Rotor broken-bar fault diagnosis of induction motor based on Hilbert-Huang transformation of the startup electromagnetic torque

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering

Volumn 25, Issue 11, 2005, Pages 107-112

  Niu, Fa Liang ^a   Huang, Jin ^a   Yang, Jia Qiang ^a   Chen, Li Yuan ^a   Jin, Hai ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Electric machinery; Electromagnetic torque; Fault diagnosis; Hilbert Huang Transformation (HHT); Induction motor

Indexed keywords

FAULT TREE ANALYSIS; MATHEMATICAL TRANSFORMATIONS; ROTORS; TORQUE;

ELECTROMAGNETIC TORQUE; EMPIRICAL MODE DECOMPOSITION; FAULT DIAGNOSIS; FREQUENCY COMPONENT; HILBERT HUANG TRANSFORMATION; INTRINSIC MODE FUNCTION;

INDUCTION MOTORS;

EID: 21844465934     PISSN: 02588013     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (11)

1. Ethan, Song Y H. Condition monitoring techniques for electrical equipment-a literature survey[J]. IEEE Transactions on Power Delivery, 2003, 18(1): 4-13.
2. Alberto Belling. On-field experience with online diagnosis of large induction motors cage failures using MCSA[J]. IEEE Trans. on Industry Applications, 2002, 38(4): 1045-1053.
3. Albert Belling, Foreknow Flippest. Evaluation of induction motor broken bars by means of electrical signature analysis[J]. IEEE Trans. on Industry Applications, 2001, 37(5): 1248-1255.
4. Liu Zhenxing, Yin Xianggen, Zhang Zhe et al. On-line monitoring and diagnosis way based on spectrum analysis of Hilbert modulus in induction motors[J]. Proceedings of the CSEE, 2003, 23(7): 158-161.
5. Hou Xinguo, Wu Guozheng, Xia Li et al. A method for detecting rotor faults in asynchronous motors based on the square of the park's vector modulus[J]. Proceedings of the CSEE, 2003, 23(9): 137-140.
6. Cruz S M A, Marques Cardoso A J. Rotor cage fault diagnosis in three-phase induction motors by the total instantaneous power spectral analysis[C]. Industry Applications Conference, 1999. Thirty-Fourth LAS Annual Meeting. 3: 1929-1934.
7. Andrzej M. Trzynadlowski, Ewen Ritchie. Comparative investigation of diagnostic media for induction motors: a case of rotor cage faults[J]. IEEE Trans. on Industrial Electronics, 2000, 47(5): 1092-1099.
8. John S. Hsu. Monitoring of defects in induction motors through air-gap torque observation[J]. IEEE Trans. on Industry Applications, 1995, 31(5): 1016-1021.
9. Zhang Zhengping, Ren Zhen, Huang Wenying et al. A novel method of motor faulted rotor detection based on wavelet ridge[J]. Proceedings of the CSEE, 2003, 23(1): 97-101.
10. Huang N E. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[C]. Proc R Soc Lond A, 1998, 454: 903-995.
11. Vinod V. Thomas, Krishna Vasudevan et al. Online cage rotor fault detection using air-gap torque spectrum[J]. IEEE Trans. on Energy Conversion, 2003, 18(2): 265-270.