@inproceedings{scholars7179,
            note = {cited By 5; Conference of 4th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2015 ; Conference Date: 19 October 2015 Through 21 October 2015; Conference Code:119504},
            year = {2016},
             doi = {10.1109/ICSIPA.2015.7412245},
         journal = {IEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings},
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
           title = {An approach to diagnose inner race surface roughness defects in bearing of induction motors},
           pages = {514--519},
            isbn = {9781479989966},
          author = {Irfan, M. and Saad, N. and Ibrahim, R. and Asirvadam, V. S. and Magzoub, M. and Hung, N. T.},
        abstract = {In this paper a Park's transformation method for the analysis of bearing inner race surface roughness defects is presented. The existing instantaneous power analysis and stator current analysis techniques are unable to diagnose bearing surface roughness defects, due the fact that characteristics defect frequency model is not available for the bearing surface roughness defects. Thus, this paper proposes a Park's transformation method which can detect surface roughness defects without requiring information of the characteristic defect frequencies. The theoretical and experimental work conducted shows that the proposed method can detect bearing inner race surface roughness faults without use of any extra hardware. The results on the real hardware implementation confirm the effectiveness of the proposed approach. {\^A}{\copyright} 2015 IEEE.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84971668250&doi=10.1109\%2fICSIPA.2015.7412245&partnerID=40&md5=f9120e805e1b534afa7a2900fc61d2b0},
        keywords = {Condition monitoring; Hardware; Image processing; Induction motors; Machine vibrations; Reconfigurable hardware; Signal detection; Signal processing; Surface defects, Bearing surfaces; Defect frequency; Hardware implementations; Instantaneous power; Park's transformation; Stator currents, Surface roughness}
}