Commenced in January 2007
Paper Count: 31105
An Investigative Study into Observer based Non-Invasive Fault Detection and Diagnosis in Induction Motors
Abstract:A new observer based fault detection and diagnosis scheme for predicting induction motors- faults is proposed in this paper. Prediction of incipient faults, using different variants of Kalman filter and their relative performance are evaluated. Only soft faults are considered for this work. The data generation, filter convergence issues, hypothesis testing and residue estimates are addressed. Simulink model is used for data generation and various types of faults are considered. A comparative assessment of the estimates of different observers associated with these faults is included.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1332098Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1581
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