Application of Fuzzy Rough Sets in Patterns Recognition of Bearing
SHEN Ren-fa1; ZHENG Hai-qi1 ; QI Yan-jie2; KANG Hai-ying1
1.Department of Guns Engineering, Ordnance Engineering College, Shijiazhuang, 050003, China;2. Dept. of Basic Courses, Xuzhou Air Force College, Xuzhou, 221000, China
Abstract:A method of patterns recognition was presented based on fuzzy rough sets. Dynamic clustering algorithm and method of anaiysis of variance is introduced to fuzzify the continuous condition attribute, and fuzzy membership functions is derived, which avoided losing information caused by discretization in rough set theory. test is introduced to judge the valid analysis of clustering, which has overcome the disadvantage of determining artificially the class number of clustering. The fuzzy decision table obtained by attribute fuzzified is used to attributes reduction, then values of attributes are reducted, and clear and concise pattern rules are obtained. The application to in fault of bearing shows the proposed algorithm can raises the accuracy greatly in contrast with normal rough sets, and is a good method in applications to f patterns recognition.