期刊
INFORMATION SCIENCES
卷 513, 期 -, 页码 553-564出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2019.11.010
关键词
Feature production; Chaotic mapping strategy; Smart machine
资金
- Ministry of Science and Technology MOST [107-2628-E-027-003-MY3]
In this paper, a smart fault-detection approach with feature production and extraction procedures is developed for industrial ball bearing systems. By developing a set of chaotic-mapping systems composed of a main system and data-feeding system with appropriate parameters, the vibration signals of different fault states captured from ball bearings in the time domain can be mathematically mapped to the chaotic domain for feature production. Furthermore, through the designed feature extraction process, the relevant Euclidean feature values (EFVs) can be obtained for the classification of four different fault states. Three fault conditions at diameters of 7 mil, 14 mil, and 21 mil and a depth of 0.011 inches are illustrated for performance investigations. The experimental results show that the proposed smart detection approach is effective and feasible for identifying different fault states in real time. (C) 2019 Published by Elsevier Inc.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据