Transactions of the Korean Society for Noise and Vibration Engineering (한국소음진동공학회논문집)

The Korean Society for Noise and Vibration Engineering (한국소음진동공학회)
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Application of Compressive Sensing and Statistical Analysis to Condition Monitoring of Rotating Machine

압축센싱과 통계학적 기법을 적용한 회전체 시스템의 상태진단

  • Lee, Myung Jun (School of Mechanical Eengineering, Chonnam National University) ;
  • Jeon, Jun Young (School of Mechanical Eengineering, Chonnam National University) ;
  • Park, Gyuhae (School of Mechanical Engineering, Chonnam National University) ;
  • Kang, To (Korea Atomic Energy Research Institute) ;
  • Han, Soon Woo (Korea Atomic Energy Research Institute)
  • Received : 2016.04.25
  • Accepted : 2016.06.20
  • Published : 2016.11.20
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Abstract

Condition monitoring (CM) encounters a large data problem due to sensors that measure vibration data with a continuous, and sometimes, high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate the efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer samples compared to traditional sampling methods. For the experiments a built-in rotating system was used and all data were compressively sampled to obtain compressed data. Optimal signal features were then selected without the reconstruction process and were used to detect and classify damage. The experimental results show that the proposed method could improve the data processing speed and the accuracy of condition monitoring of rotating systems.

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References

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