• DocumentCode
    3578279
  • Title

    Energy Efficient Machine Condition Monitoring Using Wireless Sensor Networks

  • Author

    Bergmann, Neil W. ; Li-Qun Hou

  • Author_Institution
    Sch. of Inf. Technol. & Electr. Eng., Univ. of Queensland, Brisbane, QLD, Australia
  • fYear
    2014
  • Firstpage
    285
  • Lastpage
    290
  • Abstract
    An Industrial Wireless Sensor Network system is described for condition monitoring of electric machines. On-sensor data processing is used to reduce the amount of information that needs to be transmitted, thus saving communications energy. Based on a condition monitoring interval of 3 seconds, and using 2 AAA batteries for power, the system lifetime is measured for four different operating modes. For raw data transmission to the coordinator, the system lifetime is 106 hours. If feature extraction is done on the sensor node, this is extended to 152 hours. If fault diagnosis is done on the node, the lifetime is 153 hours. If fault diagnosis is conducted every 3 seconds but results are only sent under fault conditions, or once per hour as a health check, then lifetime is dramatically increased to 1764 hours.
  • Keywords
    condition monitoring; electric machines; fault diagnosis; feature extraction; wireless sensor networks; communications energy; condition monitoring interval; electric machines; energy efficient machine condition monitoring; fault conditions; fault diagnosis; feature extraction; health check; industrial wireless sensor networks; on-sensor data processing; operating modes; sensor node; system lifetime; time 106 hr; time 153 hr; time 1764 hr; time 3 s; Batteries; Condition monitoring; Fault diagnosis; Feature extraction; Monitoring; Wireless sensor networks; condition monitoring; energy efficiency; on-sensor processing; wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communication and Sensor Network (WCSN), 2014 International Conference on
  • Print_ISBN
    978-1-4799-7090-2
  • Type

    conf

  • DOI
    10.1109/WCSN.2014.65
  • Filename
    7061741