DocumentCode :
3293598
Title :
Fault Line Detection of Leakage Protection System of Mine Based on Rough Sets and Support Vector Machine
Author :
Shi Xiaoyan ; Zhu Longji
Author_Institution :
Anhui Univ. of Sci. & Technol., Huainan, China
fYear :
2012
fDate :
July 31 2012-Aug. 2 2012
Firstpage :
402
Lastpage :
405
Abstract :
For the complexity and multiformity of leakage faults of mine, the fault information has the uncertainty. With the capability of the solving the uncertain problem, Rough Sets theory can determine the fault timely and accurately. The paper adopted Rough Sets to extract the attribute characteristics of leakage fault signal and then to build the decision table. As the training sample of Support Vector Machine, the criterion by decision rules between the leakage fault signals and line detection method to detect fault line accurately can be gotten. The test results show that adopting the Rough Sets and Support Vector Machine to detect fault line is simple, efficient and good robustness.
Keywords :
coal; electrical faults; fault diagnosis; leak detection; learning (artificial intelligence); mechanical engineering computing; mining; power cables; reliability; rough set theory; support vector machines; attribute characteristics; decision rules; decision table; fault line detection method; leakage fault information; leakage fault signal; leakage protection system; rough set theory; support vector machine; training sample; Circuit faults; Data mining; Fault detection; Fault diagnosis; Rough sets; Support vector machines; Leakage Protection; Rough Set (RS); Support Vector Machine (SVM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
Conference_Location :
GuiLin
Print_ISBN :
978-1-4673-2217-1
Type :
conf
DOI :
10.1109/ICDMA.2012.96
Filename :
6298337
Link To Document :
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