A new frequency analysis for diagnosis of bearing defects in induction motors using the adaptive lifting scheme of wavelet transforms
Year: 2018
Type: article
Abstract: This work describes a novel and effective application of the adaptive wavelet transformfor the detection of bearing faults on induction motor stator current. This transform is based on athree-step nonlinear lifting scheme: a fixed prediction followed by a space-varying update and a noadditive prediction. This transformation technique is used in a diversity of applications in digitalsignal processing and the transmission or storage of sampled data (notably the compression of thesound, or physical measurements of accuracy). Many faults in induction motor have beenidentified as bearing defects, rotor defects and external defects. Experimental results confirm theutility and the effectiveness of the proposed method for outer raceway fault diagnosis under noload and full load conditions.
Institutions: University of Biskra, University of Eloued
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4401398258