Smart Structures and Systems

  • 제29권6호
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  • Pages.799-805
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  • 2022
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Remaining useful life prediction for PMSM under radial load using particle filter

  • Lee, Younghun (Department of Mechanical Engineering, Konkuk University) ;
  • Kim, Inhwan (Department of Mechanical Engineering, Konkuk University) ;
  • Choi, Sikgyoung (Department of Mechanical Engineering, Konkuk University) ;
  • Oh, Jaewook (Department of Mechanical Engineering, Konkuk University) ;
  • Kim, Namsu (Department of Mechanical Engineering, Konkuk University)
  • 투고 : 2021.10.31
  • 심사 : 2022.03.29
  • 발행 : 2022.06.25
⟨ 이전 논문 다음 논문 ⟩

초록

Permanent magnet synchronous motors (PMSMs) are widely used in systems requiring high control precision, efficiency, and reliability. Predicting the remaining useful life (RUL) with health monitoring of PMSMs prevents catastrophic failure and ensures reliable operation of system. In this study, a model-based method for predicting the RUL of PMSMs using phase current and vibration signals is proposed. The proposed method includes feature selection and RUL prediction based on a particle filter with a degradation model. The Paris-Erdogan model describing micro fatigue crack propagation is used as the degradation model. An experimental set-up to conduct accelerated life test, capable of monitoring various signals was designed in this study. Phase current and vibration data obtained from an accelerated life test of the PMSMs were used to verify the proposed approach. Features extracted from the data were clustered based on monotonicity and correlation clustering, respectively. The results identify the effectiveness of using the current data in predicting the RUL of PMSMs.

키워드

과제정보

This work was supported by Konkuk University in 2018.

참고문헌

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