He et al., 2015 - Google Patents
Health monitoring of cooling fan bearings based on wavelet filterHe et al., 2015
View PDF- Document ID
- 4583765700428060747
- Author
- He W
- Miao Q
- Azarian M
- Pecht M
- Publication year
- Publication venue
- Mechanical Systems and Signal Processing
External Links
Snippet
In this paper, a vibration-based health monitoring approach for cooling fans is proposed using a wavelet filter for early detection of faults in fan bearings and for the assessment of fault severity. To match the wavelet filter to the fault characteristic signal, a fuzzy rule is …
- 238000001816 cooling 0 title abstract description 23
Classifications
-
- 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
- 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
- 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
- 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
- G05B23/0227—Qualitative 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
- G05B23/0229—Qualitative 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
He et al. | Health monitoring of cooling fan bearings based on wavelet filter | |
Wang et al. | Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications | |
Zhang et al. | Feature extraction method based on adaptive and concise empirical wavelet transform and its applications in bearing fault diagnosis | |
Yin et al. | Weak fault feature extraction of rolling bearings based on improved ensemble noise-reconstructed EMD and adaptive threshold denoising | |
Mishra et al. | Rolling element bearing fault diagnosis under slow speed operation using wavelet de-noising | |
Ali et al. | Online automatic diagnosis of wind turbine bearings progressive degradations under real experimental conditions based on unsupervised machine learning | |
El-Thalji et al. | A summary of fault modelling and predictive health monitoring of rolling element bearings | |
Zheng et al. | Incipient fault detection of rolling bearing using maximum autocorrelation impulse harmonic to noise deconvolution and parameter optimized fast EEMD | |
Hemmati et al. | Roller bearing acoustic signature extraction by wavelet packet transform, applications in fault detection and size estimation | |
Osman et al. | A morphological Hilbert-Huang transform technique for bearing fault detection | |
Golafshan et al. | SVD and Hankel matrix based de-noising approach for ball bearing fault detection and its assessment using artificial faults | |
Patidar et al. | An overview on vibration analysis techniques for the diagnosis of rolling element bearing faults | |
Li et al. | Rotational machine health monitoring and fault detection using EMD-based acoustic emission feature quantification | |
Wang et al. | Fuzzy diagnosis method for rotating machinery in variable rotating speed | |
Shanbr et al. | Detection of natural crack in wind turbine gearbox | |
Klausen et al. | Multi-band identification for enhancing bearing fault detection in variable speed conditions | |
Liu et al. | Wavelet spectrum analysis for bearing fault diagnostics | |
Meng et al. | Health indicator of bearing constructed by rms-CUMSUM and GRRMD-CUMSUM with multifeatures of envelope spectrum | |
Attoui et al. | Vibration-based bearing fault diagnosis by an integrated DWT-FFT approach and an adaptive neuro-fuzzy inference system | |
Jena et al. | Radial ball bearing inner race defect width measurement using analytical wavelet transform of acoustic and vibration signal | |
Singh et al. | A review of vibration analysis techniques for rotating machines | |
Jain et al. | A review on vibration signal analysis techniques used for detection of rolling element bearing defects | |
Pancaldi et al. | Impact of noise model on the performance of algorithms for fault diagnosis in rolling bearings | |
Rehab et al. | The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum | |
Zhang et al. | Generalized transmissibility damage indicator with application to wind turbine component condition monitoring |