The prefailure detection of faults in operating plant can effect major rewards in both safety and economy. A successful on-condition maintenance philosophy would pay great dividends particularly in the offshore oil industry where -until recently, only token methods have been employed. Many techniques are available for monitoring mechanical plant and several of these are considered in general terms. Industrial methods are subsequently evaluated on reciprocating compressor and rolling element bearing faults. Bearing fault analysis is considered in two stages. Initially, a series of vibration based techniques are evaluated on a large relatively noise free rotating machine. The techniques of greatest worth carrier spectra, autospectra, time signature analysis and statistical assessments - are then applied to bearings in the hostile environment of a reciprocating machine. It is shown that while discrete faults often produce predictable periodic vibrational patterns, a monitoring system aimed solely at such vibrational phenomena cannot be relied upon. To this end, a diagnostic system must encompass a series of techniques, including carrier spectrum, time signature and statistical analyses. A series of valve and piston faults in reciprocating machines are also studied. By using a number of monitoring techniques, a catalogue of fault characteristics is constructed, and the methods of greatest worth are high-lighted. It is noted that due to the complexities of a reciprocating machine, fault characteristics vary with load, and this must be borne in mind when interpreting the various parameter displays. No single technique can provide a complete cover for all compressor faults, and it is shown that those of greatest worth are acoustic emission, combined pressure and vibration plots, temperature and performance analysis. An indication of compressor temperature and internal cylinder pressure can greatly ease the detection and diagnostic process, and for the latter, bolt load determinations may be a valuable aid.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:377365 |
| Date | January 1985 |
| Creators | Johnston, Andrew Beaton |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU365562 |
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