Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Electric Power Automation Equipment》 2007-12
Add to Favorite Get Latest Update

Rule-plus-exception model of knowledge extraction for fault diagnosis of turbine-generator unit

HUANG Wen-tao1,2,WANG Wei-jie2,ZHAO Xue-zeng 2,MENG Qing-xin1(1.School of Mechatronics Engineering,Harbin Engineering University,Harbin 150001,China;2.School of Mechatronics Engineering,Harbin Institute of Technology,Harbin 150001,China)  
An improved rule-plus-exception model of cognitive psychology and machine learning is proposed based on the analysis of fault diagnosis samples regularity and rough set reduction technique,which is suitable for extracting the decision rules from the fault data containing inconsistent information.It is described in detail with its essential structure,and the example of turbine-generator unit fault diagnosis proves its feasibility and availability in which a short list of exceptions are considered,and the sample set is divided into two groups.Comparing the proposed model with the others,its superiority is proved not only on confidence,but also on the generalization ability and succinctness.
【Fund】: 中国博士后科学基金资助项目(20070410888)~~
【CateGory Index】: TP182;TM311
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved