Fault diagnosis for spark ignition engine based on multi-sensor data fusion
Fault diagnosis for spark ignition engine based on multi-sensor data fusion
- New search for: Tan Derong,
- New search for: Yan Xinping,
- New search for: Gao Song,
- New search for: Liu Zhenglin,
- New search for: Tan Derong,
- New search for: Yan Xinping,
- New search for: Gao Song,
- New search for: Liu Zhenglin,
In data fusion approaches, Dempster-Shafer (D-S) evidence theory offers an interesting tool to combine data from multi-sensor. The decision-level fusion based on Dempster-Shafer (D-S) evidence theory can process non-commensurate data and has robust operational performance, reduces ambiguity, increases confidence, and improves system reliability. This paper describes mainly a decision-level data fusion technique for fault diagnosis for electronically controlled spark ignition engines. A D-S evidence theory fault diagnosis model is founded, and the feature selection and extraction of fault signal is conducted. Experiments on a 462 mini engine show that the data fusion technique provides good engine fault diagnosis method.
Document information
Fault diagnosis for spark ignition engine based on multi-sensor data fusion
2005-01-01
819477 byte
Conference paper
Electronic Resource
English
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