TY  - JOUR
PY  - 2010//
TI  - A novel blind deconvolution de-noising scheme in failure prognosis
JO  - Transactions of the Institute of Measurement and Control
A1  - Bin Zhang, 
A1  - Khawaja, Taimoor
A1  - Patrick, Romano
A1  - Vachtsevanos, George
A1  - Orchard, Marcos
A1  - Saxena, Abhinav
SP  - 3
EP  - 30
VL  - 32
IS  - 1
N2  - 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.<p />
LA  - 
SN  - 0142-3312
UR  - http://dx.doi.org/10.1177/0142331209357844
ID  - ref1
ER  -