Non-invasive gearbox fault diagnosis using scattering transform of acoustic emission

Mehrdad Heydarzadeh; Mehrdad Nourani; John Hansen; Shahin Hedayati Kia

ICASSP 2017accepted0 citations

Non-invasive gearbox fault diagnosis using scattering transform of acoustic emission

Mehrdad Heydarzadeh, Mehrdad Nourani, John Hansen, Shahin Hedayati Kia

Abstract

Monitoring acoustic emission from mechanical systems is an effective non-invasive way of diagnosing both system performance as well as short-term/long-term system failures. A difficulty however in fault detection in such systems is inter-class variability caused by non-uniform or unknown load conditions which decrease the classification accuracy. In this paper, a scattering transform is employed to diagnose gearbox faults using acoustic emission analysis. The results analysis and solution shows that a two layer scattering transform can diagnose four gearbox faults with an average accuracy of 97% even if the system is not exposed to data of all loads in the training phase.

BibTeX

@inproceedings{icassp2017_noninvasivegearb,
  title = {Non-invasive gearbox fault diagnosis using scattering transform of acoustic emission},
  author = {Mehrdad Heydarzadeh and Mehrdad Nourani and John Hansen and Shahin Hedayati Kia},
  booktitle = {ICASSP 2017},
  year = {2017}
}