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무선 센서 네트워크 기반의 상태 모니터링을 위한 온도 데이터 시각화

Temperature Data Visualization for Condition Monitoring based on Wireless Sensor Network

  • 투고 : 2020.02.17
  • 심사 : 2020.04.15
  • 발행 : 2020.04.30

초록

예상치 못한 장비들의 결함은 우리 사회 전반에 막대한 경제적 손실을 초래하고, 이런 상황에서 상태 모니터링은 해결 가능한 방법을 제시할 수 있다. 상태 모니터링은 부착된 다양한 센서 데이터로부터 기계 고장을 예측하기 위해 신호 처리 알고리즘의 개발이 요구된다. 상태 모니터링에 사용되는 신호 처리 알고리즘은 높은 계산 효율과 고해상도를 요구하고 있다. 무선 센서 네트워크상(WSN)에서 상태 모니터링을 개선하기 위해서 데이터의 시각화는 데이터의 특징적인 표현을 극대화할 수 있다. 따라서 본 논문은 대규모 기반 시설에서 장비의 환경 상태를 식별하기 위해 WSN 기반의 상태 모니터링을 위한 온도 데이터의 시각적인 특징 추출을 제안한다. 실험 결과, 시간-주파수 분석은 시간에 따른 온도 변화를 시각적으로 확인할 수 있으며 온도 데이터 변화의 특징을 추출하는데 용이하였다.

Unexpected equipment defects can cause a huge economic losses in the society at large. Although condition monitoring can provide solutions, the signal processing algorithms must be developed to predict mechanical failures using data acquired from various sensors attached to the equipment. The signal processing algorithms used in a condition monitoring requires high computing efficiency and resolution. To improve condition monitoring on a wireless sensor network(WSN), data visualization can maximize the expressions of the data characteristics. Thus, this paper proposes the extraction of visual feature from temperature data over time using condition monitoring based on a WSN to identify environmental conditions of equipment in a large-scale infrastructure. Our results show that time-frequency analysis can visually track temperature changes over time and extract the characteristics of temperature data changes.

키워드

참고문헌

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