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Proceedings Paper

Fuzzy pattern recognition for online detection of engine misfire by measurement of crankshaft angular velocity
Author(s): Shiyuan Liu; Run-Sheng Du; Shuzi Yang
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Paper Abstract

A unique technique for the on-line detection of engine misfire has been developed, which is based on multiple feature integration through fuzzy pattern recognition. The technique requires the measurement of the instantaneous angular velocity signals. As more as 10 dimensionless features for the engine misfire detection are extracted by different ways. With the help of fuzzy pattern recognition, all the features are integrated together as a fuzzy vector, which identifies uniformly whether the engine is healthy or faulty at first, then locates the position of a misfiring cylinder or cylinders if it is necessary. The experimental results show that such a strategy is able to use reasonably the redundant and complementary information of all the features, and thus leads to better diagnostic reliability and efficiency.

Paper Details

Date Published: 9 May 2000
PDF: 5 pages
Proc. SPIE 4077, International Conference on Sensors and Control Techniques (ICSC 2000), (9 May 2000); doi: 10.1117/12.385630
Show Author Affiliations
Shiyuan Liu, Huazhong Univ. of Science and Technology (China)
Run-Sheng Du, Huazhong Univ. of Science and Technology (China)
Shuzi Yang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 4077:
International Conference on Sensors and Control Techniques (ICSC 2000)
Desheng Jiang; Anbo Wang, Editor(s)

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