scholarly journals A Knowledge Modeling Method of Blast Furnace Fault Diagnosis Based On Ontology

2012 ◽  
Author(s):  
Yajun Zhang ◽  
Jinliang Shi ◽  
Guorong Chen
Keyword(s):  
Blast Furnace ◽  
Fault Diagnosis ◽  
Modeling Method ◽  
Knowledge Modeling

scholarly journals Optional SVM for Fault Diagnosis of Blast Furnace with Imbalanced Data

2011 ◽  
Vol 51 (9) ◽  
pp. 1474-1479 ◽  
Author(s):  
Limei Liu ◽  
Anna Wang ◽  
Mo Sha ◽  
Xiyan Sun ◽  
Yunlu Li
Keyword(s):  
Blast Furnace ◽  
Fault Diagnosis ◽  
Imbalanced Data

Phasor Analysis Based Fault Modeling and Fault Diagnosis Methods for Linear Analog Circuits

2014 ◽  
Vol 981 ◽  
pp. 3-10 ◽  
Author(s):  
Yuan Gao ◽  
Cheng Lin Yang ◽  
Shu Lin Tian
Keyword(s):  
Fault Diagnosis ◽  
Data Base ◽  
Analog Circuit ◽  
Feature Selection Method ◽  
Fault Modeling ◽  
Modeling Method ◽  
Support Vector ◽  
Linear Analog ◽  
Circuit Fault Diagnosis ◽  
Phasor Analysis

Soft fault diagnosis and tolerance are two challenging problems in linear analog circuit fault diagnosis. To solve these problems, a phasor analysis based fault modeling method and its theoretical proof are presented at first. Second, to form fault feature data base, the differential voltage phasor ratio (DVPR) is decomposed into real and imaginary parts. Optimal feature selection method and testability analysis method are used to determine the optimal fault feature data base. Statistical experiments prove that the proposed fault modeling method can improve the fault diagnosis robustness. Then, Multi-class support vector machine (SVM) classifiers are used for fault diagnosis. The effectiveness of the proposed approaches is verified by both simulated and experimental results.

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