based on improved CEEMDAN and AR-MEDA
Jamadar et al. Spur Gear Fault Detection Using Design of Experiments and Support Vector Machine (SVM) Algorithm
Dien et al. Fault detection for rotating machines in non-stationary operations using order tracking and cepstrum
Kriston et al. Application of vibro-acoustic methods in failure diagnostics
Yu Early fault detection for gear shaft and planetary gear based on wavelet and hidden Markov modeling