BALL SCREW PRELOAD LOSS DETECTION BASED ON VIBRATION HOLOSPECTRA

C. C. Cheng, Y. S. Chiu, C. S. Liu, C. K. Sung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A method of detecting ball screw preload loss in feed drive systems of machine tools using vibration signals was proposed in this study. By attaching a triaxial accelerometer on the ball screw nut, the vibration amplitudes and phases of a rotating ball screw were extracted using Vold-Kalman Filtering Order Tracking (VKFOT). Holospectra were constructed to represent the rotating ball screw loci at the ball pass frequency and its multiplier in time domain. Then features extracted from the corresponding holospectra were quantified into metrices as a measure signifying the severity of ball screw preload loss using a self-organizing map. Experimental results indicated that the proposed method successfully detected the ball screw with three different levels of severity of ball screw preload loss, which also demonstrated the high sensitivity and effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings of the 29th International Congress on Sound and Vibration, ICSV 2023
EditorsEleonora Carletti
PublisherSociety of Acoustics
ISBN (Electronic)9788011034238
Publication statusPublished - 2023
Event29th International Congress on Sound and Vibration, ICSV 2023 - Prague, Czech Republic
Duration: 2023 Jul 92023 Jul 13

Publication series

NameProceedings of the International Congress on Sound and Vibration
ISSN (Electronic)2329-3675

Conference

Conference29th International Congress on Sound and Vibration, ICSV 2023
Country/TerritoryCzech Republic
CityPrague
Period23-07-0923-07-13

All Science Journal Classification (ASJC) codes

  • Acoustics and Ultrasonics

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