Dr. H S Kumar
NMAM Institute of Technology, Moodlakatte Institute of Technology, University B D T college
0000-0002-3238-0250
About
H. S. Kumar obtained his PH.D. in Mechanical engineering from VTU in 2017, M.Tech. in Production Engineering Systems Technology from University B.D.T. college of Engineering, Davanagere and B.E. in Mechanical Engg., from S.I.T., Tumkur in 2001. Currently working as Associate Professor.in the Dept. of Mechanical Engg. at NMAMIT, Nitte, Karnataka. He has 5 years industrial and 10 years of teaching experience. He has 15 papers in various National and International Journals and Conferences. His research interests are condition monitoring, Machine learning, pattern recognition and wavelet analysis.He is a reviewer for Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science SAGE publications. Journal of Quality in Maintenance Engineering, Emerald publication, International Review of Electrical Engineering (IREE), Measurement, Journal of the Brazilian Society of Mechanical Sciences and Engineering.
Employment
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NMAM Institute of Technology Assistant Professor2011 - Present
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Moodlakatte Institute of Technology Assistant Professor2009 - 2011
Education
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NMAM Institute of Technology Ph. D2011 - 2017
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University B D T college M. Tech2002 - 2005
Projects & Funding
Projects & funding information is unavailable.
Publications (14)
- Use of empirical mode decomposition and K- nearest neighbour classifier for rolling element bearing fault diagnosis Save
- Health Index Development for Fault Diagnosis of Rolling Element Bearing Save
- Detection of fake profile on social media using machine learning and feature selection techniques Save
- Use of Micro-Electro Mechanical Sensors in Bearing Condition Monitoring, A Review Save
- An experimental comparison of random forest and support vector machine for bearing fault diagnosis: A micro electro mechanical sensor approach Save
- Classification of rolling element bearing fault using singular value Save
- Fault Diagnosis of Rolling Element Bearing Through Vibration Signals Using Naïve Bayes Classifier Save
- Use of MEMS based vibration data for REB fault diagnosis Save
- Rolling element bearing fault diagnostics: Development of health index Save
- Comparison of denoising schemes and dimensionality reduction techniques for fault diagnosis of rolling element bearing using wavelet transform Save