DocumentCode :
1570479
Title :
Enhanced vibration monitoring using parametric modelling technique
Author :
Rantala, Seppo ; Suoranta, Risto
Author_Institution :
Tech. Res. Centre of Finland, Tampere, Finland
fYear :
1991
Firstpage :
2
Lastpage :
5
Abstract :
A parametric modeling technique has been applied to the predictive maintenance of rotating machinery. The case, which is explained in detail, was taken from an experiment in which a one-step gearbox was run at about 150% of nominal load until failure occurred. During the experiment, vibration signals from the gearbox were measured. The novelty of this work is to analyze the residual signal obtained by computing the difference between the predicted and measured signal. A parametric modeling technique called autoregressive modeling is utilized in the prediction procedure. The analysis of the residual signal proved to be successful; the failure could be predicted easier and earlier than using traditional fast Fourier transform (FFT)-based methods
Keywords :
automatic testing; computerised monitoring; computerised signal processing; fault location; maintenance engineering; vibration measurement; automatic testing; autoregressive modeling; computerised signal processing; failure; measured signal; one-step gearbox; parametric modelling; prediction; predictive maintenance; residual signal; rotating machinery; vibration monitoring; vibration signals; Cepstral analysis; Condition monitoring; Digital signal processing; Frequency; Parametric statistics; Signal analysis; Signal processing; Signal processing algorithms; Spectral analysis; Vibration measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1991. IMTC-91. Conference Record., 8th IEEE
Conference_Location :
Atlanta, GA
Print_ISBN :
0-87942-579-2
Type :
conf
DOI :
10.1109/IMTC.1991.161526
Filename :
161526
Link To Document :
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