A Novel Blind Deconvolution De-Noising Scheme in Failure Prognosis

With increased system complexity, Condition-Based Maintenance (CBM) becomes a promising solution to 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 modeling 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. ‡ George Vachtsevanos is the corresponding author. Phone: 404-894-6252, Fax: 404-894-7583, [email protected]. G. Vachtsevanos et. al.: BLIND DECONVOLUTION 2 List of Symbols f s Planetary carrier rotation frequency Nt Number of teeth in the annular gear p Index of gear in consideration Np Number of gears m Index of harmonics of tooth meshing frequency M Total number of tooth meshing harmonics in consideration n Index of harmonics of carrier rotation frequency N Total number of carrier rotation harmonics in consideration δ Angular phase shift caused by a crack on the plate αn Magnitude of modulating signal at its harmonic nf s βm Magnitude of vibration signal from a single gear at its harmonic mNt f s φp,m,n Magnitude of frequency components from gear p at sideband mNt+n η Remainder of (mNt+n)/Np λm,n Magnitude of combined vibration signal (superposition of vibration signals from different gears) at sideband mNt+n θ Angular phase evenly separated by Np gears Wm,n Weighting factor of nonlinear projection at sideband mNt+n. θp Angular position of gear p.