首页 | 本学科首页   官方微博 | 高级检索  
     


Fuzzy-based Refinement of the Fault Diagnosis Task in Industrial Devices
Authors:C.?D.?Bocaniala  author-information"  >  author-information__contact u-icon-before"  >  mailto:Cosmin.Bocaniala@ugal.ro"   title="  Cosmin.Bocaniala@ugal.ro"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,J.?Sa?Da?Costa,V.?Palade
Affiliation:(1) Computer Science and Engineering Department, University “Dunarea de Jos” of Galati, Domneasca 47, Galati, 6200, Romania;(2) Department of Mechanical Engineering, Technical University of Lisbon, Instituto Superior Tecnico, GCAR/IDMEC, Avenida Rovisco Pais, Lisboa, 1096, Portugal;(3) Computing Laboratory, Oxford University, Wolfson Building, Parks Road, Oxford, OX1 3QD, UK
Abstract:This paper first describes a fuzzy classifier to be used for fault diagnosis. Then, the paper presents a refinement of the diagnosis task performed with this fuzzy classifier. For each fault, a number of 20 levels of fault strength have been considered. In previous work, more than one single category per fault has been used to improve the classifier performance, i.e. distributing the strength levels into small, medium and, respectively large strength subsets. However, this distribution scheme is too rigid. This paper introduces a flexible distribution scheme that takes into account the (di)similarities between different strength levels. The refinement proposed here offers better insight on the behavior of each fault and it increases separation between overlapping faults, which improves the final outcome of the diagnosis process.
Keywords:fault diagnosis  fault isolation refinement  pattern recognition  fuzzy logic  particle swarm optimisation
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号