Similarity measures in Small World Stratification for distribution fault diagnosis

2011 ◽  
Author(s):  
Yixin Cai ◽  
Mo-Yuen Chow
Keyword(s):  
Fault Diagnosis ◽  
Similarity Measures ◽  
Small World

COMPLEX NETWORK APPLICATION IN FAULT DIAGNOSIS OF ANALOG CIRCUITS

2011 ◽  
Vol 21 (05) ◽  
pp. 1323-1330 ◽  
Author(s):  
MINFANG PENG ◽  
JIAJIA WANG ◽  
CHI K. TSE ◽  
MEIE SHEN
Keyword(s):  
Fault Diagnosis ◽  
Complex Network ◽  
Analog Circuits ◽  
Large Scale ◽  
Fault Simulation ◽  
Small World ◽  
Main Task ◽  
Electronic Circuits ◽  
Successful Isolation ◽  
High Degree

Fault diagnosis has played an important role in the identification of fault mechanisms and the subsequent successful isolation of faults in electronic circuits. In this paper, we propose a novel procedure for fault diagnosis in analog circuits. We first generate a set of fault patterns from fault simulation, and our main task is to develop a practical description of the way in which these fault patterns interact. Our approach is based on the construction of a complex network that describes the inter-dependence of the various fault patterns. Analysis of this complex network shows that the degree distribution is scalefree-like and the connectivity is small-world. We henceforth identify a small number of fault patterns that are most highly connected (of highest degrees) with other fault patterns. Furthermore, we study the connection between this network of fault patterns and the original circuit, the purpose being to relate the information of the high-degree fault patterns with the physical circuit topology, thus allowing the physical fault locations and circuit elements to be identified. Our proposed approach will find applications in automatic fault diagnosis of large-scale electronic circuits.

A New Similarity Measure of Picture Fuzzy Sets And Application in pattern recognition

2020 ◽  
pp. 5-18
Author(s):  
Ngoc Minh Chau, Nguyen Thi Lan, Nguyen Xuan Thao ◽  
Keyword(s):  
Pattern Recognition ◽  
Fault Diagnosis ◽  
Fuzzy Sets ◽  
Steam Turbine ◽  
Similarity Measure ◽  
Fuzzy Set ◽  
Similarity Measures ◽  
The Novel ◽  
Picture Fuzzy Set ◽  
Picture Fuzzy Sets

In this paper, we propose some novel similarity measures between picture fuzzy sets. The novel similarity measure is constructed by combining negative functions of each degree membership of picture fuzzy set. We apply them in several pattern recognition problems. Finally, we apply them to find the fault diagnosis of the steam turbine.

scholarly journals The Fourth Axiom of Similarity Measures

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1735 ◽  
Author(s):  
Chun-Hsiao Chu ◽  
Chih-Ping Yen ◽  
Yi-Fong Lin
Keyword(s):  
Pattern Recognition ◽  
Fault Diagnosis ◽  
Correlation Coefficient ◽  
Similarity Measure ◽  
Intuitionistic Fuzzy Set ◽  
Similarity Measures ◽  
Turbine Engine ◽  
Symmetric Structure ◽  
Source Paper ◽  
Weighted Correlation

In this research, the fourth axiom to improve the well-defined examination of similarity measures is studied, where the measures have a symmetric structure. We first provide a theoretic enhancement of three correlation coefficient similarity measures that were proposed by a source paper. Second, we use the same numerical example proposed by the source paper for pattern recognition problems to illustrate that the weighted correlation coefficient similarity measure is dependent on the set of weights. Finally, we demonstrate that the correlation coefficient similarity measure in the intuitionistic fuzzy set environment can address the issue of practical fault diagnosis when solving the turbine engine problems using similarity measures with symmetric characteristics.

scholarly journals A New Similarity Measure of Generalized Trapezoidal Fuzzy Numbers and Its Application on Rotor Fault Diagnosis

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Xin Zuo ◽  
Lijun Wang ◽  
Yuanlong Yue
Keyword(s):  
Fault Diagnosis ◽  
Similarity Measure ◽  
Fuzzy Numbers ◽  
Similarity Measures ◽  
Vital Role ◽  
Trapezoidal Fuzzy Numbers ◽  
Comparison Results ◽  
Rotor Experiment ◽  
Calculation Results ◽  
Generalized Trapezoidal Fuzzy Numbers

Fault diagnosis technology plays a vital role in the variety of critical engineering applications. Fuzzy approach is widely employed to cope with decision-making problems because it is in the simplest and most used form. This paper proposed a new similarity measure of generalized trapezoidal fuzzy numbers used for fault diagnosis. The presented similarity measure combines concepts of the geometric distance, the center of gravity point, the perimeter, and the area of the generalized trapezoidal fuzzy numbers for calculating the degree of similarity between generalized trapezoidal fuzzy numbers. This method is proposed to deal with both standardized and nonstandardized generalized trapezoidal fuzzy numbers. Some properties of the proposed similarity measure have been proved, and 12 sets of generalized fuzzy numbers have been used to compare the calculation results of the proposed similarity measures with the existing similarity measures. Comparison results indicate that the proposed similarity measure can overcome the drawbacks of existing similarity measures. Finally, a fault diagnosis experiment is carried out in laboratory based on multifunctional flexible rotor experiment bench. Experimental results demonstrate that the proposed similarity measure is more effective than other methods in terms of rotor fault diagnosis.

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