DATA REDUCTION APPROACH - ACOUSTIC EMISSION (AE) BASED DEFECT ANALYSIS: DEVELOPMENT OF BURST DETECTOR ALGORITHMS

摘要

Acoustic emission (AE) techniques offer the potential for new techniques of condition monitoring of bearings, especially for very large roller bearings with slow rates of rotation. Acoustic emission data processing must be carried out by a computer, necessitating algorithms to process recorded signals. One such algorithm is a burst detector, used to identify emission events. This paper deals with the design of a burst detector with the goal of improving upon existing algorithms. The algorithm has the benefit of detecting small amplitude and overlapping bursts, as well as supplying additional information about the decay portion of the burst.