Multiple band-pass autoregressive demodulation for rolling-element bearing fault diagnosis

Mechanical Systems and Signal Processing

Volumn 15, Issue 5, 2001, Pages 963-977

  Altmann, J ^a   Mathew, J ^b  

^a STI Technologies Inc   (United States)

^b QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BANDPASS FILTERS; EXPERT SYSTEMS; FAILURE ANALYSIS; FEATURE EXTRACTION; FUZZY SETS; MEMBERSHIP FUNCTIONS; NEURAL NETWORKS; OPTIMIZATION; SIGNAL FILTERING AND PREDICTION; SIGNAL TO NOISE RATIO; STATISTICAL METHODS; VIBRATIONS (MECHANICAL);

AUTOREGRESSIVE SPECTRUM; BAND-PASS FILTERING; DISCRETE WAVELET PACKET ANALYSIS; FUZZY INFERENCE SYSTEM; ROLLING-ELEMENT BEARING;

BEARINGS (MACHINE PARTS);

EID: 0035456123     PISSN: 08883270     EISSN: None     Source Type: Journal    
DOI: 10.1006/mssp.2001.1410     Document Type: Article

References (13)

1. Incipient damage detection in low speed bearings using the demodulated resonance technique
2. Fault detection and diagnose in low speed rolling-element bearings 1: The use of parametric spectra
3. The wavelet transform, time-frequency localisation and signal analysis
4. Optimal configuration of the time-frequency representation of vibration signals
5. Tilings of the time-frequency plane: Construction of arbitrary orthogonal bases and fast tiling algorithms
6. Wavelet packet algorithm for signal extracting and its application in fault diagnosis
7. ANFIS: Adaptive network-based fuzzy inference systems
8. Neuro-fuzzy modelling and control
9. Bearing condition monitoring via vibration and acoustic emission measurements
10. Analytical modelling of vibrations due to localised defects in rolling-element bearings