드라이브 ㆍ 컨트롤 (Journal of Drive and Control)

  • 제18권1호
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  • Pages.24-30
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  • 2021
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  • 2671-7972(pISSN)
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  • 2671-7980(eISSN)
유공압건설기계학회 (The Korean Society for Fluid Power and Construction Equipment)
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굴착기 주행디바이스의 고장 진단을 위한 AI기반 상태 모니터링 시스템 개발

Development of AI-Based Condition Monitoring System for Failure Diagnosis of Excavator's Travel Device

  • Baek, Hee Seung (Advanced Research Team, R&D, Mottrol BG, Doosan Corporation) ;
  • Shin, Jong Ho (Department of Industrial Engineering, Chosun University) ;
  • Kim, Seong Joon (Department of Industrial Engineering, Chosun University)
  • 투고 : 2020.10.14
  • 심사 : 2021.02.22
  • 발행 : 2021.03.01
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초록

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.

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참고문헌

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