Performance Analysis of Motor Vibration Based Condition Monitoring Using R-curve

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Authors

  • Mechanical Engineering Department, Ballari Institute of Technology and Management, Ballari - 583104, Karnataka ,IN
  • Mechanical Engineering Department, Ballari Institute of Technology and Management, Ballari - 583104, Karnataka ,IN
  • Mechanical Engineering Department, Ballari Institute of Technology and Management, Ballari - 583104, Karnataka ,IN
  • Al-Kitab University, Kirkuk - 36015 ,IQ
  • Department of Chemical Engineering and Petroleum Industries, Al-Mustaqbal University, Babylon - 51001 ,IQ
  • Civil Engineering Department, Dijlah University College, Baghdad ,IQ
  • Aircraft Research and Design Centre, HAL, Bangalore - 560037, Karnataka ,IN
  • Mechanical Engineering Department, Ballari Institute of Technology and Management, Ballari - 583104, Karnataka ,IN
  • Department of Mechanical Engineering, APS Polytechnic, Bangalore - 560082, Karnataka ,IN
  • Department of Mechanical Engineering, Siddaganga Institute of Technology, Tumakuru - 572103, Karnataka ,IN

DOI:

https://doi.org/10.18311/jmmf/2024/44562

Keywords:

Condition monitoring, FFT Analyzer, Maintenance, Neural Network, Vibration

Abstract

Traditional techniques of manually extracting characteristics from monitoring data need skill in signal processing and previous knowledge in failure detection, which is seldom possible on a machinery big data platform. As a result, a unique approach for automatically extracting adaptive fault characteristics from monitoring data and intelligently diagnosing fault patterns is projected to accomplish rotating equipment problem identification on a machinery big data platform. This study is focused on knowledge acquired from vibration analysis and applying towards condition monitoring techniques. Results showed 99.87% accuracy level of vibration that improves the performance of motor.

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Published

2024-08-19

How to Cite

Pavan Kumar, B. K., Basavaraj, Y., Janamatti, S. V., Algburi, S., Majdi, H. S., Mohammed, S. J., Nagaral, M., Nalband, F., Namdev, N., & Auradi, V. (2024). Performance Analysis of Motor Vibration Based Condition Monitoring Using R-curve. Journal of Mines, Metals and Fuels, 72(5), 433–438. https://doi.org/10.18311/jmmf/2024/44562

Issue

Section

Articles
Received 2024-06-20
Accepted 2024-07-19
Published 2024-08-19

 

References

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