Year

2015

Degree Name

Doctor of Philosophy

Department

School of Mechanical, Materials and Mechatronic Engineering

Abstract

This thesis presents six major contributions to the study on very low speed slew bearing condition monitoring and prognosis: (1) review of studies on vibration and AE-based condition monitoring of rolling element bearing; (2) selection of reliable features for slew bearing condition monitoring parameters from features that were reported in the literatures; (3) development of alternative features based on circular domain analysis and LLE algorithm; (4) development of incipient damage v detection method based on MSET and SPRT; (5) development of future state prediction using kernel regression method; and (6) implementation of online monitoring system based on File Transfer Protocol (FTP).

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