Abnormal State Detection for Rolling Bearings Using DBSE Approach
文献类型:会议论文
作者 | Gui J(桂珺)1,2,3,4![]() ![]() ![]() |
出版日期 | 2019 |
会议日期 | December 6-9, 2019 |
会议地点 | Chengdu, China |
关键词 | rolling bearing fault diagnosis distribution-based states extraction |
页码 | 1366-1370 |
英文摘要 | Rolling bearings play an important role in mechanical equipment. Abnormal state detection of rolling bearings is significant to avoid industrial accident. In this paper, we use Distribution-based States Extraction (DBSE) approach to detect and analyze the abnormal state of rolling bearings. We apply DBSE approach on three different datasets. Each dataset contains time series of horizon acceleration and vertical acceleration right before a specific fault of a rolling bearing. The results show that the DBSE is able to extract normal states and abnormal states before all three faults and effective for fault prediction. By analyzing statistical properties of two states for all three faults, we find distributions of acceleration data on two states are quite different. Further more, we find that standard deviations are more effective to describe features of different states than means of acceleration data. Our finding are great useful for abnormal detection and fault prediction. |
产权排序 | 1 |
会议录 | 2019 IEEE 5th International Conference on Computer and Communications, ICCC 2019
![]() |
会议录出版者 | IEEE |
会议录出版地 | NEW YORK |
语种 | 英语 |
ISBN号 | 978-1-7281-4743-7 |
源URL | [http://ir.sia.cn/handle/173321/26756] ![]() |
专题 | 沈阳自动化研究所_数字工厂研究室 |
通讯作者 | Gui J(桂珺) |
作者单位 | 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.University of Chinese Academy of Sciences, Beijing 100049, China 3.School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, China 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China |
推荐引用方式 GB/T 7714 | Gui J,Zheng ZY,Zhao XF,et al. Abnormal State Detection for Rolling Bearings Using DBSE Approach[C]. 见:. Chengdu, China. December 6-9, 2019. |
入库方式: OAI收割
来源:沈阳自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。