✦ LIBER ✦

FAULT DIAGNOSIS OF ROTATING MACHINERY THROUGH VISUALISATION OF SOUND SIGNALS

✍ Scribed by KATSUHIKO SHIBATA; ATSUSHI TAKAHASHI; TAKUYA SHIRAI

Publisher: Elsevier Science
Year: 2000
Tongue: English
Weight: 279 KB
Volume: 14
Category: Article
ISSN: 0888-3270
DOI: 10.1006/mssp.1999.1255

No coin nor oath required. For personal study only.

✦ Synopsis

As a method for diagnosing faults in rotating machinery, attention is being focused on changes in the sound signals generated by bearings. This provides the advantage of making it easier to set up sensors, since sound signals can be measured at a location some distance from the housing of the bearing. However, the signal-to-noise ratio is low compared with the vibration acceleration, which makes it di$cult to identify any characteristic di!erence between the sound signals generated by normal and faulty bearings. This report describes a symmetrised dot pattern (SDP) method, which visualises sound signals in a diagrammatic representation. Using SDP to visualize sound signals measured for fans, it was possible to distinguish di!erences between normal and faulty bearings. Moreover, through the analysis of sound signals in the time-frequency domain and wavelet analysis, the signal component indicative of a fault was identi"ed. When sound signals were modi"ed by removing the above component, SDP with the modi"ed faulty signal resembled the non-faulty case.

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