TY  - CONF
EP  - 519
A1  - Irfan, M.
A1  - Saad, N.
A1  - Ibrahim, R.
A1  - Asirvadam, V.S.
A1  - Magzoub, M.
A1  - Hung, N.T.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84971668250&doi=10.1109%2fICSIPA.2015.7412245&partnerID=40&md5=f9120e805e1b534afa7a2900fc61d2b0
PB  - Institute of Electrical and Electronics Engineers Inc.
SN  - 9781479989966
Y1  - 2016///
TI  - An approach to diagnose inner race surface roughness defects in bearing of induction motors
ID  - scholars7179
SP  - 514
KW  - Condition monitoring; Hardware; Image processing; Induction motors; Machine vibrations; Reconfigurable hardware; Signal detection; Signal processing; Surface defects
KW  -  Bearing surfaces; Defect frequency; Hardware implementations; Instantaneous power; Park's transformation; Stator currents
KW  -  Surface roughness
N2  - 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. © 2015 IEEE.
N1  - 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
AV  - none
ER  -