Dynamic wavelet-based tool for gearbox diagnosis

This paper proposes a novel wavelet-based technique for detecting and localizing gear tooth defects in a noisy environment. The proposed technique utilizes a dynamic windowing process while analyzing gearbox vibration signals in the wavelet domain. The gear vibration signal is processed through a dy...

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Bibliographic Details
Published in:Mechanical systems and signal processing 2012, Vol.26 (JAN), p.190-204
Main Authors: Omar, Farag K., Gaouda, A.M.
Format: Article
Language:English
Subjects:
Applied sciences
Drives
Dynamics
Exact sciences and technology
Fracture mechanics
Fracture mechanics (crack, fatigue, damage...)
Fundamental areas of phenomenology (including applications)
Gear tooth failure
Gearboxes
Gears
Industrial metrology. Testing
Machine diagnostics
Mechanical engineering. Machine design
Physics
Signal processing
Similarity
Solid mechanics
Structural and continuum mechanics
Vibration
Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...)
Wavelet
Wavelet multi-resolution
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Summary:This paper proposes a novel wavelet-based technique for detecting and localizing gear tooth defects in a noisy environment. The proposed technique utilizes a dynamic windowing process while analyzing gearbox vibration signals in the wavelet domain. The gear vibration signal is processed through a dynamic Kaiser's window of varying parameters. The window size, shape, and sliding rate are modified towards increasing the similarity between the non-stationary vibration signal and the selected mother wavelet. The window parameters are continuously modified until they provide maximum wavelet coefficients localized at the defected tooth. The technique is applied on laboratory data corrupted with high noise level. The technique has shown accurate results in detecting and localizing gear tooth fracture with different damage severity. ► Wavelet multi-resolution analysis (WMRA) technique for gear damage monitoring. ► Maximum resolution coefficients of WMRA localize cracks in gear teeth. ► WMRA technique detects very small cracks from signals with low SNR of −15 db.
ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2011.06.021