Induction Motor Stator Fault Detection by a Condition Monitoring Scheme Based on Parameter Estimation Algorithms
Conference item
Duan, F and Zivanovic, R (2013). Induction Motor Stator Fault Detection by a Condition Monitoring Scheme Based on Parameter Estimation Algorithms. 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED). Valencia 27 - 30 Aug 2013 Taylor & Francis. https://doi.org/10.1080/15325008.2015.1089336
Authors | Duan, F and Zivanovic, R |
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Abstract | Parameter estimation is a cost-effective method for fault detection of induction motors. This method is based on detecting change of the characteristic parameters at presence of fault. However, the challenge of parameter estimation is nonlinearity of a machine model which results in multiple local minima involved during the computation process. This paper investigates the suitability of local and global search methods to be used in the estimation of characteristic parameters that are indicating stator short circuit faults. Results of practical case studies are presented where two search methods (local and global) are evaluated and compared. A further study in noisy environment proves the feasibility of diagnosing the fault based on stator currents with low signal to noise ratio. |
Keywords | Induction Motor; Stator Fault Detection; Condition Monitoring; Parameter Estimation Algorithms; 0906 Electrical And Electronic Engineering; Energy |
Year | 2013 |
Journal | Taylor and Francis |
Publisher | Taylor & Francis |
ISSN | 1532-5008 |
Digital Object Identifier (DOI) | https://doi.org/10.1080/15325008.2015.1089336 |
Accepted author manuscript | License |
Publication dates | |
27 Aug 2013 | |
Publication process dates | |
Deposited | 27 Jun 2018 |
Accepted | 21 Aug 2013 |
https://openresearch.lsbu.ac.uk/item/878y5
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