[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Gelman et al., 2017 - Google Patents

Novel adaptation of the spectral kurtosis for vibration diagnosis of gearboxes in non-stationary conditions

Gelman et al., 2017

View PDF
Document ID
18001319120006965448
Author
Gelman L
Kolbe S
Shaw B
Vaidhianathasamy M
Publication year
Publication venue
Insight-Non-Destructive Testing and Condition Monitoring

External Links

Snippet

In this paper, the adaptation of spectral kurtosis technology is proposed, demonstrated and experimentally validated. Raw data signals were collected from a single-stage gearbox run in different combinations of speed and load, after which time synchronous averaging was …
Continue reading at pdfs.semanticscholar.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR
    • G01M13/00Testing of machine parts
    • G01M13/02Testing of gearing or of transmission mechanisms
    • G01M13/021Testing of gearing or of transmission mechanisms of gearings
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric 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
    • G05B23/0224Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/024Quantitative 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
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric 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
    • G05B23/0224Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/0227Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
    • G05B23/0229Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions knowledge based, e.g. expert systems; genetic algorithms
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01HMEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H1/00Measuring characteristics of vibrations in solids by using direct conduction to the detector
    • G01H1/003Measuring characteristics of vibrations in solids by using direct conduction to the detector of rotating machines
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR
    • G01M13/00Testing of machine parts
    • G01M13/04Testing of bearings

Similar Documents

Publication Publication Date Title
Vishwakarma et al. Vibration analysis & condition monitoring for rotating machines: a review
Cocconcelli et al. STFT based approach for ball bearing fault detection in a varying speed motor
Yang et al. Vibration feature extraction techniques for fault diagnosis of rotating machinery: a literature survey
Sawalhi et al. Vibration response of spalled rolling element bearings: Observations, simulations and signal processing techniques to track the spall size
Sait et al. A review of gearbox condition monitoring based on vibration analysis techniques diagnostics and prognostics
Klausen et al. Cross-correlation of whitened vibration signals for low-speed bearing diagnostics
Gelman et al. Novel adaptation of the spectral kurtosis for vibration diagnosis of gearboxes in non-stationary conditions
Dhamande et al. Detection of combined gear-bearing fault in single stage spur gear box using artificial neural network
Segla et al. Bearing fault diagnosis with an improved high frequency resonance technique
Singh et al. A review of vibration analysis techniques for rotating machines
Gelman et al. Novel spectral kurtosis technology for adaptive vibration condition monitoring of multi-stage gearboxes
Bouaouiche et al. Detection of defects in a bearing by analysis of vibration signals
Cocconcelli et al. Kurtosis over energy distribution approach for STFT enhancement in ball bearing diagnostics
Abdelkader et al. Rolling bearing faults diagnosis based on empirical mode decomposition: Optimized threshold de-noising method
Saidi et al. The use of spectral kurtosis as a trend parameter for bearing faults diagnosis
Rahmoune et al. Early detection of pitting failure in gears using a spectral kurtosis analysis
Elasha et al. Effectiveness of adaptive filter algorithms and spectral kurtosis in bearing faults detection in a gearbox
Randall et al. Signal processing tools for tracking the size of a spall in a rolling element bearing
RU2826382C1 (en) Method of diagnosing technical condition of rolling bearings in real time
Baqqar et al. A general regression neural network model for gearbox fault detection using motor operating parameters
Liu An intelligent system for bearing condition monitoring
Zhang Analysis of Escalator Based on Spectral Kurtosis and Envelope Demodulation Method Diagnosis and Application of Motor Bearing Faults
Elasha et al. Detection of machine soft foot with vibration analysis
Guo et al. Extraction of weak transient signals based on adaptive window merging for rolling bearing fault diagnosis
Medina et al. A dictionary sparse based representation of vibration signals for gearbox fault detection