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Fault detection and localization of mechanical drives based on data fusion techniques : doctoral dissertation
Peršin, Gabrijel
The thesis focuses on reliable fault diagnosis of mechanical drives, while cosidering integration of several condition monitoring approaches. Partial decisions regarding machine condition, obtained ...independently from vibration and oil analysis techniques, are used within the fusion process based on the incidence table. The incidence table offers in-depth relations between faults and signatures from oil properties or vibration features, used for estimation of final fault probabilities. Analysis of oil parameters is based on trend change detection, followed by qualitative analysis, which reveals the nature of the ongoing change. Recognition of fault signatures in oil parameters is followed by estimation of fault probability. Vibration analysis is based on spectral kurtosis and filtering, used to extract fault-related non-stationary component from background noise. The component is used for extraction of diagnostic features, which are used for fault-related impact detection, based on k-means clustering and k-nearest neighbours classification. Experimental validation, which included oil contamination experiment, gear pitting, and bearing inner and outer race damage, proved the proposed approach to offer reliable estimation of fault probabilities, by fusion of partial probabilities obtained by oil and vibration analysis.
Type of material - dissertation
; adult, serious
Publication and manufacture - Ljubljana : [G. Peršin], 2013
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