Multi-information Fusion Fault Diagnosis Based on KNN and Improved Evidence Theory

2021 ◽  
Author(s):  
Yuwei Liu ◽  
Yuqiang Cheng ◽  
Zhenzhen Zhang ◽  
Jianjun Wu
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory

Fault Classification of Hydroelectric Generating Unit Based on Improved Evidence Theory

2014 ◽  
Vol 7 (1) ◽  
pp. 78-83 ◽  
Author(s):  
Jiatang Cheng ◽  
Li Ai ◽  
Zhimei Duan ◽  
Yan Xiong
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
Fault Classification ◽  
Fusion Method ◽  
Inconsistent Result ◽  
High Conflict

Aiming at the problem of the conventional vibration fault diagnosis technology with inconsistent result of a hydroelectric generating unit, an information fusion method was proposed based on the improved evidence theory. In this algorithm, the original evidence was amended by the credibility factor, and then the synthesis rule of standard evidence theory was utilized to carry out information fusion. The results show that the proposed method can obtain any definitive conclusion even if there is high conflict evidence in the synthesis evidence process, and may avoid the divergent phenomenon when the consistent evidence is fused, and is suitable for the fault classification of hydroelectric generating unit.

The Research on Fault Diagnosis of Civil Aircraft Information Fusion Based on the Evidence Theory

2014 ◽  
Vol 983 ◽  
pp. 392-395
Author(s):  
Xue Peng
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
Similarity Coefficient ◽  
Maintenance Cost ◽  
Civil Aircraft ◽  
Fusion Theory ◽  
Improved Methods

In this paper, information fusion theory based on the evidence theory is used in the fault diagnosis field of civil aircraft. Considering the conflict resulted from information fusion in some certain conditions, two improved methods, including Similarity Coefficient and Full Factor are put forward to solve the conflict problems. In a nutshell, the methods are pretty effective and reliable, and the maintenance cost of airlines can be reduced obviously.

scholarly journals Composite Fault Diagnosis for Rotating Machinery of Large Units Based on Evidence Theory and Multi-Information Fusion

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Naiquang Su ◽  
Xiao Li ◽  
Qinghua Zhang ◽  
Zhiqiang Huo ◽  
Xavier Chiementin
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Large Scale ◽  
Evidence Theory ◽  
Rotating Machinery ◽  
Uncertain Information ◽  
Sample Distribution ◽  
Multiple Data ◽  
Diagnosis Method ◽  
Conflict Information

Due to the complexity of the structure and process of large-scale petrochemical equipment, different fault characteristics are mixed and present multiple couplings and ambiguities, leading to the difficulty in identifying composite faults in rotating machinery. This paper proposes a composite faults diagnosis method for rotating machinery of the large unit based on evidence theory and multi-information fusion. The evidence theory and multi-information fusion method mainly deal with multisource information and conflict information, synthesize multiple uncertain information, and obtain synthetic information from multiple data sources. To detect faults in rotating machinery, the dimensionless index ranges of composite faults are first used to form a feature set as the reference. Then, a two-sample distribution test is applied to compare the known fault samples with the tested fault samples, and the maximum statistical distance is used. Finally, the multiple maximum statistical distances are fused by evidence theory and identifying fault types based on the fusion result. The proposed method was applied to the large petrochemical unit simulation experiment system, the results of which showed that our proposed method could accurately identify composite faults and provide maintenance guidance for composite fault diagnosis.

An Information Fusion Model Based on Dempster–Shafer Evidence Theory for Equipment Diagnosis

2017 ◽  
Vol 4 (2) ◽  
Author(s):  
Dengji Zhou ◽  
Tingting Wei ◽  
Huisheng Zhang ◽  
Shixi Ma ◽  
Fang Wei
Keyword(s):  
Fault Diagnosis ◽  
Diagnostic Accuracy ◽  
Information Fusion ◽  
Evidence Theory ◽  
Diagnostic System ◽  
Fusion Model ◽  
First Case ◽  
Evidence Algorithm ◽  
Data Layer ◽  
Analytical System

An abnormal operating effect can be caused by different faults, and a fault can cause different abnormal effects. An information fusion model, with hybrid-type fusion frame, is built in this paper, so as to solve this problem. This model consists of data layer, feature layer and decision layer, based on an improved Dempster–Shafer (D-S) evidence algorithm. After the data preprocessing based on event reasoning in data layer and feature layer, the information will be fused based on the new algorithm in decision layer. Application of this information fusion model in fault diagnosis is beneficial in two aspects, diagnostic applicability and diagnostic accuracy. Additionally, this model can overcome the uncertainty of information and equipment to increase diagnostic accuracy. Two case studies are implemented by this information fusion model to evaluate it. In the first case, fault probabilities calculated by different methods are adopted as inputs to diagnose a fault, which is quite different to be detected based on the information from a single analytical system. The second case is about sensor fault diagnosis. Fault signals are planted into the measured parameters for the diagnostic system, to test the ability to consider the uncertainty of measured parameters. The case study result shows that the model can identify the fault more effectively and accurately. Meanwhile, it has good expansibility, which may be used in more fields.

Approach of Combination of Weighted Evidence Based on Evidential Closeness Degree and its Application

2012 ◽  
Vol 630 ◽  
pp. 377-382
Author(s):  
Zhuan Zhe Zhao ◽  
Min Ping Jia ◽  
Kang He ◽  
Hao Zhou ◽  
Yu Jie Ding
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Calculation Method ◽  
Evidence Theory ◽  
Weights Of Evidence ◽  
Evidence Based ◽  
Combination Rules ◽  
New Approach ◽  
Symptom Domains ◽  
Diagnosis Model

Since the information fusion based on Dempster-Shafer(D-S) evidence theory involves counter-intuitive behaviors when evidences highly conflict, a new approach of combination of weighted based on evidence closeness degree is proposed and applied in fault diagnosis．Firstly, the calculation method of evidence distance and evidential closeness degree as well as its revision are given according to the relevance and importance of various evidence sources; Then the closeness degree is normalized in order to obtain the weights of evidence sources. And the information fusion is realized with the base of weighted evidence theory. Finally, the approach is applied to fault diagnosis model of multi-evidences (multi-symptom domains or multi-sensors) in this paper. In the experiments, the proposed approach is compared with the existing combination rules and the results show that the reliability and accuracy of fault diagnosis are significantly improved and its uncertainty is decreased remarkably. The fusion problem given above is also solved effectively.

scholarly journals The Comprehensive Diagnostic Method Combining Rough Sets and Evidence Theory

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Guang Yang ◽  
Shuofeng Yu ◽  
Shan Lu ◽  
George Smith
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Rough Sets ◽  
Evidence Theory ◽  
Accuracy Rate ◽  
Complementary Information ◽  
High Conflict ◽  
Evidence Combination ◽  
Basic Probability ◽  
Inference Strategy

Abstract To solve the difficulties in practice caused by the subjectivity, relativity and evidence combination focus element explosion during the process of solving the uncertain problems of fault diagnosis with evidence theory, this paper proposes a fault diagnosis inference strategy by integrating rough sets with evidence theory along with the theories of information fusion and mete-synthesis. By using rough sets, redundancy of characteristic data is removed and the unrelated essential characteristics are extracted, the objective way of basic probability assignment is proposed, and an evidence synthetic method is put forward to solve high conflict evidence. The method put forward in this paper can improve the accuracy rate of fault diagnosis with the redundant and complementary information of various faults by synthesizing all evidences with the rule of the composition of evidence theory. Besides, this paper proves the feasibility and validity of experiments and the efficiency in improving fault diagnosis.

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