Accelerated Life Test of Industrial Cleaner Motor

산업용 청소기 모터의 가속수명시험

  • Eom, Hak-Yong (Department of Reliability Assessment, Korea Institute of Machinery & Materials) ;
  • Lee, Gi-Chun (Department of Reliability Assessment, Korea Institute of Machinery & Materials) ;
  • Chang, Mu-Seong (Department of Reliability Assessment, Korea Institute of Machinery & Materials) ;
  • Park, Jong-Won (Department of Reliability Assessment, Korea Institute of Machinery & Materials) ;
  • Lee, Yong-Bum (Department of Reliability Assessment, Korea Institute of Machinery & Materials)
  • 엄학용 (한국기계연구원 신뢰성평가연구실) ;
  • 이기천 (한국기계연구원 신뢰성평가연구실) ;
  • 장무성 (한국기계연구원 신뢰성평가연구실) ;
  • 박종원 (한국기계연구원 신뢰성평가연구실) ;
  • 이용범 (한국기계연구원 신뢰성평가연구실)
  • Received : 2018.02.20
  • Accepted : 2018.07.26
  • Published : 2018.09.25

Abstract

Purpose: In this study, the life of the motor is investigated by performing the accelerated life test with the brush wear of the industrial cleaner motor as the main failure mode. Methods: The accelerating stress factor of the accelerated life test is a voltage, which can increase the number of revolutions of the motor to accelerate the brush wear due to the friction between the brush and the commutator. Also, the accelerating stress level was determined after determining the maximum allowable level of the voltage through the preliminary test. Results: The motor failure time at each accelerating stress level was predicted by regression analysis with brush wear length as performance degradation data. The main failure mode, which is brush wear, of the motor was reproduced by this test. The shape parameter of the Weibull distribution was confirmed to be the same statistically at all accelerating stress levels by the likelihood ratio test. Conclusion: The life of the motor was investigated by performing the accelerated life test with the brush wear of the industrial cleaner motor as the main failure mode. Through the accelerating test method of the cleaner motor, various life expectancy and life expectancy of the acceleration factor are predicted.

Keywords

References

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