Application of psychoacoustic filtering for machine fault detection Online publication date: Fri, 10-Nov-2006
by P. Potocnik, E. Govekar, I. Grabec
International Journal of Materials and Product Technology (IJMPT), Vol. 27, No. 3/4, 2006
Abstract: A method for nondestructive machine fault detection based on the evaluation of acoustic machine signatures is proposed. Various mechanical defects of rotary machines can be reflected in altered acoustic signatures. The proposed method is based on the psychoacoustic modelling of human auditory perception. For the purpose of machine fault detection, the gammatone filterbank is applied in the preprocessing of acoustic signals. Filtered signals are then rectified and features are calculated as mean values of rectified signals. A set of features represents an extracted machine signature. The machine states are evaluated by comparing the extracted signature with the database of previously collected machine signatures. The proposed approach is illustrated by a case study where the quality of commercially produced compressors is estimated. Results show that major faults that occur in a production can be reliably detected.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Materials and Product Technology (IJMPT):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook