State of the art in monitoring rotating machinery. Part 2

In the last thirty years there have been many developments in the use of vibration measurement and analysis for monitoring the condition of rotating machinery while in operation. These have been in all three areas of interest, namely fault detection, diagnosis and prognosis. Of these areas, diagnosis and prognosis still require an expert to determine what analyses to perform and to interpret the results. Currently much effort is being put into automating fault diagnosis and prognosis. Major economic benefits come from being able to predict with reasonable certainty how much longer a machine can safely operate (often a matter of several months from when incipient faults are first detected). This article discusses the different requirements for detecting and diagnosing faults, outlining a robust procedure for the former, and then goes on to discuss a large number of signal processing techniques that have been proposed for diagnosing both the type and severity of the faults once detected. Change in the severity can of course be used for prognostic purposes. Most procedures are illustrated using actual signals from case histories. Part 1 of this article appeared in the March 2004 issue of S&V.

[1]  Robert B. Randall,et al.  A New Method of Modeling Gear Faults , 1982 .

[2]  R. Randall,et al.  OPTIMISATION OF BEARING DIAGNOSTIC TECHNIQUES USING SIMULATED AND ACTUAL BEARING FAULT SIGNALS , 2000 .

[3]  P. D. McFadden,et al.  Model for the vibration produced by a single point defect in a rolling element bearing , 1984 .

[4]  Robert B. Randall,et al.  Unsupervised noise cancellation for vibration signals: part II—a novel frequency-domain algorithm , 2004 .

[5]  D. W. Thomas,et al.  Bearing Fault Detection Using Adaptive Noise Cancelling , 1982 .

[6]  P. D. McFadden,et al.  A revised model for the extraction of periodic waveforms by time domain averaging , 1987 .

[7]  Wenyi Wang,et al.  Autoregressive Model-Based Gear Fault Diagnosis , 2002 .

[8]  William A. Gardner,et al.  Introduction to random processes with applications to signals and systems: Reviewer: D. W. Clarke Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PK, England , 1988, Autom..

[9]  R. Tibshirani,et al.  An introduction to the bootstrap , 1993 .

[10]  Robert B. Randall.  Frequency Analysis , 1987 .

[11]  P J Sweeney,et al.  Gear Transmission Error Measurement Using Phase Demodulation , 1996 .

[12]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[13]  Robert B. Randall,et al.  THE RELATIONSHIP BETWEEN SPECTRAL CORRELATION AND ENVELOPE ANALYSIS IN THE DIAGNOSTICS OF BEARING FAULTS AND OTHER CYCLOSTATIONARY MACHINE SIGNALS , 2001 .

[14]  R. Potter,et al.  Computed Order Tracking Obsoletes Older Methods , 1989 .

[15]  Robert B. Randall,et al.  Differential Diagnosis of Gear and Bearing Faults , 2002 .