Preemptive Diagnosis of Minor Machine Failure by DDS Spectrum Analysis

Abstract

A preemptive diagnostic system has been developed to detect minor machine failures before machine breakdown for a computer controlled robotic drilling end-effector. By using the Dynamic Data System (DDS) approach, a set of discrete time series data taken from the continuous vibration signal of the machine is analyzed to detect machine failure and to distinguish failures due to the spindle, gears, air motors, and ball bearings of the machine drive system. Experiments validate that the proposed diagnostic method can identify spindle, air motors, gear, and bearing defects in the Robotic Drilling Unit.