@inproceedings{cc65444fed6e45da8cb0b362627c0718,
title = "BALL SCREW PRELOAD LOSS DETECTION BASED ON VIBRATION HOLOSPECTRA",
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.",
author = "Cheng, {C. C.} and Chiu, {Y. S.} and Liu, {C. S.} and Sung, {C. K.}",
note = "Funding Information: This study was partially supported by Hiwin Technologies Corporation; and the National Science and Technology Council, Taiwan (grant no. NSTC 111-2218-E-002-032; grant no. MOST 110-2221-E-194 -035 -MY2). Publisher Copyright: {\textcopyright} 2023 Proceedings of the International Congress on Sound and Vibration. All rights reserved.; 29th International Congress on Sound and Vibration, ICSV 2023 ; Conference date: 09-07-2023 Through 13-07-2023",
year = "2023",
language = "English",
series = "Proceedings of the International Congress on Sound and Vibration",
publisher = "Society of Acoustics",
editor = "Eleonora Carletti",
booktitle = "Proceedings of the 29th International Congress on Sound and Vibration, ICSV 2023",
}