• DocumentCode
    693545
  • Title

    Poster abstract: Enabling a cloud-based logging service for ball screw with an autonomous networked sensor system

  • Author

    Huang-Chen Lee ; Yu-Chang Chang ; Yen-Shuo Huang ; Wei-Kuan Wang ; Yuan-Sun Chu

  • Author_Institution
    Dept. of Commun. Eng., Nat. Chung-Cheng Univ., Minxiong, Taiwan
  • fYear
    2013
  • fDate
    8-11 April 2013
  • Firstpage
    341
  • Lastpage
    342
  • Abstract
    Precision ball screw assembly (hereafter called “ball screw”), as shown in Fig. 1, is a mechanical wear out part that widely used in CNC (computer numerical control) machine tools to control the movement of processing targets and spindles. Up until now, there has been no simple way to directly measure ball screw for knowing the state of wear quantitatively. An indirect approach is logging all the signals (vibration, temperature, and preload change) during the operation of ball screw, and to use them to construct the wear model for estimating its remaining lifetime. To achieve this goal, we proposed a cloud-based logging system in this study that emphasizes (1) logging all the signals during operation in a ball screw´s whole lifetime, and transferring to the data server without data loss; and (2) saving all the data into the cloud data storage of the ball screw´s manufacturer. The data collected from many ball screws can be used to analyze and construct the wear model of ball screw, allowing the manufacturer to understand the state of wear and send a warning to the tool machine´s owner before excessive wear.
  • Keywords
    ball screws; machine tools; wear; wireless sensor networks; autonomous networked sensor system; cloud data storage; cloud-based logging service; data server; precision ball screw assembly; wear model; Assembly; Fasteners; Machine tools; Servers; Vibrations; Wireless communication; Wireless sensor networks; ball screw; factory; wireless sensor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Processing in Sensor Networks (IPSN), 2013 ACM/IEEE International Conference on
  • Conference_Location
    Philadelphia, PA
  • Type

    conf

  • DOI
    10.1109/IPSN.2013.6917588
  • Filename
    6917588