Electrical motor current signal analysis using a dynamic time warping method for fault diagnosis

Journal of Physics: Conference Series

Volumn 305, Issue 1, 2011, Pages

  Zhen, D ^a   Alibarbar, A ^b   Zhou, X ^c   Gu, F ^a   Ball, A D ^a  

^a UNIVERSITY OF HUDDERSFIELD   (United Kingdom)

^b MANCHESTER METROPOLITAN UNIVERSITY   (United Kingdom)

^c CHONGQING UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CONDITION MONITORING; DAMAGE DETECTION; ELECTRIC FAULT CURRENTS; PHASE SHIFT; TIME DOMAIN ANALYSIS;

CURRENT SIGNAL; DYNAMIC TIME WARPING; ELECTRICAL CURRENT; ELECTRICAL MOTORS; FAULT DETECTION AND DIAGNOSIS; OPERATING CONDITION; PHASE CURRENTS; RESIDUAL SIGNALS;

FAULT DETECTION;

EID: 80052053747     PISSN: 17426588     EISSN: 17426596     Source Type: Conference Proceeding    
DOI: 10.1088/1742-6596/305/1/012093     Document Type: Conference Paper

References (13)

1. Peter, E and Fanning, P 2004 Vibration Based Conditon Monitoring: A Review Structural Health Monitoring
2. Stack, JR, TG Habetler and RG Harley Bearing fault detection via autoregressive stator current modeling Industry Applications Conference, 2003. 38th IAS Ann. Meeting. Conf. Record of the 2003
3. Henniger, O and S Muller Effects of time normalization on the accuracy of Dynamic Time Warping.
4. Kaprykowsky, H and X Rodet Globally Optimal Short-Time Dynamic Time Warping, Application to Score to Audio Alignment Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proc. 2006 IEEE Int. Conf. on. 2006
5. Strle, B, Mozina, M and Bratko, I Qualitative approximation to Dynamic Time Warping similarity between time series data.
6. Ko, MH, et al. 2008 Using dynamic time warping for online temporal fusion in multisensor systems Information Fusion 9 (3) 370-388
7. Keogh, J E and Pazzani, M JPazzani Derivative Dynamic Time Warping.
8. Tormene, P, et al. 2009 Matching incomplete time series with dynamic time warping: an algorithm and an application to post-stroke rehabilitation Artificial Intelligence Medicine 45 (1) 11-34
9. Chu, S, et al. 2002 Iterative Deepening Dynamic Time Warping for time series
10. Keogh, E and Pazzani, M Scaling up dynamic time warping for datamining applications. Proceedings of the 6th ACM SIGKDD International Conferenc on Knowledge Discovery and Data Mining, 2000
11. El Hachemi Benbouzid, M 2000 A review of induction motors signature analysis as a medium for faults detection Industrial Electronics, IEEE Trans. on 47 (5) 984-993
12. Abdelhamid Naid, Gu, FS, Shao, Y, Al-Arbi, S Ball, AD Bispectrum Analysis of Motor Current Signals for Fault Diagnosis of Reciprocating Compressors Key Engineering Materials, June, 2009. Damage Assessment of Structures VIII p 505-511
13. Zhen, D, Gu, J, Wang, T, Gu, FS and Ball, AD 2010 Diagnostic Feature Development based on Dynamic Time Warping of Dynamic Signals under Variable Machine Operating Condition CM 2010 and MFPT 2010 : The Seventh Int. Conf. on Condition Monitoring and Machinery Failure Prevention Technologies, 22-24 June 2010 (Stratford-upon-Avon, UK)