It is widely acknowledged that bearing failures are the primary reason for
breakdowns in rotating machinery. These failures are extremely costly,
particularly in terms of lost production. Roller bearings are widely used in
industrial machinery and need to be maintained in good condition to ensure the
continuing efficiency, effectiveness, and profitability of the production process.
The research presented here is an investigation of the use of acoustic emission
(AE) to monitor bearing conditions at low speeds.
Many machines, particularly large, expensive machines operate at speeds below
100 rpm, and such machines are important to the industry. However, the
overwhelming proportion of studies have investigated the use of AE techniques
for condition monitoring of higher-speed machines (typically several hundred
rpm, or even higher). Few researchers have investigated the application of these
techniques to low-speed machines (<100 rpm), This PhD addressed this
omission and has established which, of the available, AE techniques are suitable
for the detection of incipient faults and measurement of fault growth in low-speed
bearings.
The first objective of this research program was to assess the applicability of AE
techniques to monitor low-speed bearings. It was found that the measured
statistical parameters successfully monitored bearing conditions at low speeds
(10-100 rpm).
The second objective was to identify which commonly used statistical parameters
derived from the AE signal (RMS, kurtosis, amplitude and counts) could identify
the onset of a fault in either race. It was found that the change in AE amplitude
and AE RMS could identify the presence of a small fault seeded into either the
inner or the outer races. However, the severe attenuation of the signal from the
inner race meant that, while AE amplitude and RMS could readily identify the
incipient fault, kurtosis and the AE counts could not. Thus, more attention needs
to be given to analysing the signal from the inner race. The third objective was to identify a measure that would assess the degree of
severity of the fault. However, once the defect was established, it was found that
of the parameters used only AE RMS was sensitive to defect size.
The fourth objective was to assess whether the AE signal is able to detect defects
located at either the centre or edge of the outer race of a bearing rotating at low
speeds. It is found that all the measured AE parameters had higher values when
the defect was seeded in the middle of the outer race, possibly due to the shorter
path traversed by the signal between source and sensor which gave a lower
attenuation than when the defect was on the edge of the outer race. Moreover,
AE can detect the defect at both locations, which confirmed the applicability of
the AE to monitor the defects at any location on the outer race.
| Identifer | oai:union.ndltd.org:CRANFIELD1/oai:dspace.lib.cranfield.ac.uk:1826/12324 |
| Date | 01 1900 |
| Creators | Alshimmeri, Fiasael |
| Contributors | Addali, Abdulmajid, Amaral Teixeira, Joao |
| Publisher | Cranfield University |
| Source Sets | CRANFIELD1 |
| Detected Language | English |
| Type | Thesis or dissertation, Doctoral, PhD |
| Rights | © Cranfield University, 2017. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder. |
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