Application of Rough Set Theory in Fault Diagnostic Rules Acquisition

被引：1

作者：

殷晨波 ^{[1
]}

周庆敏 ^{[2
]}

李永生 ^{[1
]}

机构：

[1] College of Mechanical and Power Engineering, Nanjing University of Technology

[2] College of Information Science and Engineering, Nanjing University of Technology

来源：

JournalofDonghuaUniversity(EnglishEdition) | 2007年 / 02期

关键词：

variable precision rough set; fault diagnosis; rules acquisition;

D O I：

10.19884/j.1672-5220.2007.02.029

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Rough set theory is a new mathematical tool to deal with vagueness and uncertainty. But original rough sets theory only generates deterministic rules and deals with data sets in which there is no noise. The variable precision rough set model (VPRSM) is presented to handle uncertain and noisy information. A method based on VPRSM is proposed to apply to fault diagnosis feature extraction and rules acquisition for industrial applications. An example for fault diagnosis of rotary machinery is given to show that the method is very effective.

引用

页码：276 / 279

页数：4

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