Research on Information Fusion for Machine Potential Fault Operation and Maintenance
Abstract
:1. Introduction
2. Related Work
3. Information Fusion Based on D–S Evidence
3.1. D–S Evidence Theory
3.2. Lack of D–S Evidence Theory
3.3. Improved Evidence Theory
3.3.1. Weight of Evidence Reliability Based on Entropy
3.3.2. Weight of Evidence Consistency Based on Evidence Correlation Matrix
3.3.3. Reference Evidence Generation
3.3.4. Comprehensive Evidence Fusion Rule
4. Experiments
4.1. Reliability Weight Calculation
4.2. Consistency Weight Calculation
4.3. Reference Evidence Calculation
4.4. Comprehensive Evidence Fusion Generation
4.5. Results Analysis
5. Application and Verification
5.1. Problem Description
5.2. Establish Problem Identification Framework
5.3. Suspected Failure Probability Of Machines
5.4. Comparative Analysis
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Fusion Methods | Advantage | Disadvantage | Main Application Scenarios |
---|---|---|---|
Bayesian inferences | Simple calculation rules and fast calculation speed. | This method should be based on the accurate prior probability. | |
fuzzy reasoning | Information processing is closer to people’s thinking with strong explanatory ability. | There are a lot of subjective factors in design of reasoning rule and the standards are not unified. | |
Neural network | High data utilization and high accuracy. | Poor interpretability and high computational complexity. | |
D–S evidence | Suitable for the fusion of multi-source information with strong explanatory ability and flexible fusion mode. | The serious conflict between evidences is hard to resolve. |
Witness 1 | Witness 2 | Fusion Result | |
---|---|---|---|
A | 0.99 | 0.00 | 0.00 |
B | 0.01 | 0.01 | 1.00 |
C | 0.00 | 0.99 | 0.00 |
Witness 1 | Witness 2 | |
---|---|---|
A | 0.60 | 0.60 |
B | 0.40 | 0.20 |
C | 0.00 | 0.20 |
Witness 1 | Witness 2 | Witness 3 | Witness 4 | D–S Fusion Result | |
---|---|---|---|---|---|
A | 0.90 | 0.95 | 0.95 | 0.00 | 0.00 |
B | 0.09 | 0.04 | 0.03 | 0.03 | 0.63 |
C | 0.01 | 0.01 | 0.02 | 0.97 | 0.37 |
0.1553 | 0.0971 | 0.1008 | 0.0585 |
0.2076 | 0.2547 | 0.2517 | 0.2860 |
0.2734 | 0.2538 | 0.4723 | 0.005 |
Reference Evidence | |||
---|---|---|---|
0.6680 | 0.0450 | 0.2870 | |
0.9362 | 0.0490 | 0.0148 | |
0.9381 | 0.0469 | 0.0150 |
Evidence Fusion Result | |||
---|---|---|---|
0.0000 | 0.6255 | 0.3745 | |
0.6680 | 0.0450 | 0.2870 | |
0.9362 | 0.0490 | 0.0148 | |
0.9381 | 0.0469 | 0.0150 |
Order | Probability | Order | Probability |
---|---|---|---|
0.3309 | 0.0376 | ||
0.3176 | 0.0092 | ||
0.1713 | 0.0083 | ||
0.0793 | 0.0054 | ||
0.0376 | 0.0027 |
Order | Probability | Order | Probability |
---|---|---|---|
0.2547 | 0.0217 | ||
0.1456 | 0.0235 | ||
0.1315 | 0.1543 | ||
0.0021 | 0.0122 | ||
0.2111 | 0.0433 |
Order | Probability | Order | Probability |
---|---|---|---|
0.2958 | 0.0303 | ||
0.2385 | 0.0158 | ||
0.1530 | 0.0755 | ||
0.0438 | 0.0085 | ||
0.1175 | 0.0214 |
Order | Probability | Order | Probability |
---|---|---|---|
0.5149 | 0.005 | ||
0.2826 | 0.001 | ||
0.1377 | 0.008 | ||
0.0010 | 0.000 | ||
0.0486 | 0.000 |
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Xu, W.; Wan, Y.; Zuo, T.-Y.; Sha, X.-M. Research on Information Fusion for Machine Potential Fault Operation and Maintenance. Symmetry 2020, 12, 375. https://doi.org/10.3390/sym12030375
Xu W, Wan Y, Zuo T-Y, Sha X-M. Research on Information Fusion for Machine Potential Fault Operation and Maintenance. Symmetry. 2020; 12(3):375. https://doi.org/10.3390/sym12030375
Chicago/Turabian StyleXu, Wei, Yi Wan, Tian-Yu Zuo, and Xin-Mei Sha. 2020. "Research on Information Fusion for Machine Potential Fault Operation and Maintenance" Symmetry 12, no. 3: 375. https://doi.org/10.3390/sym12030375