@article{scholars5657,
            year = {2015},
       publisher = {Springer New York LLC},
         journal = {Journal of Failure Analysis and Prevention},
           pages = {730--736},
            note = {cited By 11},
          volume = {15},
          number = {5},
             doi = {10.1007/s11668-015-0009-6},
           title = {Analysis of Bearing Surface Roughness Defects in Induction Motors},
        abstract = {In this paper, a Park{\^a}??s transformation method for the analysis of various bearing surface roughness defects is presented. The existing instantaneous power analysis and stator current analysis techniques are unable to diagnose bearing surface roughness defects, due to the fact that characteristics defect frequency model is not available for these types of defects. Thus, this paper proposes a Park{\^a}??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 outer and 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, ASM International.},
        keywords = {Condition monitoring; Hardware; Induction motors; Machine vibrations; Surface defects, Analysis of various; Bearing surfaces; Defect frequency; Hardware implementations; Instantaneous power; Intelligent diagnostics; S-transformation; Stator currents, Surface roughness},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942503272&doi=10.1007\%2fs11668-015-0009-6&partnerID=40&md5=542eff12eebf95bd194ad59f79a98a8a},
            issn = {15477029},
          author = {Irfan, M. and Saad, N. and Ibrahim, R. and Asirvadam, V. S. and Hung, N. T. and Magzoub, M. A.}
}