Application of Blind Deconvolution Denoising in Failure Prognosis
- 28 October 2008
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Instrumentation and Measurement
- Vol. 58 (2), 303-310
- https://doi.org/10.1109/tim.2008.2005963
Abstract
Fault diagnosis and failure prognosis are essential techniques in improving the safety of many mechanical systems. However, vibration signals are often corrupted by noise; therefore, the performance of diagnostic and prognostic algorithms is degraded. In this paper, a novel denoising structure is proposed and applied to vibration signals collected from a testbed of the helicopter main gearbox subjected to a seeded fault. The proposed structure integrates a denoising algorithm, feature extraction, failure prognosis, and vibration modeling into a synergistic system. Performance indexes associated with the quality of the extracted features and failure prognosis are addressed, before and after denoising, for validation purposes.Keywords
This publication has 11 references indexed in Scilit:
- An integrated approach to helicopter planetary gear fault diagnosis and failure prognosis2007 IEEE Autotestcon, 2007
- Use of blind deconvolution de-noising scheme in failure prognosis2007 IEEE Autotestcon, 2007
- Intelligent Fault Diagnosis and Prognosis for Engineering SystemsPublished by Wiley ,2006
- Use of stochastic resonance for enhancement of low-level vibration signal componentsMechanical Systems and Signal Processing, 2005
- A Particle Filtering Framework for Failure PrognosisPublished by ASME International ,2005
- Unsupervised noise cancellation for vibration signals: part I—evaluation of adaptive algorithmsMechanical Systems and Signal Processing, 2004
- A novel blind deconvolution scheme for image restoration using recursive filteringIEEE Transactions on Signal Processing, 1998
- Time synchronous averaging of ball mill vibrationsMechanical Systems and Signal Processing, 1989
- An Explanation for the Asymmetry of the Modulation Sidebands about the Tooth Meshing Frequency in Epicyclic Gear VibrationProceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 1985
- Suppression of acoustic noise in speech using spectral subtractionIEEE Transactions on Acoustics, Speech, and Signal Processing, 1979