Knowledge Acquisition of Spindle bearings Fault Based on Rough Sets

摘要：

　　An identification method of spindle beating fault based on rough sets theory is proposed in the article.By collecting beatings typical fault signal and using signal information processing techniques,vibration fault data is obtained.Then,equidistant clustering analysis method is introduced into discretization of experimental data of continuous attributes.In this way,vibration fault data table meets the requirement of rough sets data analysis.Besides,attribute importance algorithm is used in order to realize the reduction of condition attribute in the decision table.Thus,fault information which hidden in huge signal data is extracted.Therefore,simple and clear fault pattern rules are acquired.The result indicates that the method can realize fault pattern identification of spindles bearings and it is of great application value in practical fault pattern identification.

关键词： rough sets knowledge acquisition bearings fault decision table

作者: Xiaozheng Xie Rongzhen Zhao li Yang Yunping Yao

作者单位: Lanzhou University of Technology,Lanzhou,Gansu Province,730050,P.R.China;Key Laboratory of Digital M Gansu Blue Star Cleaning Technology Co.,Ltd.Lanzhou,Gansu Province,730060,P.R.China

会议类型: 国际会议

会议名称: the 2012 2nd International Conference on Frontiers of Manufacturing Science and Measuring Technology (第二届制造科学与检测技术国际会议(ICFMM 2012))

会议地点: 西安

会议语种:英文

页码: 1133-1136

在线出版日期: 2012-06-12（万方平台首次上网日期，不代表论文的发表时间）