Ball nut preload diagnosis of the hollow ball screw through sensed current signals

Yi Cheng Huang, Shi Lun Sun, Kuan Heng Peng

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


This paper studies the diagnostic results of hollow ball screws with different ball nut preload levels through the Hilbert-Huang transform (HHT) and multiscale entropy (MSE) process. The method is tested using ball screw pretension and an oil cooling circulation system. MSE was used to determine the hollow ball screw preload status through the servo motor current signals. Ball screws with maximum dynamic preloads of 2%, 4%, and 6% were predesigned, manufactured, and tested. Signal patterns are discussed and revealed by the Hilbert Spectrum. Different preload features are extracted using HHT and MSE. The irregularity development of the ball screw driving motion current can be discriminated and abstracted via MSE based on complexity perception. Experimental results show that the proposed approach can successfully predict the prognostic status of ball nut preload. A comparative evaluation of MSE allows for smart sensing for the health of the ball screw. This method effectively diagnoses the ball nut preload status.

Original languageEnglish
Pages (from-to)134-142
Number of pages9
JournalInternational Journal of Automation and Smart Technology
Issue number3
Publication statusPublished - 2014

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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