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소형 모사 장비의 데이터를 이용한 선박용 전기 추진 모터의 고장 유형별 진동 신호의 분류

Classification of Vibration Signals for Different Types of Failures in Electric Propulsion Motors for Ships Using Data from Small-Scale Apparatus

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초록

With the enforcement of environmental regulations by the International Maritime Organization, the market for eco-friendly ships is expanding, and ships using electric propulsion devices are emerging as a promising solution. Many studies have been conducted to predict the failure of ships, but most of them are mainly research on the main diesel engine of ships. As the ship's propulsion method changes, new data is needed to predict the failure of electric propulsion ships. In this paper aims to analyze the failure characteristics of the electric propulsion system in consideration of the difference in the type of failure between the internal diesel engine and the electric propulsion system. The ship's propulsion unit assumed a DC motor and a signal pattern for normal conditions and general failure modes, but the failure record of the electric propulsion device operated on the actual ship was not available, so it generated a failure signal for small electric motor equipment to identify the failure signal. Assuming unbalance, misalignment, and bearing failure, which are the primary failure modes of the ship's electric motor, a failure signal was generated using a "rotator vibration data generator," and the frequency band, size, and phase difference of the measured vibration signal were analyzed to analyze the characteristics of each failure condition. Finally, the characteristics of each failure condition were identified so that the signals according to the failure type could be classified.

Abstract

With the enforcement of environmental regulations by the International Maritime Organization, the market for eco-friendly ships is expanding, and ships using electric propulsion devices are emerging as a promising solution. Many studies have been conducted to predict the failure of ships, but most of them are mainly research on the main diesel engine of ships. As the ship's propulsion method changes, new data is needed to predict the failure of electric propulsion ships. In this paper aims to analyze the failure characteristics of the electric propulsion system in consideration of the difference in the type of failure between the internal diesel engine and the electric propulsion system. The ship's propulsion unit assumed a DC motor and a signal pattern for normal conditions and general failure modes, but the failure record of the electric propulsion device operated on the actual ship was not available, so it generated a failure signal for small electric motor equipment to identify the failure signal. Assuming unbalance, misalignment, and bearing failure, which are the primary failure modes of the ship's electric motor, a failure signal was generated using a "rotator vibration data generator," and the frequency band, size, and phase difference of the measured vibration signal were analyzed to analyze the characteristics of each failure condition. Finally, the characteristics of each failure condition were identified so that the signals according to the failure type could be classified.

참고문헌 (9)

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  3. 김도희, "LSTM-AutoEncoder를 활용한 선박 메인엔진의 이상 탐지 및 라벨링", 한국빅데이터학회 학회지, 7(1), pp.125~137 (2022), 사)한국빅데이터학회[DOI]
  4. Kim, S.N., "Technology Trend of DC Electric Propulsion Ship", Fire Protection Technology, 44, pp.30~43 (2018)
  5. Kudelina, k., "Main Faults and Diagnostic Possibilities of BLDC Motors", International Workshop on Electric Drives (2020)
  6. Pandarakone, S. E., "Distinct Fault Analysis of Induction Motor Bearing Using Frequency Spectrum Determination and Support Vector Machine", Journal of Institute of Electrical and Electronics Engineers Transactions on Industry Applications, 53(6), pp.3049~3056 (2016)
  7. 박재철, "선박 추진용 2행정 저속엔진의 고장모드 데이터 개발 및 LSTM 알고리즘을 활용한 특성인자 신뢰성 검증연구", 대한조선학회 논문집, 60(2), pp.95~109 (2023), 대한조선학회[DOI]
  8. 박준현, "개선된 선박 엔진의 고장 예측 알고리즘", 한국정보기술학회논문지, 15(11), pp.175~185 (2017), 한국정보기술학회[DOI]
  9. Shifat, T.A., "An Effective Stator Fault Diagnosis Framework of BLDC Motor Based on Vibration and Current Signals", Journal of Institute of Electical and Electronics Engineers Access, 8(99), pp.106968~106981 (2020)

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