The Optimization of Threshold Value of the Relational Degree in Grey Theory Method for Fault Diagnosis

1997 ◽  
Author(s):  
Y. H. Liu ◽  
F. Ma
Keyword(s):  
Fault Diagnosis ◽  
Error Rate ◽  
Threshold Value ◽  
Grey Theory ◽  
Theory Method ◽  
Optimal Range ◽  
Relational Degree ◽  
New Ideas

Abstract In this paper, optimization of the threshold value of the relational degree in Grey Theory method for fault diagnosis is considered. With an emphasis on minimizing both the error rate and miss rate of fault diagnosis, new ideas are proposed to determine the optimal range of the threshold value. A practical example is given to demonstrate the feasibility of the proposed method.

Complex Fault Diagnosis Based on Immune Principle

2013 ◽  
Vol 433-435 ◽  
pp. 744-749
Author(s):  
Jian Cen ◽  
Xu Hong Zhang ◽  
Dan Xiang ◽  
Xu Lu
Keyword(s):  
Black Holes ◽  
Fault Diagnosis ◽  
Error Rate ◽  
Adaptive Threshold ◽  
Training Time ◽  
Selection Theory ◽  
Clone Selection ◽  
Complex Fault ◽  
Simulation Results ◽  
Paper Reply

To improve the accuracy of fault diagnosis, this paper reply to biological immune theory, candidate detectors have been created in non-self-space, according to biological mutation mechanism and the clone selection theory, to mature candidate detector and to reduce training time. Fault samples have classified in non-self-space, in order to reduce unclear boundaries of fault samples. The use of adaptive threshold are adapted to in the diagnosis process, to reduce the diagnosis of black holes arising, the error rate and missed rate reduce, therefore the accuracy of fault diagnosis improve. Fault test and simulation results show that the effectiveness of the method.

The Developmental Research on Fault Diagnosis System of Mine Fan Based on Grey Theory

2011 ◽  
Vol 105-107 ◽  
pp. 656-659 ◽  
Author(s):  
Dong Chen Li
Keyword(s):  
Fault Diagnosis ◽  
Data Storage ◽  
Grey Theory ◽  
Developmental Research ◽  
Software Platform ◽  
Diagnosis System ◽  
Fault Monitoring ◽  
On Line ◽  
Fault Diagnosis System

The system uses GRAP in Grey Theory to conduct fault diagnosis of fan and chooses LabWEV for software platform, developing a set of system aiming at fault monitoring on line and diagnosis of mine fan in order to guarantee the running state of fan continuously and efficiently . This system has functions of monitoring on line,fault diagnosis,fault warning,data storage, history inquiry and so on.

Assessment of airport performance using the grey theory method

2017 ◽  
Vol 7 (3) ◽  
pp. 426-436 ◽  
Author(s):  
Mohamed Ibrahim Eshtaiwi ◽  
Ibrahim A. Badi ◽  
Ali M. Abdulshahed ◽  
Turan Erman Erkan
Keyword(s):  
System Theory ◽  
Performance Evaluation ◽  
Service Quality ◽  
Design Methodology ◽  
Grey System Theory ◽  
Grey Theory ◽  
Theory Method ◽  
Grey System ◽  
Content Type ◽  
Overall Performance

Purpose Performance evaluation of airports or any other organisation is paramount for improving performance. The purpose of this paper is to evaluate and compare the performance of the three international airports in Libya (MJI, MRA, and LAQ airports) by considering five aspects of performance. Design/methodology/approach The considered aspects are airport service quality, airport operations, airport economy, safety and security, and environmental. The paper uses the grey system theory to assess these airports by summarizing the opinions of experts. Findings The finding of this study provides directions of the evaluated airports to take the correct actions to improve overall performance. Originality/value No literature has been found till date is to evaluate and compare the performance of the international airports in Libya.

Bus Priority at Intersections Based on Grey Theory Method of Drainage

ICTIS 2011 ◽  
2011 ◽  
Author(s):  
Youyang Wang ◽  
Wanchao Zhang ◽  
Xiaokuan Yang
Keyword(s):  
Grey Theory ◽  
Theory Method ◽  
Bus Priority

Study on Intelligence Fault Diagnosis Approach Based on Digraph Model and Application to Satellite Battery

2014 ◽  
Vol 889-890 ◽  
pp. 929-932
Author(s):  
Zi Qian Cui ◽  
Min Qiang Xu ◽  
Ri Xin Wang
Keyword(s):  
Fault Diagnosis ◽  
Threshold Value ◽  
Intelligent Fault Diagnosis ◽  
Battery System ◽  
Multiple Fault ◽  
Logical Operators ◽  
Diagnosis Method ◽  
Digraph Model ◽  
Diagnosis Approach

This article presents a SSDG---based intelligent fault diagnosis method. This method uses five signed threshold value modes to define nodes for carrying quantified information. This method establishes the SDGs of the system and its components, uses the based on rules method to diagnosis, then expands the diagnosing rule bank with logical operators to construct the diagnosing rule bank of the system. Applying in satellite battery system, this method can diagnosis the multiple fault, and batter explain, reworked and faster diagnosis.

