The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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A Study on the Diagonosis and Prediction System of Vehicle Faults Using Condition Based Maintenance Technique

상태기반 유지보수 기법을 적용한 차량고장 진단 및 예측 시스템 연구

  • 송길종 ((주)엔제로 기업부설연구소 교통팀) ;
  • 임재중 ((주)엔제로 기업부설연구소)
  • Received : 2019.03.19
  • Accepted : 2019.08.03
  • Published : 2019.08.31
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Abstract

Recently, with the development of sensor and communication technology, researchers at home and abroad have actively conducted research on methodologies for determining maintenance through diagnosis and prediction techniques by collecting information on the status of equipment or systems. Based on the status of vehicle parts at this point in time, this study presented a system framework for making maintenance decisions by predicting the change in vehicle part status to a future date based on the current state of vehicle parts. In addition, condition diagnosis and predictive data adjustment was configured through tracking the status of vehicle parts before and after maintenance activities. We hope that the application of the results of this study will contribute a little to the safety of citizens using public buses and to the activation of the condition-based maintenance system of vehicles.

최근 들어 센서 및 통신기술의 발달로 국내외 연구자들은 장비나 시스템의 상태정보를 수집하여 진단 및 예측 기법을 통한 유지보수를 결정하는 방법론에 대해 연구를 활발히 진행하고 있다. 본 연구에서는 이러한 연구 문헌 고찰을 통해 현시점의 차량부품 상태를 바탕으로 미래 시점까지의 차량부품 상태변화 추이를 예측하여 유지보수 의사결정을 수행하는 시스템 프레임워크를 제시하였다. 또한, 유지보수 활동에 따른 전과 후의 차량부품 상태변화 추적을 통해서 상태 진단 및 예측 데이터 조정이 가능하도록 구성하였다. 향후 본 연구 결과의 적용을 통해 대중버스를 이용하는 시민들의 안전과 차량의 상태기반 유지보수 체계 활성화에 조금이나마 기여할 수 있기를 기대한다.

Keywords

References

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