• DocumentCode
    2049476
  • Title

    Data acquisition and management of remote crane monitoring system based on CAN bus

  • Author

    Zhufeng Li ; Guangquan Yang ; Xusheng Du ; Xin Liu

  • Author_Institution
    Transp. & Econ. Res. Inst., China Acad. of Railway Sci., Beijing, China
  • fYear
    2015
  • fDate
    2-5 Aug. 2015
  • Firstpage
    2460
  • Lastpage
    2465
  • Abstract
    Data acquisition and management are key links of RCMS. Without reasonable data acquisition method or excellent data organization and management structure, the reliable operation of RCMS is impossible. In this paper, the architecture of remote crane monitoring data flow is established, and sorted data acquisition is analyzed and designed according to the characteristics of field monitoring data, and hybrid acquisition of mass of different data is solved. The E-R database model and data management structure is established, thus improves the robustness and maintainability of monitoring system. In order to ensure the data continuity during the disconnection-recovery of field wireless network, real-time database and CMS gateway are designed. This study solves the data acquisition and data management of RCMS and based on this, further fault diagnosis, performance prediction and none downtime intelligent maintenance of cranes are much more prone to implement.
  • Keywords
    control engineering computing; controller area networks; cranes; data acquisition; database management systems; fault diagnosis; field buses; CAN bus; E-R database model; RCMS; data acquisition; data management; fault diagnosis; field wireless network disconnection-recovery; remote crane monitoring system; Cranes; Data acquisition; Databases; Logic gates; Monitoring; Real-time systems; Reliability; CAN bus; acquisition; data flow; data management; database;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2015 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-7097-1
  • Type

    conf

  • DOI
    10.1109/ICMA.2015.7237873
  • Filename
    7237873