The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
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Status Diagnosis of Pump and Motor Applying K-Nearest Neighbors

K-최근접 이웃 알고리즘을 적용한 펌프와 모터의 상태 진단

  • 김남진 (전남대학교 전기 및 반도체공학과) ;
  • 배영철 (전남대학교 전기.전자통신.컴퓨터공학부)
  • Received : 2018.11.08
  • Accepted : 2018.12.15
  • Published : 2018.12.31
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Abstract

Recently the research on artificial intelligence is actively processing in the fields of diagnosis and prediction. In this paper, we acquire the data of electrical current, revolution per minute (RPM) and vibration that is occurred in the motor and pump where hey are installed in the industrial fields. We train the acquired data by using the k-nearest neighbors. Also, we propose the status diagnosis methods that judges normal and abnormal status of motor and pump by using the trained data. As a proposed result, we confirm that normal status and abnormal status are well judged.

최근 인공지능에 대한 연구가 진단과 예측 분야에서 활발하게 진행되고 있다. 본 논문에서는 산업 현장에 설치되어 있는 모터와 펌프에서 발생하는 진동, 회전 수, 전류 데이터 취득한다. 취득한 데이터로부터 k-최근접 이웃(k-nearest neighbors) 알고리즘을 적용하여 이들 데이터를 학습하고, 학습한 데이터를 이용하여 펌프와 모터의 이상상태와 건전 상태를 판단하는 상태진단법을 제안한다. 제안 결과 정상상태와 이상상태가 잘 구분됨을 확인할 수 있었다.

Keywords

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그림 1. 펌프와 모터의 진동 신호 취득 시스템 Fig. 1 Vibration signal acquisition system of pump and motor

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그림 2. 펌프와 모터의 전류와 회전수 취득 시스템 Fig. 2 Current and RPM signal acquisition system of pump and motor

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그림 3. 진동 신호 Fig. 3 Vibration signal

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그림 4. 전류 신호 Fig. 4 Current signal

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그림 5. 회전수 신호 Fig. 5 RPM signal

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그림 6. 부싱 마모 수리 Fig. 6 Repair for bushing abrasion

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그림 7. 모터에서 측정한 전류, 회전수, 진동수의 정상과 이상 상태 Fig. 7 Normal and abnormal status of current, RPM, and vibration in motor and pump

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그림 6. K = 3, K= 5일 때 ‘K-최근접 이웃’ 알고리즘 Fig. 6 K-nearest neighbors algorithm when K=3, K=5

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그림 7. 특성에 따른 산포도와 결정 경계 Fig. 7 Decision boundary and scattering plot according to characteristics

표 1. 특성에 따른 예측 정확도 Table 1. Prediction accuracy according characteristics

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표 2. 각 특성과 측정값에 따른 모터의 상태 Table 2. Motor status according to each characteristics and measurement value

KCTSAD_2018_v13n6_1249_t0002.png 이미지

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