Title: Signature extraction from acoustic signals and its application for ANN based engine fault diagnosis
Authors: Om Prakash; Vrijendra Singh; Prem Kumar Kalra
Addresses: Indian Institute of Information Technology Allahabad, Deoghat, Jhalwa, Allahabad 211012, India ' Indian Institute of Information Technology Allahabad, Deoghat, Jhalwa, Allahabad 211012, India ' Indian Institute of Technology, Old Residency Road, Ratanada, Jodhpur 342 011, Rajasthan, India
Abstract: In present study, the approach of signature extraction from acoustic signals based on Short Time Fourier Transform (STFT) and its use for Artificial Neural Network (ANN) based fault diagnosis of internal combustion engine is explored. STFT can provide a time-frequency resolution data for signal signature extraction. It is suitable for extracting mechanical fault information form acoustic signals. In present work, a protocol of time dependent frequency information for development of signature and its application in engine fault diagnosis is proposed. The results of the protocol application show that the extracted signatures of seven classes of acoustic signals as engine fault information are effective for the development of classification model.
Keywords: ANNs; artificial neural networks; LOOCV; leave one out cross validation; signature, STFT; short time Fourier transform; signature extraction; acoustic signals; engine faults; fault diagnosis; internal combustion engines.
International Journal of Signal and Imaging Systems Engineering, 2012 Vol.5 No.3, pp.220 - 226
Available online: 17 Oct 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article