A novel blind deconvolution de-noising scheme in failure prognosis
- 16 February 2010
- journal article
- research article
- Published by SAGE Publications in Transactions of the Institute of Measurement and Control
- Vol. 32 (1), 3-30
- https://doi.org/10.1177/0142331209357844
Abstract
With increased system complexity, condition-based maintenance (CBM) becomes a promising solution for system safety by detecting faults and scheduling maintenance procedures before faults become severe failures resulting in catastrophic events. For CBM of many mechanical systems, fault diagnosis and failure prognosis based on vibration signal analysis are essential techniques. Noise originating from various sources, however, often corrupts vibration signals and degrades the performance of diagnostic and prognostic routines, and consequently, the performance of CBM. In this paper, a new de-noising structure is proposed and applied to vibration signals collected from a testbed of the main gearbox of a helicopter subjected to a seeded fault. The proposed structure integrates a blind deconvolution algorithm, feature extraction, failure prognosis and vibration modelling into a synergistic system, in which the blind deconvolution algorithm attempts to arrive at the true vibration signal through an iterative optimization process. Performance indexes associated with quality of the extracted features and failure prognosis are addressed, before and after de-noising, for validation purposes.Keywords
This publication has 12 references indexed in Scilit:
- A blind deconvolution separation of multiple sources, with application to bearing diagnosticsMechanical Systems and Signal Processing, 2005
- Blind separation of vibration components: Principles and demonstrationsMechanical Systems and Signal Processing, 2005
- Use of stochastic resonance for enhancement of low-level vibration signal componentsMechanical Systems and Signal Processing, 2005
- Unsupervised noise cancellation for vibration signals: part I—evaluation of adaptive algorithmsMechanical Systems and Signal Processing, 2004
- BLIND SOURCES SEPARATION APPLIED TO ROTATING MACHINES MONITORING BY ACOUSTICAL AND VIBRATIONS ANALYSISMechanical Systems and Signal Processing, 2000
- A novel blind deconvolution scheme for image restoration using recursive filteringIEEE Transactions on Signal Processing, 1998
- Blind deconvolution of ultrasonic signals in nondestructive testing applicationsIEEE Transactions on Signal Processing, 1997
- Adaptive suppression of vibrations - a repetitive control approachIEEE Transactions on Control Systems Technology, 1996
- Iterative blind deconvolution method and its applicationsOptics Letters, 1988
- Discrete constrained iterative deconvolution algorithms with optimized rate of convergenceSignal Processing, 1984