Warp Degree Optimization of Automobile Bumper in Sequential Injection Molding

2013 ◽  
Vol 329 ◽  
pp. 176-181
Author(s):  
Jiang Dong Cao ◽  
Jian Bo Ding ◽  
Lei Gang Wang
Keyword(s):  
Large Scale ◽  
Grey Theory ◽  
Thin Wall ◽  
Sequential Injection ◽  
Injection Method ◽  
Packing Pressure ◽  
Relational Degree ◽  
Opening And Closing ◽  
Corporate Profits ◽  
Grey Relational

An automobile bumper is a large scale thin-wall plastic part. It is difficult for the weld lines of product to be removed by conventional injection method. Five valve gates in sequential injection have been used to control successfully weld lines to the border, but the warp degree of the product is too large. Through grey theory the packing pressure and time of valves opening and closing have been optimized. The grey relational degree have been calculated, the optimal process parameters group have been obtained by variance analysis. The result has been verified successfully in Moldflow software, the warp degree of product has been decreased greatly and satisfied the requirement of industry production. The injection method can be applied in actual production and increase corporate profits.

Hydraulic System Fault Diagnosis Based on EMD and Improved PSO-Elman ANN

2013 ◽  
Vol 284-287 ◽  
pp. 2936-2940
Author(s):  
Zeng Shou Dong ◽  
Xiao Yu Zhang ◽  
Jian Chao Zeng
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Convergence Rate ◽  
Hydraulic System ◽  
Learning Algorithm ◽  
Threshold Value ◽  
Pso Algorithm ◽  
Elman Neural Network ◽  
Neural Network Learning ◽  
Network Convergence

The element parameters of engineering machinery hydraulic system are detected, the fault eigenvector is extracted, and the information is applied to neural network fault diagnosis. Experience mode decomposition (EMD) is used to extract fault characteristic vectors in this paper, combined with the pressure, temperature and flow rate of dominant signal as neural network's inputs. In addition, the paper improves the Elman neural network learning algorithm by PSO algorithm. It can effectively increase network convergence rate and computing power. The particle swarm is used to optimize Elman neural network weights and the threshold value and then applied in the fault diagnosis system by training the network. The results show that the method increases the neural network convergence rate and reduces diagnoses error.

The Motor Fault Diagnosis Based on Neural Network and the Theory of D-S Evidence

2013 ◽  
Vol 683 ◽  
pp. 881-884 ◽  
Author(s):  
Chang Fei Sun ◽  
Zhi Shan Duan ◽  
Yang Yang ◽  
Miao Wang ◽  
Li Jie Hu
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Information Fusion ◽  
Threshold Value ◽  
Fusion Technology ◽  
Independent Evidence ◽  
Modes Of Failure ◽  
Processing Data ◽  
Single Feature ◽  
Diagnosis Method

In order to reduce the uncertainty of the traditional method that use a single parameter in the motor fault diagnosis, create a reliable motor fault diagnosis model by using multivariate information fusion technology and the combination of neural network and the theory of D-S evidence .First, fusion the information of many kinds of sensors, preliminary identify the modes of failure, find the information of different fault feature by analysing and processing data, establish the domain of feature. Then part diagnose the domain of feature by using neural network. The local diagnosis results form independent evidence body. Calculate the credibility of the fault distribution of each evidence body for recognition framework. It is difficult to discriminant fault types by directly using these reliability distribution. So choose appropriate D-S evidence formula to fusion each evidence body and further process and analyse the information of evidence. The credibility of the distribution is nearer and nearer to the judgement threshold value of fault types with one fusion, and the rest of the credibility distribution of the fault is more and more smaller. So the basic reliability distribution has better peak and separability, the diagnose results is more accurate, and finally achieve accurate diagnosis of the motor fault. The diagnosis example shows that the diagnosis method based on neural network and the theory of D-S evidence can realize comprehensive diagnosis of motor fault by using multi-resources information. The reliability and accuracy of this diagnosis method are far higher than that of the local diagnosis using single feature. It improves the precision of the motor fault diagnosis.

Study on Fault Diagnosis of Ship Power System Based on Multi-Source Information Fusion Technology

2014 ◽  
Vol 644-650 ◽  
pp. 3726-3729 ◽  
Author(s):  
Lei Liu ◽  
Xiu Qiang Li
Keyword(s):  
Fault Diagnosis ◽  
Power System ◽  
Information Fusion ◽  
Evidence Theory ◽  
Theory Method ◽  
Fusion Technology ◽  
Source Information ◽  
Ship Power System ◽  
The Impact ◽  
Electrical Data

This paper firstly establishes a mathematical model of ship power system, and then analyzes the characteristics and common faults of ship power system. D-S evidence theory method is used on research of common faults of the ship power system, to enhance the pertinence of fault diagnosis. By using multi-source information fusion diagnosis, the need for quantities of electrical data is reduced, and, it can effectively reduce the impact of protection or switch malfunction on the fault diagnosis of ship power system and thus improve the accuracy of diagnosis.

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