Bottleneck Features for Enhancing the Synchronous Generator Fault Diagnosis System Performance-Reference-Cited by-同舟云学术

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Bottleneck Features for Enhancing the Synchronous Generator Fault Diagnosis System Performance

Published:2021-08-27 Issue: Volume: Page:435-445
ISSN:2367-3370
Container-title:Intelligent Sustainable Systems
language:
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Author:

Santhosh Kumar C.,Bramendran A.,Sreekumar K. T.

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-2422-3_34

Reference16 articles.

1. Jardine, A.S., Lin, D., Banjevic, D.: A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical systems and signal processing 20(7), 1483–1510 (2006)

2. Neethu Mohan, K.P. Soman, S. Sachin Kumar,A data-driven strategy for short-term electric load forecasting using dynamic mode decomposition model, Applied Energy, Volume 232,Pages 229-244, (2018)

3. Perez, Ramn, Esteban Inga, Alexander Aguila, Carmen Vsquez, Liliana Lima, Amelec Viloria, and Maury-Ardila Henry. Fault diagnosis on electrical distribution systems based on fuzzy logic. In International Conference on Sensing and Imaging, pp. 174-185. Springer, Cham, (2018)

4. Samanta, B.: Gear fault detection using artificial neural networks and support vector machines with genetic algorithms. Mechanical systems and signal processing 18(3), 625–644 (2004)

5. A. S. Raghunath, K. T. Sreekumar, C. S. Kumar and K. I. Ramachandran, "Improving Speed Independent Performance of Fault Diagnosis Systems through Feature Mapping and Normalization," 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA), Anaheim, CA, 2016, pp. 764-767, https://doi.org/10.1109/ICMLA.2016.0136.

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