Fault Recognition
Author:
Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-15-0512-6_6
Reference19 articles.
1. Verma, N.K., Roy, A., Salour, A.: An optimized fault diagnosis method for reciprocating air compressors based on SVM. In: Proceedings of the IEEE Control and System Graduate Research Colloquium Incorporating 2011 IEEE International Conference on System Engineering and Technology, Selangor, Malaysia, pp. 65–69 (2011)
2. Sevakula, R.K., Verma, N.K.: Wavelet transforms for fault detection using SVM in power systems. In: IEEE International Conference on Power Electronics, Drives and Energy Systems, Bengaluru, India, pp. 1–6 (2012)
3. Verma, N.K., Gupta, V.K., Sharma, M., Sevakula, R.K.: Intelligent condition based monitoring of rotating machines using sparse auto-encoders. In: IEEE Conference on Prognostics and Health Management, Maryland, USA, pp. 1–7 (2013)
4. Jamal, A., Verma, N.K.: Automatic fault diagnosis system using acoustic data. In: IEEE 8th International Conference on Industrial and Information Systems, Kandy, Sri Lanka, pp. 421–426 (2013)
5. Verma, N.K., Agrawal, A.K., Sevakula, R.K., Prakash, D., Salour, A.: Improved signal preprocessing techniques for machine fault diagnosis. In: 2013 IEEE 8th International Conference on Industrial and Information Systems, pp. 403–408 (2013)
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