TY  - JOUR
PB  - Institute of Electrical and Electronics Engineers Inc.
SN  - 02780046
EP  - 5950
AV  - none
TI  - Electrical Signature Analysis-Based Detection of External Bearing Faults in Electromechanical Drivetrains
SP  - 5941
N1  - cited By 36
Y1  - 2018///
VL  - 65
JF  - IEEE Transactions on Industrial Electronics
A1  - Shahriar, M.R.
A1  - Borghesani, P.
A1  - Tan, A.C.C.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85038853139&doi=10.1109%2fTIE.2017.2782240&partnerID=40&md5=3e4f9c48da3bc0b85eb19552ad65962f
ID  - scholars10207
KW  - Condition monitoring; Defects; Electric fault currents; Electric variables measurement; Failure analysis; Jitter; Monitoring; Vibration analysis; Wind turbines
KW  -  Detection capability; Electrical measurement; Electrical signal; Electrical signature analysis; Electromechanical drivetrain; Shafts; Torsional resonances; Vibrations
KW  -  Fault detection
IS  - 7
N2  - An electrical signature analysis (ESA)-based method to detect bearing defects in electromechanical drivetrains (e.g., wind turbines) is proposed in this paper. The novelty of the proposed technique is justified by its capability to detect a defect that occurs in a drivetrain bearing, external to the machine. Unlike the traditional vibration-based method, the electrical measurements of the terminal machine are utilized in this case to perform the fault detection. The proposed ESA-based method is developed utilizing a new electrical signal model of bearing defect, proposed in this paper, based on the excitation of torsional resonances. The proposed ESA-based method and the signal model are validated through experimental tests. The proposed technique demonstrates excellent fault detection capability even at low operating speed, which is advantageous over the traditional vibration-based method in terms of sensor cost, installation complexity, and detection reliability. © 1982-2012 IEEE.
ER  -