FAULT DIAGNOSIS IN ROTATING MACHINERY USING FUZZY MEASURES AND FUZZY INTEGRALS

被引：0
|
作者：
Tsunoyama, Masahiro [1 ]
Masumori, Kensuke [1 ]
Hori, Hayato [2 ]
Jinno, Hirokazu [2 ]
Ogawa, Masayuki [2 ]
Sato, Tatsuo [2 ]
机构：
[1] Niigata Inst Technol, 1719 Fujihashi, Kashiwazaki, Niigata 9451195, Japan
[2] Niigata Worthington Co Ltd, Kashiwazaki, Niigata 9450056, Japan
来源：
ICFC 2010/ ICNC 2010: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON FUZZY COMPUTATION AND INTERNATIONAL CONFERENCE ON NEURAL COMPUTATION | 2010年
关键词：
Fault diagnosis; Fuzzy measure; Fuzzy integral; Vibration diagnosis;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In the fault diagnosis of rotating machinery using fuzzy measures and fuzzy integrals, the optimization of membership functions and identification of fuzzy measures are important for accurate diagnosis. Herein, a method for optimizing membership functions is proposed based on the statistical properties of vibration spectra and identifying fuzzy measures based on interaction levels using partial correlation coefficients between spectra. The possibility of a given fault is obtained from fuzzy integrals using membership degrees determined by the membership function, and the fuzzy measures for the set of spectra. The method is also evaluated using the example of diagnosis of misalignment and unbalance faults.
引用
收藏
页码：120 / 124
页数：5
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