Abstract
Based on fuzzy logic theory, the information fusion technique at decision-making level is introduced for fault diagnosis system. A comprehensive fault diagnosis method based on fuzzy logic and D-S evidence theory is presented by making use of multi-sensor information fusion technique. In this method, the basic reliability distribution of evidence theory is obtained by using fuzzy membership function, which can significantly improve the accuracy of the fault diagnosis through taking full advantages of redundant and complementary fault information from all sensors. Finally the method is applied for fault diagnosis of ship diesel engine. Diagnostic results indicate that the technique is effective, greatly improving the efficiency of fault diagnosis.
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This work is partially supported by CNSF Grant #70471031.
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References
Waltz, E., Lilnas, A.: Multisensor Data Fusion. Artech House, Boston (1990)
Hall, D.L., Lilnas, J.: An Introduction to Multisensor Data Fusion. In: Proc. IEEE, vol. 85(1), pp. 6–23 (1997)
Varshney, P.K.: Multisensor Data Fusion. J. Eclec. Commu Eng 9(6), 245–253 (1997)
Luo, R.C., Gonzalez, R.C.: Data Fusion and Sensor Integration. In: Abidi, M.A. (ed.) State-of-the-art 1990s, Data Fusion in Robotics and Machine Intelligence, pp. 7–136. Academic Press, Inc. London (1992)
Liu, L.J., Yang, J.Y.: Model-based object classification using fused data. SPIE 1611, 65–73 (1991)
Han, J., Tao, Y.G.: Data Fusion Algorithm of Multi-sensor Based on D-S Evidential Theory and Fuzzy Mathematic. Chinese Journal of Scientific Instrument 21(6), 644–647 (2000)
He, Y., Wang, G.H., Lu, D.J.: Multi-sensor Information Fusion With Application. Publishing House of Electronics Industry, Beijing (2000)
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© 2007 Springer-Verlag Berlin Heidelberg
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Yang, G., Wu, X. (2007). Synthesized Fault Diagnosis Method Based on Fuzzy Logic and D-S Evidence Theory. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2007. Lecture Notes in Computer Science(), vol 4682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74205-0_106
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DOI: https://doi.org/10.1007/978-3-540-74205-0_106
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74201-2
Online ISBN: 978-3-540-74205-0
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