title: The development of a monitoring system using a Wireless and Powerless Sensing Node deployed inside a spindle.
abstract: Installation of a Wireless and Powerless Sensing Node (WPSN) inside a spindle enables the direct transmission of monitoring signals through a metal case of a certain thickness instead of the traditional method of using connecting cables. Thus, the node can be conveniently installed inside motors to measure various operational parameters. This study extends this earlier finding by applying this advantage to the monitoring of spindle systems. After over 2 years of system observation and optimization, the system has been verified to be superior to traditional methods. The innovation of fault diagnosis in this study includes the unmatched assembly dimensions of the spindle system, the unbalanced system, and bearing damage. The results of the experiment demonstrate that the WPSN provides a desirable signal-to-noise ratio (SNR) in all three of the simulated faults, with the difference of SNR reaching a maximum of 8.6 dB. Following multiple repetitions of the three experiment types, 80% of the faults were diagnosed when the spindle revolved at 4,000 rpm, significantly higher than the 30% fault recognition rate of traditional methods. The experimental results of monitoring of the spindle production line indicated that monitoring using the WPSN encounters less interference from noise compared to that of traditional methods. Therefore, this study has successfully developed a prototype concept into a well-developed monitoring system, and the monitoring can be implemented in a spindle production line or real-time monitoring of machine tools.
authors.affiliation: Graduate Institute of Mechanical and Electrical Engineering, National Taipei University of Technology, No. 1, Sec. 3 Zhongxiao E. Rd., Taipei City, 106, Taiwan. t5669016@ntut.org.tw
authors.forename: Liang-Cheng
authors.initials: LC
authors.lastname: Chang
authors.forename: Da-Sheng
authors.initials: DS
authors.lastname: Lee
mesh_terms: D000054:Acceleration; D003198:Computer Simulation; D019544:Equipment Failure Analysis / Q000295:instrumentation* / Q000379:methods*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D059629:Signal-To-Noise Ratio; D013057:Spectrum Analysis; D013223:Statistics as Topic; D013997:Time Factors; D014732:Vibration; D059015:Wireless Technology / Q000295:instrumentation*