NDLI: Research on Data Mining Based on Rough Set and Its Application in Fault Diagnosis of Steam Turbine

Content Provider	IEEE Xplore Digital Library
Author	Qinglin Guo Cunbin Li
Copyright Year	2007
Description	Author affiliation: North China Electr. Power Univ., Beijing (Qinglin Guo)
Abstract	For overcoming shortages of some current knowledge attaining methods, a novel approach for fault forecast and diagnosis of steam turbine based on rough set data mining theory is brought forward. Data pretreatment, knowledge reduction and rule abstraction are three important problems in the research of rough set theory.The historical fault data of steam turbine is processed with fuzzy and scatter method. The processed data is used to structure the fault diagnosis decision-making table that is treated as "knowledge database". This paper introduced rough sets data mining method to take potential diagnosis rule from the fault diagnosis decision-making table of steam turbine. These rules can offer effective fault diagnosis service for steam turbine. The algorithm for classified rule learning and reducing is brought forward, and an experimental system for fault forecast and diagnosis of steam turbine based on rough set data mining theory is implemented. Their diagnosis precision is above 88%. And experiments do prove that it is feasible to use the method to develop a system for fault forecast and diagnosis of steam turbine, which is valuable for further study in more depth.
Starting Page	188
Ending Page	192
File Size	243722
Page Count	5
File Format	PDF
ISBN	9780769528748
DOI	10.1109/FSKD.2007.473
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Databases Decision making Scattering Rough sets Fuzzy set theory Data mining Turbines Diagnostic expert systems Fuzzy systems
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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