By England) Comadem 200 (2001 Manchester, Raj B. K. N. Rao
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Instead some form of on-line processing is required to autonomously reduce the information content of the signal whilst retaining that part of the information which is of principal interest. ). For example Rogers [Rogers (1979)] positioned two AE sensors diametrically opposite each other on the inside face of a crane slew ring. The detected activity was presented in the form of an amplitude distribution and in the form of a linear location of its source position. In contrast Miettinen & Pataniitty [Miettinen & Pataniitty (1999)] used a trend of AE count rate as a means of providing long term monitoring of the AE activity from 16 wheel bearings rotating at 8 rpm and supporting a kiln.
Figures 11 and 12 are close-up views of figure 10. 42 Classification using the centroid value of AR coefBcients, ORD and noise Ml o - Outer race defect SIS n - noise 022 Cluster 2 Outer race defect signatures 013 s? oU 03 i 012 n2» Ouster 1, noise S!. 8 1 Euclidean distance between centroid vaiu^ of AR coefficients associated with individual AE's "At Figure 8 Classification of AE's associated with background noise and outer race defects.
In this paper a new AE based signal processing approach is introduced which can provide simple but sensitive means of detecting the presence and evolution of faults in very slowly rotating machinery. These developments have frirther led to the creation of what is believed to be the first easily retro-fitted and affordable on-line monitoring module for very slowly rotating machinery. KEYWORDS AE, Acoustic Emission, Bearings, CM, Condition Monitoring, Rotating Machinery, Slow Speed. INTRODUCTION It is well known that the application of traditional Vibration monitoring techniques becomes progressively more difficult to apply as the speed of rotation of a machine decreases.